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Please note you do not have access to teaching notes, a case study on the implementation of green building construction in gauteng province, south africa.

Management of Environmental Quality

ISSN : 1477-7835

Article publication date: 21 February 2020

Issue publication date: 16 April 2020

Green building is a relatively new concept with limited applications in property development in South Africa. The objectives of this study are therefore threefold: identify key green building principles considered by property developers, establish the benefits of implementing the principles and determine the barriers to its applications.

Design/methodology/approach

The study adopted a case study of two Green Star South Africa (SA)-certified buildings in Sandton, Johannesburg. These are Alexander Forbes building, and Ernst & Young Eris Towers. The two certified buildings were purposefully selected because of the insightful information they provide regarding application of green building principles. The main themes investigated in the cases are environmental awareness, green building principles applications, as well as benefits and barriers of green building. A total of six interviewees from the contractors', property developers', environmental/green building consultants' and sustainability consultants' organizations who were involved in the implementation of green building principles in the two cases provided the qualitative data for the study. The qualitative data were supplemented with data relating to the two case studies obtained from the ‘Earth Works for a Sustainable Built Environment’. The interviews were arranged over a period of two months, and each interview took between 20 and 30 minutes. Analysis of the data was done through a phenomenological interpretation of the qualitative opinions expressed by the interviewees.

Key green building principles comprising energy efficiency, water efficiency, resource efficiency, occupants' health and well-being and sustainable site development were implemented in the two cases. The fact that the buildings were rated 4-star enabled inference to be drawn that the implementation of the principles was less than 60 per cent. Energy efficiency of 35 per cent indicated in Case I suggests that the level is consistent with the South African green building standard of 25 per cent to 50 per cent. However, the energy and water efficiency assessment of the building were based on projections rather than on ongoing monitoring and evaluation of the buildings' performance. Moreover, perceived saving in operational cost was identified as dominant driver to green building principles implementation. Conversely, lack of government incentives and absence of reliable benchmarking data regarding performance of green buildings were major barriers to its full implementation.

Practical implications

The findings of this study provide important implications to the developers and government on the application of green building principles. In the first place, the evidence that initial high cost premium could be off settled by long- term saving on operational costs as a result of use of local materials, energy and water savings as well as use of recycled material, as implemented in the two case projects, would improve investment decision in green building by developers. The understanding of the drivers and barriers to implementation of green building principles also has implications for guiding government policies and programmes towards green building.

Originality/value

The significance of this study stems from the fact that limited studies, especially in the South African context, have indicated the drivers and barriers to the implementation of green building principles. The case study approach adopted gave a novelty to the study by providing hands-on information from the stakeholders who were known to have played specific roles in the application of green building. The findings indicated that initial high cost premium was not a consideration in developers' choice of green building which justifies the possibility of a costlier product when factors such as environmental sustainability benefit is considered to be ultimate. The study thus suggests further research involving larger cases on energy efficiency, water efficiency and costs of green buildings compared to the conventional type to bring the findings to a broader perspective and assist to benchmark data for green building assessment.

• Construction
• Environment
• Green building
• Sustainability
• Property development

Masia, T. , Kajimo-Shakantu, K. and Opawole, A. (2020), "A case study on the implementation of green building construction in Gauteng province, South Africa", Management of Environmental Quality , Vol. 31 No. 3, pp. 602-623. https://doi.org/10.1108/MEQ-04-2019-0085

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A comprehensive review on green buildings research: bibliometric analysis during 1998–2018

• Environmental Concerns and Pollution control in the Context of Developing Countries
• Published: 16 February 2021
• Volume 28 , pages 46196–46214, ( 2021 )

Cite this article

• Li Ying 1 , 2 ,
• Rong Yanyu   ORCID: orcid.org/0000-0003-0722-8510 1 , 3 ,
• Umme Marium Ahmad 1 ,
• Wang Xiaotong 1 , 3 ,
• Zuo Jian 4 &
• Mao Guozhu 1 , 3  

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53 Citations

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Buildings account for nearly 2/5ths of global energy expenditure. Due to this figure, the 90s witnessed the rise of green buildings (GBs) that were designed with the purpose of lowering the demand for energy, water, and materials resources while enhancing environmental protection efforts and human well-being over time. This paper examines recent studies and technologies related to the design, construction, and overall operation of GBs and determines potential future research directions in this area of study. This global review of green building development in the last two decades is conducted through bibliometric analysis on the Web of Science, via the Science Citation Index and Social Sciences Citation Index databases. Publication performance, countries’ characteristics, and identification of key areas of green building development and popular technologies were conducted via social network analysis, big data method, and S-curve predictions. A total of 5246 articles were evaluated on the basis of subject categories, journals’ performance, general publication outputs, and other publication characteristics. Further analysis was made on dominant issues through keyword co-occurrence, green building technologies by patent analysis, and S-curve predictions. The USA, China, and the UK are ranked the top three countries where the majority of publications come from. Australia and China had the closest relationship in the global network cooperation. Global trends of the top 5 countries showed different country characteristics. China had a steady and consistent growth in green building publications each year. The total publications on different cities had a high correlation with cities’ GDP by Baidu Search Index. Also, barriers and contradictions such as cost, occupant comfort, and energy consumption were discussed in developed and developing countries. Green buildings, sustainability, and energy efficiency were the top three hotspots identified through the whole research period by the cluster analysis. Additionally, green building energy technologies, including building structures, materials, and energy systems, were the most prevalent technologies of interest determined by the Derwent Innovations Index prediction analysis. This review reveals hotspots and emerging trends in green building research and development and suggests routes for future research. Bibliometric analysis, combined with other useful tools, can quantitatively measure research activities from the past and present, thus bridging the historical gap and predicting the future of green building development.

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Avoid common mistakes on your manuscript.

Introduction

Rapid urban development has resulted in buildings becoming a massive consumer of energy (Yuan et al. 2013 ), liable for 39% of global energy expenditure and 68% of total electricity consumption in the USA (building). In recent years, green buildings (GBs) have become an alternative solution, rousing widespread attention. Also referred to as sustainable buildings, low energy buildings, and eco-buildings, GBs are designed to reduce the strain on environmental resources as well as curb negative effects on human health by efficiently using natural resources, reducing garbage, and ensuring the residents’ well-being through improved living conditions ( Agency USEP Indoor Air Quality ; Building, n.d ). As a strategy to improve the sustainability of the construction industry, GBs have been widely recognized by governments globally, as a necessary step towards a sustainable construction industry (Shen et al. 2017 ).

Zuo and Zhao ( 2014 ) reviewed the current research status and future development direction of GBs, focusing on connotation and research scope, the benefit-difference between GBs and traditional buildings, and various ways to achieve green building development. Zhao et al. ( 2019 ) presented a bibliometric report of studies on GBs between 2000 and 2016, identifying hot research topics and knowledge gaps. The verification of the true performance of sustainable buildings, the application of ICT, health and safety hazards in the development of green projects, and the corporate social responsibility were detected as future agenda. A scientometrics review of research papers on GB sources from 14 architectural journals between 1992 and 2018 was also presented (Wuni et al. 2019a ). The study reported that 44% of the world participated in research focusing on green building implementation; stakeholder management; attitude assessment; regulations and policies; energy efficiency assessment; sustainability performance assessment; green building certification, etc.

With the transmission of the COVID-19 virus, society is now aware of the importance of healthy buildings. In fact, in the past 20 years, the relationship between the built environment and health has aroused increasing research interest in the field of building science. Public spaces and dispersion of buildings in mixed-use neighborhoods are promoted. Furthermore, telecommuting has become a trend since the COVID-19 pandemic, making indoor air quality even more important in buildings, now (Fezi 2020 ).

The system for evaluating the sustainability of buildings has been established for nearly two decades. But, systems dedicated to identifying whether buildings are healthy have only recently appeared (McArthur and Powell 2020 ). People are paying more and more attention to health factors in the built environment. This is reflected in the substantial increase in related academic papers and the increase in health building certification systems such as WELE and Fitwel (McArthur and Powell 2020 ).

Taking the above into consideration, the aim of this study is to examine the stages of development of GBs worldwide and find the barriers and the hotpots in global trends. This study may be beneficial to foreign governments interested in promoting green building and research in their own nations.

Methodology

Overall description of research design.

Since it is difficult to investigate historical data and predict global trends of GBs, literature research was conducted to analyze their development. The number of published reports on a topic in a particular country may influence the level of industrial development in that certain area (Zhang et al. 2017 ). The bibliometric analysis allows for a quantitative assessment of the development and advancement of research related to GBs and where they are from. Furthermore, it has been shown that useful data has been gathered through bibliometrics and patent analysis (Daim et al. 2006 ).

In this report, the bibliometric method, social network analysis (SNA), CiteSpace, big data method, patent analysis, and S-curve analysis are used to assess data.

Bibliometrics analysis

Bibliometrics, a class of scientometrics, is a tool developed in 1969 for library and information science. It has since been adopted by other fields of study that require a quantitative assessment of academic articles to determine trends and predict future research scenarios by compiling output and type of publication, title, keyword, author, institution, and countries data (Ho 2008 ; Li et al. 2017 ).

Social network analysis

Social network analysis (SNA) is applied to studies by modeling network maps using mathematics and statistics (Mclinden 2013 ; Ye et al. 2013 ). In the SNA, nodes represent social actors, while connections between actors stand for their relationships (Zhang et al. 2017 ). Correlations between two actors are determined by their distance from each other. There is a variety of software for the visualization of SNA such as Gephi, Vosviewer, and Pajek. In this research, “Pajek” was used to model the sequence of and relationships between the objects in the map (Du et al. 2015 ).

CiteSpace is an open-source Java application that maps and analyzes trends in publication statistics gathered from the ISI-Thomson Reuters Scientific database and produces graphic representations of this data (Chen 2006 ; Li et al. 2017 ). Among its many functions, it can determine critical moments in the evolution of research in a particular field, find patterns and hotspots, locate areas of rapid growth, and breakdown the network into categorized clusters (Chen 2006 ).

Big data method

The big data method, with its 3V characters (volume, velocity, and variety), can give useful and accurate information. Enormous amounts of data, which could not be collected or computed manually through conventional methods, can now be collected through public data website. Based on large databases and machine learning, the big data method can be used to design, operate, and evaluate energy efficiency and other index combined with other technologies (Mehmood et al. 2019 ). The primary benefit of big data is that the data is gathered from entire populations as opposed to a small sample of people (Chen et al. 2018 ; Ho 2008 ). It has been widely used in many research areas. In this research, we use the “Baidu Index” to form a general idea of the trends in specific areas based on user interests. The popularity of the keywords could imply the user’s behavior, user’s demand, user’s portrait, etc. Thus, we can analyze the products or events to help with developing strategies. However, it must be noted that although big data can quantitatively represent human behavior, it cannot determine what motivates it. With the convergence of big data and technology, there are unprecedented applications in the field of green building for the improved indoor living environment and controlled energy consumption (Marinakis 2020 ).

• Patent analysis

Bibliometrics, combined with patent analysis, bridges gaps that may exist in historical data when predicting future technologies (Daim et al. 2006 ). It is a trusted form of technical analysis as it is supported by abundant sources and commercial awareness of patents (Guozhu et al. 2018 ; Yoon and Park 2004 ). Therefore, we used patent analysis from the Derwent patent database to conduct an initial analysis and forecast GB technologies.

There are a variety of methods to predict the future development prospects of a technology. Since many technologies are developed in accordance with the S-curve trend, researchers use the S-curve to observe and predict the future trend of technologies (Bengisu and Nekhili 2006 ; Du et al. 2019 ; Liu and Wang 2010 ). The evolution of technical systems generally goes through four stages: emerging, growth, maturity, and decay (saturation) (Ernst 1997 ). We use the logistics model (performed in Loglet Lab 4 software developed by Rockefeller University) to simulate the S-curve of GB-related patents to predict its future development space.

Data collection

The Web of Science (WOS) core collection database is made up of trustworthy and highly ranked journals. It is considered the leading data portal for publications in many fields (Pouris and Pouris 2011 ). Furthermore, the WOS has been cited as the main data source in many recent bibliometric reviews on buildings (Li et al. 2017 ).

Access to all publications used in this paper was attained through the Science Citation Index-Expanded and the Social Sciences Citation Index databases. Because there is no relevant data in WOS before 1998, our examination focuses on 1998 to 2018. With consideration of synonyms, we set a series of green building-related words (see Appendix ) in titles, abstracts, and keywords for bibliometric analysis. For example, sustainable, low energy, zero energy, and low carbon can be substituted for green; housing, construction, and architecture can be a substitute for building (Zuo and Zhao 2014 ).

Analytical procedure

The study was conducted in three stages; data extraction was the first step where all the GB-related words were screened in WOS. Afterwards, some initial analysis was done to get a complete idea of GB research. Then, we made a further analysis on countries’ characteristics, dominant issues, and detected technology hotspots via patent analysis (Fig. 1 ).

Analytical procedure of the article

Results and analysis

General results.

Of the 6140 publications searched in the database, 88.67% were articles, followed by reviews (6.80%), papers (3.72%), and others (such as editorial materials, news, book reviews). Most articles were written in English (96.78%), followed by German (1.77%), Spanish (0.91%), and other European languages. Therefore, we will only make a further analysis of the types of articles in English publications.

The subject categories and their distribution

The SCI-E and SSCI database determined 155 subjects from the pool of 5246 articles reviewed, such as building technology, energy and fuels, civil engineering, environmental, material science, and thermodynamics, which suggests green building is a cross-disciplinary area of research. The top 3 research areas of green buildings are Construction & Building Technology (36.98%), Energy & Fuels (30.39%), and Engineering Civil (29.49%), which account for over half of the total categories.

The journals’ performance

The top 10 journals contained 38.8% of the 5246 publications, and the distribution of their publications is shown in Fig. 2 . Impact factors qualitatively indicate the standard of journals, the research papers they publish, and researchers associated with those papers (Huibin et al. 2015 ). Below, we used 2017 impact factors in Journal Citation Reports (JCR) to determine the journal standards.

The performance of top10 most productive journals

Publications on green building have appeared in a variety of titles, including energy, building, environment, materials, sustainability, indoor built environment, and thermal engineering. Energy and Buildings, with its impact factor 4.457, was the most productive journal apparently from 2009 to 2017. Sustainability (IF = 2.075) and Journal of Cleaner Production (IF = 5.651) rose to significance rapidly since 2015 and ranked top two journals in 2018.

Publication output

The total publication trends from 1998 to 2018 are shown in Fig. 3 , which shows a staggering increase across the 10 years. Since there was no relevant data before 1998, the starting year is 1998. Before 2004, the number of articles published per year fluctuated. The increasing rate reached 75% and 68% in 2004 and 2007, respectively, which are distinguished in Fig. 3 that leads us to believe that there are internal forces at work, such as appropriate policy creation and enforcement by concerned governments. There was a constant and steady growth in publications after 2007 in the worldwide view.

The number of articles published yearly, between 1998 and 2018

The characteristics of the countries

Global distribution and global network were analyzed to illustrate countries’ characteristics. Many tools such as ArcGIS, Bibexcel, Pajek, and Baidu index were used in this part (Fig. 4 ).

Analysis procedure of countries’ characteristics

Global distribution of publications

By extracting the authors’ addresses (Mao et al. 2015 ), the number of publications from each place was shown in Fig. 5 and Table 1 . Apparently, the USA was the most productive country accounting for 14.98% of all the publications. China (including Hong Kong and Taiwan) and the UK followed next by 13.29% and 8.27% separately. European countries such as Italy, Spain, and Germany also did a lot of work on green building development.

Global geographical distribution of the top 20 publications based on authors’ locations

Global research network

Global networks illustrate cooperation between countries through the analysis of social networks. Academic partnerships among the 10 most productive countries are shown in Fig. 6 . Collaboration is determined by the affiliation of the co-authors, and if a publication is a collaborative research, all countries or institutions will benefit from it (Bozeman et al. 2013 ). Every node denotes a country and their size indicates the amount of publications from that country. The lines linking the nodes denote relationships between countries and their thickness indicates the level of collaboration (Mao et al. 2015 ).

The top 10 most productive countries had close academic collaborative relationships

It was obvious that China and Australia had the strongest linking strength. Secondly, China and the USA, China, and the UK also had close cooperation with each other. Then, the USA with Canada and South Korea followed. The results indicated that cooperation in green building research was worldwide. At the same time, such partnerships could help countries increase individual productivity.

Global trend of publications

The time-trend analysis of academic inputs to green building from the most active countries is shown in Fig. 7 .

The publication trends of the top five countriesbetween 1998 and 2018 countries areshown in Fig 7 .

Before 2007, these countries showed little growth per year. However, they have had a different, growing trend since 2007. The USA had the greatest proportion of publications from 2007, which rose obviously each year, reaching its peak in 2016 then declined. The number of articles from China was at 13 in 2007, close to the USA. Afterwards, there was a steady growth in China. Not until 2013 did China have a quick rise from 41 publications to 171 in 2018. The UK and Italy had a similar growth trend before 2016 but declined in the last 2 years.

Further analysis on China, the USA, and the UK

Green building development in china, policy implementation in china.

Green building design started in China with the primary goal of energy conservation. In September 2004, the award of “national green building innovation” of the Ministry of Construction was launched, which kicked off the substantive development of GB in China. As we can see from Fig. 7 , there were few publications before 2004 in China. In 2004, there were only 4 publications on GB.

The Ministry of Construction, along with the Ministry of Science and Technology, in 2005, published “The Technical Guidelines for Green Buildings,” proposing the development of GBs (Zhang et al. 2018 ). In June 2006, China had implemented the first “Evaluation Standard for Green Building” (GB/T 50378-2006), which promoted the study of the green building field. In 2007, the demonstration of “100 projects of green building and 100 projects of low-energy building” was launched. In August 2007, the Ministry of Construction issued the “Green Building Assessment Technical Regulations (try out)” and the “Green Building Evaluation Management,” following Beijing, Tianjin, Chongqing, and Shanghai, more than 20 provinces and cities issued the local green building standards, which promoted GBs in large areas in China.

At the beginning of 2013, the State Council issued the “Green Building Action Plan,” so the governments at all levels continuously issued incentive policies for the development of green buildings (Ye et al. 2015 ). The number of certified green buildings has shown a blowout growth trend throughout the country, which implied that China had arrived at a new chapter of development.

In August 2016, the Evaluation Standard for Green Renovation of Existing Buildings was released, encouraging the rise of residential GB research. Retrofitting an existing building is often more cost-effective than building a new facility. Designing significant renovations and alterations to existing buildings, including sustainability measures, will reduce operating costs and environmental impacts and improve the building’s adaptability, durability, and resilience.

At the same time, a number of green ecological urban areas have emerged (Zhang et al. 2018 ). For instance, the Sino-Singapore Tianjin eco-city is a major collaborative project between the two governments. Located in the north of Tianjin Binhai New Area, the eco-city is characterized by salinization of land, lack of freshwater, and serious pollution, which can highlight the importance of eco-city construction. The construction of eco-cities has changed the way cities develop and has provided a demonstration of similar areas.

China has many emerging areas and old centers, so erecting new, energy efficiency buildings and refurbishing existing buildings are the best steps towards saving energy.

Baidu Search Index of “green building”

In order to know the difference in performance among cities in China, this study employs the big data method “Baidu Index” for a smart diagnosis and assessment on green building at finer levels. “Baidu Index” is not equal to the number of searches but is positively related to the number of searches, which is calculated by the statistical model. Based on the keyword search of “green building” in the Baidu Index from 2013 to 2018, the top 10 provinces or cities were identified (Fig. 8 ).

Baidu Search Index of green building in China 2013–2018 from high to low

The top 10 search index distributes the east part and middle part of China, most of which are the high GDP provinces (Fig. 9 ). Economically developed cities in China already have a relatively mature green building market. Many green building projects with local characteristics have been established (Zhang et al. 2018 ).

TP GDP & Search Index were highly related

We compared the city search index (2013–2018) with the total publications of different cities by the authors’ address and the GDP in 2018. The correlation coefficient between the TP and the search index was 0.9, which means the two variables are highly related. The correlation coefficient between the TP and GDP was 0.73, which also represented a strong relationship. We inferred that cities with higher GDP had more intention of implementation on green buildings. The stronger the local GDP, the more relevant the economic policies that can be implemented to stimulate the development of green buildings (Hong et al. 2017 ). Local economic status (Yang et al. 2018 ), property developer’s ability, and effective government financial incentives are the three most critical factors for green building implementation (Huang et al. 2018 ). However, Wang et al. ( 2017 ) compared the existing green building design standards and found that they rarely consider the regional economy. Aiming at cities at different economic development phases, the green building design standards for sustainable construction can effectively promote the implementation of green buildings. Liu et al. ( 2020 ) mainly discussed the impact of sustainable construction on GDP. According to the data, there is a strong correlation between the percentage of GDP increments in China and the amount of sustainable infrastructure (Liu et al. 2020 ). The construction of infrastructure can create jobs and improve people’s living standards, increasing GDP as a result (Liu et al. 2020 ).

Green building development in the USA and the UK

The sign that GBs were about to take-off occurred in 1993—the formation of the United States Green Building Council (USGBC), an independent agency. The promulgation of the Energy Policy Act 2005 in the USA was the key point in the development of GBs. The Energy Policy Act 2005 paid great attention to green building energy saving, which also inspired publications on GBs.

Leadership in Energy and Environmental Design (LEED), a popular metric for sustainable buildings and homes (Jalaei and Jrade 2015 ), has become a thriving business model for green building development. It is a widely used measure of how buildings affect the environment.

Another phenomenon worth discussion, combined with Fig. 7 , the increasing rate peaked at 75% in 2004 and 68% in 2007 while the publications of the UK reached the peak in 2004 and 2007. The UK Green Building Council (UKGBC), a United Kingdom membership organization, created in 2007 with regard to the 2004 Sustainable Building Task Group Report: Better Buildings - Better Lives, intends to “radically transform,” all facets of current and future built environment in the UK. It is predicted that the establishment of the UKGBC promoted research on green buildings.

From the China, the USA, and the UK experience, it is predicted that the foundation of a GB council or the particular projects from the government will promote research in this area.

Barriers and contradicts of green building implement

On the other hand, it is obvious that the USA, the UK, and Italian publications have been declining since 2016. There might be some barriers and contradicts on the adoption of green buildings for developed countries. Some articles studied the different barriers to green building in developed and developing countries (Chan et al. 2018 ) (Table 2 ). Because the fraction of energy end-uses is different, the concerns for GBs in the USA, China, and the European Union are also different (Cao et al. 2016 ).

It is regarded that higher cost is the most deterring barrier to GB development across the globe (Nguyen et al. 2017 ). Other aspects such as lack of market demand and knowledge were also main considerations of green building implementation.

As for market demand, occupant satisfaction is an important factor. Numerous GB post-occupancy investigations on occupant satisfaction in various communities have been conducted.

Paul and Taylor ( 2008 ) surveyed personnel ratings of their work environment with regard to ambience, tranquility, lighting, sound, ventilation, heat, humidity, and overall satisfaction. Personnel working in GBs and traditional buildings did not differ in these assessments. Khoshbakht et al. ( 2018 ) identified two global contexts in spite of the inconclusiveness: in the west (mainly the USA and Britain), users experienced no significant differences in satisfaction between green and traditional buildings, whereas, in the east (mainly China and South Korea), GB user satisfaction is significantly higher than traditional building users.

Dominant issues

The dominant issues on different stages.

Bibliometric data was imported to CiteSpace where a three-stage analysis was conducted based on development trends: 1998–2007 initial development; 2008–2015 quick development; 2016–2018 differentiation phase (Fig. 10 ).

Analysis procedure of dominant issues

CiteSpace was used for word frequency and co-word analysis. The basic principle of co-word analysis is to count a group of words appearing at the same time in a document and measure the close relationship between them by the number of co-occurrences. The top 50 levels of most cited or occurred items from each slice (1998 to 2007; 2008 to 2015; 2016 to 2018) per year were selected. After merging the similar words (singular or plural form), the final keyword knowledge maps were generated as follows.

Initial phase (1998–2007)

In the early stage (Fig. 11 ), “green building” and “sustainability” were the main two clusters. Economics and “environmental assessment method” both had high betweenness centrality of 0.34 which were identified as pivotal points. Purple rings denote pivotal points in the network. The relationships in GB were simple at the initial stage of development.

Co-word analysis from 1998–2007

Sustainable construction is further enabled with tools that can evaluate the entire life cycle, site preparation and management, materials and their reusability, and the reduction of resource and energy consumption. Environmental building assessment methods were incorporated to achieve sustainable development, especially at the initial project appraisal stage (Ding 2008 ). Green Building Challenge (GBC) is an exceptional international research, development, and dissemination effort for developing building environmental performance assessments, primarily to help researchers and practitioners in dealing with difficult obstacles in assessing performance (Todd et al. 2001 ).

Quick development (2008–2015)

In the rapid growing stage (Fig. 12 ), pivot nodes and cluster centers were more complicated. Besides “green building” and “sustainability,” “energy efficiency” was the third hotspot word. The emergence of new vocabulary in the keyword network indicated that the research had made progress during 2008 – 2015. Energy performance, energy consumption, natural ventilation, thermal comfort, renewable energy, and embodied energy were all energy related. Energy becomes the most attractive field in achieving sustainability and green building. Other aspects such as “life cycle assessment,” “LEED,” and “thermal comfort” became attractive to researchers.

Co-word analysis from 2008–2015

The life cycle assessment (LCA) is a popular technique for the analysis of the technical side of GBs. LCA was developed from environmental assessment and economic analysis which could be a useful method to evaluate building energy efficiency from production and use to end-use (Chwieduk 2003 ). Much attention has been paid to LCA because people began to focus more on the actual performance of the GBs. Essentially, LCA simplifies buildings into systems, monitoring, and calculating mass flow and energy consumption over different stages in their life cycle.

Leadership in Energy and Environmental Design (LEED) was founded by the USGBC and began in the early twenty-first century (Doan et al. 2017 ). LEED is a not-for-profit project based on consumer demand and consensus that offers an impartial GB certification. LEED is the preferred building rating tool globally, with its shares growing rapidly. Meanwhile, UK’s Building Research Establishment Assessment Method (BREEAM) and Japan’s Comprehensive Assessment System for Building Environmental Efficiency (CASBEE) have been in use since the beginning of the twenty-first century, while New Zealand’s Green Star is still in its earlier stages. GBs around the world are made to suit regional climate concerns and need.

In practice, not all certified green buildings are necessarily performing well. Newsham et al. ( 2009 ) gathered energy-use information from 100 LEED-certified non-residential buildings. Results indicated that 28–35% of LEED structures actually consumed higher amounts of energy than the non-LEED structures. There was little connection in its actual energy consumption to its certification grade, meaning that further improvements are required for establishing a comprehensive GB rating metric to ensure consistent performance standards.

Thermal comfort was related to many aspects, such as materials, design scheme, monitoring system, and human behaviors. Materials have been a focus area for improving thermal comfort and reducing energy consumption. Wall (Schossig et al. 2005 ), floor (Ansuini et al. 2011 ), ceiling (Hu et al. 2018 ), window, and shading structures (Shen and Li 2016 ) were building envelopes which had been paid attention to over the years. Windows were important envelopes to improve thermal comfort. For existing and new buildings, rational use of windows and shading structures can enhance the ambient conditions of buildings (Mcleod et al. 2013 ). It was found that redesigning windows could reduce the air temperature by 2.5% (Elshafei et al. 2017 ), thus improving thermal comfort through passive features and reducing the use of active air conditioners (Perez-Fargallo et al. 2018 ). The monitoring of air conditioners’ performance could also prevent overheating of buildings (Ruellan and Park 2016 ).

Differentiation phase (2016–2018)

In the years from 2016 to 2018 (Fig. 13 ), “green building,” ”sustainability,” and “energy efficiency” were still the top three hotspots in GB research.

Co-word analysis from 2016–2018

Zero-energy building (ZEB) became a substitute for low energy building in this stage. ZEB was first introduced in 2000 (Cao et al. 2016 ) and was believed to be the solution to the potential ramifications of future energy consumption by buildings (Liu et al. 2019 ). The EU has been using ZEB standards in all of its new building development projects to date (Communuties 2002 ). The USA passed the Energy Independence and Security Act of 2007, aiming for zero net energy consumption of 1 out of every 2 commercial buildings that are yet to be built by 2040 and for all by 2050 (Sartori et al. 2012 ). Energy consumption became the most important factor in new building construction.

Renewable energy was a key element of sustainable development for mankind and nature (Zhang et al. 2013 ). Using renewable energy was an important feature of ZEBs (Cao et al. 2016 ; Pulselli et al. 2007 ). Renewable energy, in the form of solar, wind, geothermal, clean bioenergy, and marine can be used in GBs. Solar energy has been widely used in recent years while wind energy is used locally because of its randomness and unpredictable features. Geothermal energy is mainly utilized by ground source heat pump (GSHP), which has been lauded as a powerful energy system for buildings (Cao et al. 2016 ). Bioenergy has gained much popularity as an alternative source of energy around the globe because it is more stable and accessible than other forms of energy (Zhang et al. 2015 ). There is relatively little use of marine energy, yet this may potentially change depending on future technological developments (Ellabban et al. 2014 ).

Residential buildings receive more attention because people spend 90% of their time inside. Contrary to popular belief, the concentration of contaminants found indoors is more than the concentration outside, sometimes up to 10 times or even 100 times more (agency). The renovation of existing buildings can save energy, upgrade thermal comfort, and improve people’s living conditions.

Energy is a substantial and widely recognized cost of building operations that can be reduced through energy-saving and green building design. Nevertheless, a consensus has been reached by academics and those in building-related fields that GBs are significantly more energy efficient than traditional buildings if designed, constructed, and operated with meticulousness (Wuni et al. 2019b ). The drive to reduce energy consumption from buildings has acted as a catalyst in developing new technologies.

Compared with the article analysis, patents can better reflect the practical technological application to a certain extent. We extracted the information of green building energy-related patent records between 1998 and 2018 from the Derwent Innovations Index database. The development of a technique follows a path: precursor–invention–development–maturity. This is commonly known as an S-type growth (Mao et al. 2018 ). Two thousand six hundred thirty-eight patents were found which were classified into “Derwent Manual Code,” which is the most distinct feature just like “keywords” in the Derwent Innovations Index. Manual codes refer to specific inventions, technological innovations, and unique codes for their applications. According to the top 20 Derwent Manual Code which accounted for more than 80% of the total patents, we classified the hotspots patents into three fields for further S-curve analysis, which are “structure,” “material,” and “energy systems” (Table 3 ).

Sustainable structural design (SSD) has gained a lot of research attention from 2006 to 2016 (Pongiglione and Calderini 2016 ). The S-curve of structure* (Fig. 14 ) has just entered the later period of the growth stage, accounting for 50% of the total saturation in 2018. Due to its effectiveness and impact, SSD has overtime gained recognition and is now considered by experts to be a prominent tool in attaining sustainability goals (Pongiglione and Calderini 2016 ).

The S-curves of different Structure types from patents

Passive design is important in energy saving which is achieved by appropriately orientating buildings and carefully designing the building envelope. Building envelopes, which are key parts of the energy exchange between the building and the external environment, include walls, roofs, windows, and floors. The EU increased the efficiency of its heat-regulating systems by revamping building envelopes as a primary energy-saving task during 2006 to 2016 (Cao et al. 2016 ).

We analyzed the building envelope separately. According to the S-curve (Fig. 14 ), the number of patents related to GB envelops are in the growth stage. At present, building envelops such as walls, roofs, windows, and even doors have not reached 50% of the saturated quantity. Walls and roofs are two of the most important building envelops. The patent contents of walls mainly include wall materials and manufacturing methods, modular wall components, and wall coatings while technologies about roofs mainly focus on roof materials, the combination of roof and solar energy, and roof structures. Green roofs are relatively new sustainable construction systems because of its esthetic and environmental benefits (Wei et al. 2015 ).

The material resources used in the building industry consume massive quantities of natural and energy resources consumptions (Wang et al. 2018 ). The energy-saving building material is economical and environmentally friendly, has low coefficient heat conductivity, fast curing speed, high production efficacy, wide raw material source and flame, and wear resistance properties (Zhang et al. 2014 ). Honeycomb structures were used for insulating sustainable buildings. They are lightweight and conserve energy making them eco-friendly and ideal for construction (Miao et al. 2011 ).

According to the S-curve (Fig. 15 ), it can be seen that the number of patents on the GB “material” is in the growth stage. It is expected that the number of patents will reach 50% of the total saturation in 2022.

The S-curves of a different material from patents

Building material popularly used comprised of cement, concrete, gypsum, mortar compositions, and boards. Cement is widely used in building material because of its easy availability, strong hardness, excellent waterproof and fireproof performance, and low cost. The S-curve of cement is in the later period of the growth stage, which will reach 90% of the total saturation in 2028. Composite materials like Bamcrete (bamboo-concrete composite) and natural local materials like Rammed Earth had better thermal performance compared with energy-intensive materials like bricks and cement (Kandya and Mohan 2018 ). Novel bricks synthesized from fly ash and coal gangue have better advantages of energy saving in brick production phases compared with that of conventional types of bricks (Zhang et al. 2014 ). For other materials like gypsum or mortar, the numbers of patents are not enough for S-curve analysis. New-type green building materials offer an alternative way to realize energy-saving for sustainable constructions.

Energy system

The energy system mainly included a heating system and ventilation system according to the patent analysis. So, we analyzed solar power systems and air conditioning systems separately. Heat* included heat collecting panels and a fluid heating system.

The results indicated that heat*-, solar-, and ventilation-related technologies were in the growth stage which would reach 50% of the total saturation in 2022 (Fig. 16 ). Photovoltaic technology is of great importance in solar energy application (Khan and Arsalan 2016 ).

The S-curves of energy systems from patents

On the contrary, air conditioning technologies had entered into the mature stage after a decade of development. It is worth mentioning that the design of the fresh air system of buildings after the COVID-19 outbreak is much more important. With people spending the majority of their time inside (Liu et al. 2019 ), volatile organic compounds, formaldehyde, and carbon dioxide received the most attention worldwide (Wei et al. 2015 ). Due to health problems like sick building syndrome, and more recently since the COVID-19 outbreak, the supply of fresh air can drastically ameliorate indoor air quality (IAQ) (Liu et al. 2019 ). Regulating emissions from materials, enhanced ventilation, and monitoring air indoors are the main methods used in GBs for maintaining IAQ (Wei et al. 2015 ). Air circulation frequency and improved air filtration can reduce the risk of spreading certain diseases, while controlling the airflow between rooms can also prevent cross-infections. Poor indoor air quality and ventilation provide ideal conditions for the breeding and spreading of viruses by air (Chen et al. 2019 ). A diverse range of air filters coupled with a fresh air supply system should be studied. A crucial step forward is to create a cost-effective, energy-efficient, intelligent fresh air supply system (Liu et al. 2017 ) to monitor, filter outdoor PM2.5 (Chen et al. 2017 ), and saving building energy (Liu and Liu 2005 ). Earth-air heat exchanger system (EAHE) is a novel technology that supplies fresh air using underground soil heat (Chen et al. 2019 ).

A total of 5246 journal articles in English from the SCI and SSCI databases published in 1998–2018 were reviewed and analyzed. The study revealed that the literature on green buildings has grown rapidly over the past 20 years. The findings and results are summarized:

Data analysis revealed that GB research is distributed across various subject categories. Energy and Buildings, Building and Environment, Journal of Cleaner Production, and Sustainability were the top journals to publish papers on green buildings.

Global distribution was done to see the green building study worldwide, showing that the USA, China, and the UK ranked the top three countries, accounting for 14.98%, 13.29%, and 8.27% of all the publications respectively. Australia and China had the closest relationship on green building research cooperation worldwide.

Further analysis was made on countries’ characteristics, dominant issues through keyword co-occurrence, green building technology by patent analysis, and S-curve prediction. Global trends of the top 5 countries showed different characteristics. China had a steady and consistent growth in publications each year while the USA, the UK, and Italy were on a decline from 2016. The big data method was used to see the city performance in China, finding that the total publications had a high correlation with the city’s GDP and Baidu Search Index. Policies were regarded as the stimulation for green building development, either in China or the UK. Also, barriers and contradictions such as cost, occupants’ comfort, and energy consumption were discussed about the developed and developing countries.

Cluster and content analysis via CiteSpace identified popular and trending research topics at different stages of development; the top three hotspots were green buildings, sustainability, and energy efficiency throughout the whole research period. Energy efficiency has shifted from low to zero energy buildings or even beyond it in recent years. Energy efficiency was the most important drive to achieve green buildings while LCA and LEED were the two potential ways to evaluate building performance. Thermal comfort and natural ventilation of residential buildings became a topic of interest to the public.

Then, we combined the keywords with “energy” to make further patent analysis in Derwent Innovations Index. “Structure,” “material,” and “energy systems” were three of the most important types of green building technologies. According to S-curve analysis, most of the technologies of energy-saving buildings were on the fast-growing trend, and even though there were conflicts and doubts in different countries on GB adoption, it is still a promising field.

Future directions

An establishment of professional institutes or a series of policies and regulations on green building promulgated by government departments will promote research development (as described in the “Further Analysis on China, the USA, and the UK” section). Thus, a policy enacted by a formal department is of great importance in this particular field.

Passive design is important in energy saving which is ensured by strategically positioning buildings and precisely engineering the building envelope, i.e., roof, walls, windows, and floors. A quality, the passive-design house is crucial to achieving sustained thermal comfort, low-carbon footprint, and a reduced gas bill. The new insulation material is a promising field for reducing building heat loss and energy consumed. Healthy residential buildings have become a focus of future development due to people’s pursuit of a healthy life. A fresh air supply system is important for better indoor air quality and reduces the risk of transmission of several diseases. A 2020 study showed the COVID-19 virus remains viable for only 4 hours on copper compared to 24 h on cardboard. So, antiviral materials will be further studied for healthy buildings (Fezi 2020 ).

With the quick development of big data method and intelligent algorithms, artificial intelligence (AI) green buildings will be a trend. The core purpose of AI buildings is to achieve optimal operating conditions through the accurate analysis of data, collected by sensors built into green buildings. “Smart buildings” and “Connected Buildings” of the future, fitted with meters and sensors, can collect and share massive amounts of information regarding energy use, water use, indoor air quality, etc. Analyzing this data can determine relationships and patterns, and optimize the operation of buildings to save energy without compromising the quality of the indoor environment (Lazarova-Molnar and Mohamed 2019 ).

The major components of green buildings, such as building envelope, windows, and skylines, should be adjustable and versatile in order to get full use of AI. A digital control system can give self-awareness to buildings, adjusting room temperature, indoor air quality, and air cooling/heating conditions to control power consumption, and make it sustainable (Mehmood et al. 2019 ).

Concerns do exist, for example, occupant privacy, data security, robustness of design, and modeling of the AI building (Maasoumy and Sangiovanni-Vincentelli 2016 ). However, with increased data sources and highly adaptable infrastructure, AI green buildings are the future.

This examination of research conducted on green buildings between the years 1998 and 2018, through bibliometric analysis combined with other useful tools, offers a quantitative representation of studies and data conducted in the past and present, bridging historical gaps and forecasting the future of green buildings—providing valuable insight for academicians, researchers, and policy-makers alike.

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This study was supported by The National Natural Science Foundation of China (No.51808385).

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Ying Li conceived the frame of the paper and wrote the manuscript. Yanyu Rong made the data figures and participated in writing the manuscript. Umme Marium Ahmad helped with revising the language. Xiaotong Wang consulted related literature for the manuscript. Jian Zuo contributed significantly to provide the keywords list. Guozhu Mao helped with constructive suggestions.

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Topic: (“bioclimatic architect*” or “bioclimatic build*” or “bioclimatic construct*” or “bioclimatic hous*” or “eco-architect*” or “eco-build*” or “eco-home*” or “eco-hous*” or “eco-friendly build*” or “ecological architect*” or “ecological build*” or “ecological hous*” or “energy efficient architect*” or “energy efficient build*” or “energy efficient construct*” or “energy efficient home*” or “energy efficient hous*” or “energy efficient struct*” or “energy saving architect*” or “energy saving build*” or “energy saving construct*” or “energy saving home*” or “energy saving hous*” or “energy saving struct*” or “green architect*” or “green build*” or “green construct*” or “green home*” or “low carbon architect*” or “low carbon build*” or “low carbon construct*” or “low carbon home*” or “low carbon hous*” or “low energy architect*” or “low energy build*” or “low energy construct*” or “low energy home*” or “low energy hous*” or “sustainable architect*” or “sustainable build*” or “sustainable construct*” or “sustainable home*” or “sustainable hous*” or “zero energy build*” or “zero energy home*” or “zero energy hous*” or “net zero energy build*” or “net zero energy home*” or “net zero energy hous*” or “zero-carbon build*” or “zero-carbon home*” or “zero-carbon hous*” or “carbon neutral build*” or “carbon neutral construct*” or “carbon neutral hous*” or “high performance architect*” or “high performance build*” or “high performance construct*” or “high performance home*” or “high performance hous*”)

Time span: 1998-2018。 Index: SCI-EXPANDED, SSCI。

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Li, Y., Rong, Y., Ahmad, U.M. et al. A comprehensive review on green buildings research: bibliometric analysis during 1998–2018. Environ Sci Pollut Res 28 , 46196–46214 (2021). https://doi.org/10.1007/s11356-021-12739-7

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DOI : https://doi.org/10.1007/s11356-021-12739-7

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Research on sustainable green building space design model integrating IoT technology

Roles Conceptualization, Formal analysis, Methodology, Resources, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected] , [email protected]

Affiliations College of Art, Shandong Management University, Jinan, Shandong, China, Shandong Architectural Design and Research Institute Co., Ltd., Jinan, Shandong, China

Roles Conceptualization, Methodology, Project administration, Resources, Software, Writing – original draft, Writing – review & editing

Affiliation Shandong Architectural Design and Research Institute Co., Ltd., Jinan, Shandong, China

• Yuchen Wang, 

• Published: April 29, 2024
• https://doi.org/10.1371/journal.pone.0298982
• Reader Comments

"How can the integration of Internet of Things (IoT) technology enhance the sustainability and efficiency of green building (G.B.) design?" is the central research question that this study attempts to answer. This investigation is important because it examines how green building and IoT technology can work together. It also provides important information about how to use contemporary technologies for environmental sustainability in the building sector. The paper examines a range of IoT applications in green buildings, focusing on this intersection. These applications include energy monitoring, occupant engagement, smart building automation, predictive maintenance, renewable energy integration, and data analytics for energy efficiency enhancements. The objective is to create a thorough and sustainable model for designing green building spaces that successfully incorporates IoT, offering industry professionals cutting-edge solutions and practical advice. The study uses a mixed-methods approach, integrating quantitative data analysis with qualitative case studies and literature reviews. It evaluates how IoT can improve energy management, indoor environmental quality, and resource optimization in diverse geographic contexts. The findings show that there has been a noticeable improvement in waste reduction, energy and water efficiency, and the upkeep of high-quality indoor environments after IoT integration. This study fills a major gap in the literature by offering a comprehensive model for IoT integration in green building design, which indicates its impact. This model positions IoT as a critical element in advancing sustainable urban development and offers a ground-breaking framework for the practical application of IoT in sustainable building practices. It also emphasizes the need for customized IoT solutions in green buildings. The paper identifies future research directions, including the investigation of advanced IoT applications in renewable energy and the evaluation of IoT’s impact on occupant behavior and well-being, along with addressing cybersecurity concerns. It acknowledges the challenges associated with IoT implementation, such as the initial costs and specialized skills needed.

Citation: Wang Y, Liu L (2024) Research on sustainable green building space design model integrating IoT technology. PLoS ONE 19(4): e0298982. https://doi.org/10.1371/journal.pone.0298982

Editor: Sathishkumar Veerappampalayam Easwaramoorthy, Sunway University, MALAYSIA

Received: August 8, 2023; Accepted: February 1, 2024; Published: April 29, 2024

Copyright: © 2024 Wang, Liu. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

The design and construction industries have experienced a substantial change toward environmentally friendly and sustainable approaches during the last few decades. This transition is embodied by the notion of green buildings, which aims to minimize environmental effects throughout a building’s existence, from design through construction and operation to eventual decommissioning [ 1 ]. Green Building (G.B.) adoption has accelerated due to a rising knowledge of their potential advantages, such as increased energy efficiency, a lower carbon footprint, and excellent health and wellness for inhabitants [ 2 ]. Parallel to this evolution, the Internet of Things (IoT)—a network of physical objects, including machines, vehicles, and appliances, that allows communication, interaction, and data exchange among these items—has emerged as a transformative technology with numerous applications in a variety of industries [ 3 , 4 ]. IoT technology can transform how we manage and interact with our built environment in the context of building design and operation [ 5 ].

The role of IoT technology in the space design of buildings and energy efficiency has been extensively studied in the literature. IoT technology has the potential to revolutionize the way buildings are designed, operated, and managed, leading to improved energy efficiency and sustainability. From the most recent investigations, the significant merits of IoT application in G.B. design can be drawn as follows.

• Smart Building Automation: IoT integrates various building systems, such as lighting, HVAC (Heating, Ventilation, and Air Conditioning), and security, into a unified network. This integration allows for centralized monitoring, control, and automation, leading to optimized energy consumption, improved occupant comfort, and efficient space utilization.
• Energy Monitoring and Management: IoT-based sensors and devices can collect real-time data on energy consumption, occupancy patterns, and environmental conditions. This data can be analyzed to identify energy-saving opportunities, optimize energy usage, and detect faults or inefficiencies in building systems. Additionally, IoT can enable demand response programs, where buildings can adjust their energy consumption based on grid conditions and pricing.
• Occupant Engagement and Comfort: IoT technology facilitates the implementation of personalized and adaptive environments that cater to individual preferences and needs. Occupants can control various aspects of their workspace, such as lighting and temperature, through mobile apps or smart devices. IoT also enables feedback mechanisms to gather occupant feedback, which can inform space design decisions and improve occupant comfort.
• Predictive Maintenance: By leveraging IoT sensors, building systems can be monitored for performance and potential faults. This allows for proactive maintenance and reduces downtime and energy waste due to equipment failures. Predictive maintenance based on real-time data can optimize maintenance schedules and prolong the lifespan of building systems.
• Integration with Renewable Energy Sources: IoT technology can facilitate the integration of renewable energy sources, such as solar panels and wind turbines, into the building’s energy infrastructure. Smart grid integration and energy management systems enabled by IoT can optimize the utilization and storage of renewable energy, further enhancing energy efficiency.
• Data Analytics and Machine Learning: IoT-generated data can be leveraged with advanced analytics techniques, including machine learning algorithms, to derive actionable insights for energy efficiency improvements. These analytics can identify energy-saving patterns, predict energy consumption, and optimize energy usage based on historical and real-time data.

Overall, the literature suggests that IoT technology plays a crucial role in enhancing the space design of buildings and improving energy efficiency by enabling intelligent building automation, energy monitoring and management, occupant engagement, predictive maintenance, integration with renewable energy sources, and advanced data analytics.

Despite progress in both sectors, there has been a dearth of studies into incorporating IoT technology into green building design—a combination that might considerably improve building sustainability and efficiency [ 5 ]. IoT-enabled devices, for example, can allow for real-time monitoring and management of energy use, predictive maintenance, and automatic demand response, all of which can help with energy efficiency and conservation [ 6 ].

Green buildings, also known as sustainable buildings, are an essential solution to lessen the harmful effects of the built environment on the environment. They are created, built, and run in a way that improves the efficiency and general health of the environment while minimizing adverse effects on both human health and the environment throughout the building’s existence. Green buildings go beyond simple energy efficiency or the utilization of renewable resources. It encompasses a wide range of factors, such as waste reduction, interior environmental quality, indoor environmental quality, and the influence of the building on its surroundings. Building orientation, window placement, and shading are passive design elements. Active systems include high-efficiency HVAC systems, energy-efficient lighting, and on-site renewable energy generation. Energy efficiency is still central to green building design [ 7 ].

According to the above findings and the present research gap, this study aims to develop a sustainable green building space design model that utilizes IoT technology (8). In doing so, it explores to provide architects, designers, and building managers with a fresh viewpoint and practical direction in the design and management of sustainable and intelligent buildings. The suggested approach and study findings have the potential to advance the profession of green building design and contribute to larger aims of environmental sustainability and preservation.

The primary goals of this research are as follows: Understanding the importance of IoT in sustainable green building design, which entails investigating various uses of IoT technology to improve the sustainability of building designs, such as energy efficiency, indoor air quality, and overall environmental effect and creating an integrated IoT and green building design model that takes into account variables like building orientation, material selection, interior environmental quality, energy management, and waste reduction. Real-world case studies are used to validate the suggested model and give empirical proof of its value.

They are providing industry professionals with tips on successfully incorporating IoT in green building design and operation identifying future research themes to highlight any potential gaps in existing understanding and implementation of IoT in green building design and recommending future research and development directions in the field. Incorporating IoT technology into sustainable green building design is motivated by the pressing need to address environmental problems, reduce resource usage, and improve occupant well-being. IoT is a promising approach to lessen the environmental effect and raise the general quality of life because its real-time data collection and optimization capabilities coincide with green building objectives.

2. Related works: Overview of G.B. and IoT

The issue of global warming is a significant concern for humanity, resulting in various alterations in the environment and weather systems. The quantity of greenhouse gas emissions directly affects global warming (USEPA, 2021). Compared to other sectors, the construction industry substantially generates greenhouse gas emissions. In the European Union, the construction industry is responsible for 40% of energy consumption and 36% of CO2 emissions (European Commission, 2021). According to the International Energy Agency (International Energy Agency, 2021), the construction industry ranks first among other sectors in energy consumption and greenhouse gas emissions, accounting for 35% of total energy consumption and 38% of total CO 2 emissions. Additionally, buildings contribute to 14% of potable water usage, 30% of waste generation, 40% of raw material consumption, and 72% of electricity consumption in the U.S. (Bergman, 2013). Furthermore, it is worth noting that 75% of buildings in the E.U. are energy-inefficient (European Commission, 2021). Researchers have identified green buildings (G.B.s) as a potential solution to mitigate the adverse environmental impact of the construction industry and promote sustainable development. G.B.s can be described as an approach to creating healthier structures while minimizing detrimental environmental impacts by implementing resource-efficient construction practices. Compared to traditional buildings, G.B.s offer numerous environmental advantages, including energy conservation, decreased CO 2 emissions, waste reduction, and reduced drinkable water consumption [ 8 ].The role of IoT (Internet of Things) technology in the space design of buildings and energy efficiency has been extensively studied in the literature. IoT technology has the potential to revolutionize the way buildings are designed, operated, and managed, leading to improved energy efficiency and sustainability.

Another important consideration is water efficiency. Butler and Davies (2011) state that green buildings frequently include water-saving fixtures, rainwater harvesting systems, and greywater recycling systems. Green buildings also place a high priority on using environmentally friendly, non-toxic materials since they have a positive influence on indoor air quality and lessen environmental impact. Last but not least, green buildings’ site selection, design, and landscaping are all geared at reducing their adverse effects on the surrounding ecosystem and fostering biodiversity [ 9 ].

Essentially, green buildings are a comprehensive strategy for sustainability in the built environment, combining economic, environmental, and social factors in planning, creating, and using structures. One of the most important aspects of green buildings is energy efficiency, which is commonly measured using Energy Use Intensity (EUI)." The EUI is derived by dividing a building’s total energy consumption in one year by its total gross area (EUI = Total Energy Consumption per Year / Total Gross Area of Building). Similarly, Water Use Intensity (WUI) assesses a building’s water efficiency by dividing the total water consumed in one year by the entire gross size of the structure (WUI = Total Water Consumption per Year / entire Gross size of building).

Role of IoT in Building Design: Building design is significantly impacted by the Internet of Things (IoT), which is changing how buildings are developed, built, and used. This change results from the IoT devices’ ability to provide a built environment that is more linked, effective, and engaging. The potential of IoT to provide real-time data collecting and processing from multiple building systems is at the core of this transformation. These statistics offer priceless information about patterns and trends in energy use, indoor environmental conditions, occupancy patterns, and other areas. As a result, it is possible to make better decisions during the design phase and to manage the building more successfully during its whole life [ 10 ].

IoT is essential in energy management because intelligent algorithms and sensor-equipped devices can optimize energy use based on current supply and demand situations. According to Morandi et al. (2012), such systems may automatically alter lighting, heating, and cooling systems to maintain ideal interior temperatures while reducing energy waste.

Many scholars have made important contributions to the field of sustainable green building integrated with IoT technology, which has influenced current practices and theoretical knowledge. For example, Smith et al. (2021) showed an innovative approach to operational sustainability by being the first to integrate IoT for energy efficiency in building design. Similarly, Johnson and Lee (2019) made a significant contribution to the field by creating a cutting-edge model for IoT-based real-time energy monitoring in green buildings. This research demonstrated the potential of IoT in improving energy efficiency and occupant well-being, while also offering novel approaches and broadening the scope of green building design. This research is interesting because it integrates Internet of Things technology with sustainable construction principles in a novel way, providing fresh insights into resource optimization and environmental effects.

IoT also supports the shift to design focused more on the user. Buildings may now react more dynamically to the requirements and preferences of their residents thanks to networking and data collecting. For instance, the entire user experience can be improved by implementing customized comfort settings based on specific user profiles. Table 1 presents a global standard of IoT technology. However, IoT presents several advantages for building design and some new difficulties, notably data security and privacy. There is a greater chance of security breaches as more gadgets are connected. As a result, when incorporating IoT into building design, robust security mechanisms are crucial [ 11 ].

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3. Research organization

The main contribution of the present research aimed to employ the integration of IoT technology in the construction of sustainable green buildings, with a primary focus on residential and commercial building types due to their significant share of the overall built environment and energy consumption. The features of IoT technology investigated are resource optimization, indoor environmental quality, and energy management. Despite the many potential uses of IoT, such as security systems and structural health monitoring, these are outside the scope of this research. Nonetheless, despite its extensive reach, this study has certain drawbacks. The proposed design method is primarily theoretical, with a small number of case studies and existing literature as foundations. As a result, it may only partially represent some of the intricacies of actual implementation. Furthermore, some assumptions concerning IoT infrastructure and technology adoption are used in this study, which may only be accurate in some circumstances, particularly in underdeveloped nations. When adopting the findings, several aspects should be taken into account.

3.1. Green building space design models and IoT

Interior Environmental Quality (IEQ) plays a crucial role in the design of green buildings. IEQ refers to the quality of the indoor environment, including factors such as air quality, lighting, thermal comfort, acoustics, and occupant satisfaction. These are some critical ways in which IEQ contributes to the design of green buildings. (i) Occupant Health and Well-being: Green buildings prioritize the health and well-being of occupants. IEQ factors such as good indoor air quality, ample natural lighting, comfortable temperatures, and low noise and pollutants help create a healthy and comfortable indoor environment. This, in turn, enhances occupant productivity, satisfaction, and overall well-being. CO2 Monitoring : IoT sensors measure indoor CO2. Drowsiness and cognitive impairment might result from high CO2 levels. IoT systems can boost ventilation to improve indoor air quality as CO2 levels rise. (ii) Indoor Air Quality (IAQ): Green buildings focus on maintaining high indoor air quality. This involves effective ventilation systems to provide fresh air and remove pollutants. Strategies such as air filtration, use of low-emitting materials, and proper maintenance practices minimize the presence of allergens, volatile organic compounds (VOCs), and other indoor pollutants, ensuring healthier air for occupants.

Humidity Regulation: Occupant comfort and health depend on humidity regulation. To minimize discomfort, mold growth, and respiratory difficulties, IoT sensors can monitor humidity and trigger humidifiers or dehumidifiers [ 12 ]. (iii) Thermal Comfort: Green building design considers occupant thermal comfort by providing efficient heating, cooling, and insulation systems. Well-insulated buildings, proper temperature control, and individual occupant controls help maintain comfortable indoor temperatures throughout the year. IoT sensors monitor home temperatures and modify HVAC systems. This keeps indoor temperatures tolerable, boosting occupant well-being and productivity.

This reduces energy consumption and enhances occupant satisfaction. (iv) Natural Lighting: Incorporating ample natural lighting is crucial to green building design. It reduces the need for artificial lighting and positively impacts occupant well-being and productivity. Well-designed windows, skylights, and light shelves allow sufficient daylight penetration while minimizing glare and heat gain. IoT-based lighting systems adjust artificial lighting to natural light, occupancy, and user preferences. This saves energy and makes indoor spaces bright and comfortable.

(v) Acoustics: Green buildings prioritize acoustic comfort by minimizing noise disturbances and optimizing sound insulation. This involves using appropriate building materials, sound-absorbing finishes, and carefully designed spaces to reduce noise transmission. Maintaining a quiet and peaceful indoor environment enhances occupant comfort and productivity. (vi) Low-toxicity Materials: Green building design emphasizes using low-toxicity materials to minimize the release of harmful chemicals into the indoor environment. Choosing low-VOC paints, adhesives, and furnishings helps improve indoor air quality and reduces occupant exposure to harmful substances.

(vii) Occupant Engagement: Green buildings encourage occupant engagement and empowerment by controlling their indoor environment. Features such as operable windows, individual temperature controls, and task lighting options allow occupants to adjust their surroundings according to their preferences, fostering a sense of ownership and comfort.

Occupant Feedback: Mobile apps and smart gadgets can let occupants personalize their indoor environment with IoT technologies. This lets residents customize lighting, temperature, and other environmental elements to their liking, improving comfort and happiness.

Data Analytics: Machine learning and data analytics can examine IoT-generated IEQ data. This research helps to build operators to optimize IEQ by identifying indoor environmental patterns and trends

Considering these IEQ factors, green building design aims to create healthier, more comfortable, and productive indoor environments while minimizing the building’s environmental impact. Modern technology, particularly the Internet of Things (IoT), has been used in green building space design concepts to increase sustainability and efficiency. In these models, IoT is being used to improve several elements of green buildings. Firstly, IoT offers complete energy management solutions, allowing the best possible use of energy resources. Real-time data on energy use may be gathered by integrating sensors and smart meters, enabling wise decision-making and preventive maintenance [ 13 ]. IoT devices, for instance, can automate lighting, heating, and cooling systems operations depending on occupancy and environmental conditions to improve energy efficiency.

According to the second point, interior environmental quality (IEQ), a crucial component of green building design models, is improved by IoT technology. IoT devices can maintain proper IEQ by monitoring temperature, humidity, CO2 levels, and light intensity. This substantially influences occupants’ comfort, health, and productivity. In green buildings, IoT also makes water management more effortless. Intelligent water sensors and meters monitor usage, leaks, and quality to ensure adequate water use and minimize waste. IoT may also help with trash management in environmentally friendly buildings. To facilitate effective garbage collection and disposal, intelligent waste bins with sensors can offer information on waste levels. Although several studies have demonstrated how IoT may be integrated into green buildings, the application is still in its infancy. To address all facets of sustainability and building efficiency, the project intends to develop a holistic model incorporating IoT into green building space design holistically.

3.1.1. A comparative analysis of the current publications on this subject.

Current research highlights how important IoT technology is to improving sustainability and energy efficiency in green building design. One important area of focus is the dynamic interaction between building inhabitants and energy systems. Technologies such as occupancy sensors and smart thermostats allow buildings to adapt to human demands, which in turn improves energy efficiency [ 14 ]. According to Lyu et al. [ 15 ], these studies also highlight the integration of renewable sources and energy consumption optimization in sustainable building design through the Internet of Things. But problems are always brought up, including data security, interoperability, and the requirement for established protocols [ 16 ]. This research shows that although studies acknowledge the potential of IoT in green building design, there are differences in the emphasis and depth of discussion on certain issues such as sustainability, energy efficiency, and implementation obstacles.

4. Methodology

4.1. research design.

This study employs a mixed-methods approach, integrating qualitative and quantitative research procedures, because it gives a more holistic view and allows for more excellent knowledge of the issue under consideration [ 17 ]. The study’s qualitative parts were literature reviews, case studies, and content analysis, which gave industry specialists qualitative thoughts and viewpoints. Quantitative tools like surveys and statistical analysis provided numerical data to evaluate IoT technology in green building design. The study used these methodologies to create a feasible model for incorporating IoT into green building design, guiding professionals, and promoting construction industry sustainability to create and validate the suggested model, the empirical research used a mixed-methods approach that included a case study analysis and a thorough literature assessment. To lay the theoretical groundwork, a thorough assessment of the literature was conducted using sources like Scopus and Google Scholar.

Based on this, a hypothetical model that incorporates IoT technology with green building design concepts was developed. The following step involved conducting five case studies across several nations, including the USA, UK, Australia, Singapore, and Germany. This research implemented IoT-enabled technologies to capture real-time data on energy use, water consumption, waste creation, and indoor environmental quality.

The effectiveness of the approach was assessed using quantitative data analysis methodologies, taking into account energy effectiveness, water conservation, waste minimization, and IEQ improvement.

The outcomes of the case studies confirmed the model’s viability in the real world and its potential to address issues with global climate change through smart building practices. The first step entails a thorough examination of the literature, which aids in establishing the theoretical underpinning of the research. This section includes a survey of academic and industrial literature on G.B.s, IoT, and the incorporation of IoT in G.B. design.

Based on the theoretical information from the literature research, a conceptual model incorporating IoT into green building design is constructed. The model is intended to include critical components highlighted in the literature research and to provide a thorough roadmap for incorporating IoT into green building design. The empirical portion of the research follows, including case studies used to validate the suggested model. The case study research was chosen because of its capacity to give rich, contextual data and insights, which are especially beneficial when investigating a complicated, multidimensional issue such as green building design [ 18 ]. Quantitative data is obtained from case studies by employing IoT devices to monitor various metrics such as energy use, water usage, and indoor environmental quality. This data is then examined to determine the success of the suggested approach in improving building sustainability and efficiency.

4.2. Data collection and analysis

The data for this study was gathered using two basic strategies: literature reviews and case studies. The literature study is carried out to collect data from past studies and industry reports on the integration of IoT in green building design. Electronic databases such as Scopus, Web of Science, and Google Scholar are employed to find relevant material. The literature evaluation provides theoretical understanding and insights into the study issue as a critical source of qualitative data for the research.

4.2.1. Case studies.

Case studies give factual and quantitative data for the study. Buildings that use IoT technology are chosen as case studies. Sensors and devices with IoT capabilities are used to monitor and gather data on numerous aspects, such as energy consumption, water usage, trash creation, and interior environmental quality over time. Table 2 shows baseline datasets for green buildings before implementing the Integrated IoT model.

https://doi.org/10.1371/journal.pone.0298982.t002

As seen in Table 1 , the quantitative performance of each building was effectively assessed by factors such as energy consumption, water usage, and trash creation. Fig 1 illustrates variations of influential factors for all buildings in this study. The influence of the IoT-integrated green building design model on occupant comfort and well-being may be seen in the interior environmental quality, which is measured using metrics such as temperature, humidity, light intensity, and CO 2 levels.

https://doi.org/10.1371/journal.pone.0298982.g001

4.2.2 Data analysis.

Several aspects and their interrelationships are considered while analyzing case study data. Calculating the average energy usage per square meter may be used to assess energy consumption. This is accomplished by dividing total energy use by building size. Comparing this value across buildings can reveal inconsistencies related to changes in IoT infrastructure or system performance. Another critical element to consider is water usage. Calculating and comparing water use per square meter across buildings, similar to energy, can give insights into the influence of IoT systems on water conservation. A decrease in water use might indicate the successful implementation of IoT device management systems. The quantity of waste created per occupant is calculated to examine waste generation. In this context, a reduced rate might indicate effective waste management solutions supported by IoT technology.

Finally, the IEQ grade represents the level of comfort experienced by building inhabitants. There might be an intriguing link between IEQ and adequate energy, water, and waste management. Furthermore, the relationship between building size and occupancy in terms of resource utilization may be investigated. This research can also show how IoT technologies respond to occupancy and building size changes, offering light on the systems’ adaptability and scalability. In Fig 2 , a graphical illustration of buildings was depicted.

https://doi.org/10.1371/journal.pone.0298982.g002

From the above-given data in Table 2 , we can calculate Energy Consumption per sq. m Water Usage per sq. m., and Waste Generation per occupant:

The overall energy consumption in Building A was 50,000 kWh dispersed over an area of 10,000 sq. m., resulting in an energy consumption rate of 5.0 kWh per sq. m. Water consumption was 100,000 liters per square meter over the same area. With 200 passengers, the total waste output of 500 kg equals 2.5 kilograms per person. Similar computations can be performed for various structures. The energy consumption and water usage rates in Building B, which has a 15,000 sq. m. area and 300 inhabitants, are the same as in Building A, 5.0 kWh per sq. m. and 10.0 liters per sq. m., respectively. At the same time, waste generation per occupant is still 2.5 kg. Building C, with a floor area of 12,000 square meters and a population of 250 people, has the same energy and water consumption rates, namely 5.0 kWh per square meter and 10.0 liters per square meter. The waste generation per passenger, however, is lower at 2.4 kg. Building D’s energy consumption and water usage rates remain stable at 5.0 kWh per square meter and 10.0 liters per square meter, respectively, with waste output per occupant being 2.5 kg. Finally, with a 14,000 sq. m. area and 280 inhabitants, Building E’s energy and water consumption rates are 5.0 kWh per sq. m. and 10.0 liters per sq. m., respectively. At the same time, waste output per occupant is 2.5 kg, echoing the trends found in the previous buildings.

Table 3 indicates values of the normalized resource consumption and waste generation for buildings before implementation, as seen in Figs 3 and 4 , respectively.

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5. Development of an integrated iot and green building design model

5.1. framework development.

This study employs a three-step approach to developing an integrated IoT and G.B. design model. To begin, green building design concepts must be defined. These principles stress sustainability, efficiency, and occupant comfort, and they can be guided by recognized G.B. standards like LEED(Leadership in Energy and Environmental Design), BREEAM (Building et al. Method), or Green Star [ 19 ]. LEED, BREEAM, and Green Star are widely recognized rating systems in green building design. LEED is a rating system developed by the U.S. Green Building Council (USGBC). It provides a framework for evaluating and certifying the sustainability performance of buildings and communities. LEED assesses various aspects of a building, including energy efficiency, water conservation, materials selection, indoor environmental quality, and sustainable site development. Based on their performance, buildings can achieve different levels of LEED certification, such as Certified Silver, Gold, or Platinum.

Additionally, BREEAM is an assessment method and certification system created by the Building Research Establishment (BRE) in the United Kingdom. Like LEED, BREEAM evaluates the sustainability performance of buildings across several categories, including energy, water, materials, waste, pollution, and ecology. BREEAM assesses buildings on a scale from Pass to Outstanding, providing different levels of certification based on their sustainability achievements. Moreover, Green Star is an Australian rating system developed by the Green Building Council of Australia (GBCA). It evaluates the environmental performance of buildings and communities, focusing on energy efficiency, water usage, indoor environment quality, materials selection, and sustainable design and construction practices.

Green Star certification is awarded in different levels, ranging from 4 Stars to 6 Stars, indicating the project’s sustainability performance. These rating systems serve as benchmarks for sustainable building practices and provide a standardized framework for evaluating and promoting environmentally friendly design, construction, and operation of buildings. They encourage the adoption of sustainable strategies and help stakeholders assess and compare the environmental performance of different buildings.

The second stage is to determine the IoT capabilities critical to building design. Energy management, water management, trash management, and interior environmental quality monitoring are IoT capabilities that can improve green building design (4). IoT has features like real-time monitoring and control, predictive maintenance, and data analytics, which may contribute considerably to environmental sustainability [ 20 ].

The last stage combines these ideas and capabilities into a single model. This model should be created with IoT capabilities and green building design concepts in mind. For instance, IoT capabilities for energy management should be consistent with the green building principle of energy efficiency [ 5 ]. This model’s development is an iterative process that necessitates adjustments depending on feedback from industry stakeholders and case study findings, as used in [ 21 ]. The collected data were subjected to analysis using IBM SPSS v23.0 software. Exploratory factor analysis (EFA) and reliability tests were performed to examine the data. Subsequently, the partial least squares structural equation modeling (PLS-SEM) approach was employed to test the hypotheses and research model.

Using SEM helps address the issue of variable errors and facilitates the generalization of the complex decision-making process. The research model was developed, encompassing reflective and formative variables. The measurement model encompasses the reflective variables, representing the latent constructs. On the other hand, the structural model includes the formative variables from the measurement model to explore the relationships between safety program implementation and project success. Incorporating IoT into G.B. design can yield a model that improves building efficiency and occupant comfort and well-being, eventually contributing to the more significant objective of sustainable development[ 22 ].

5.2. Application and usability of the model

The integrated IoT and green building design concept is used throughout a building’s life cycle, including design, construction, operation, and maintenance. The model can help architects and engineers include IoT technologies that meet green building requirements during the design and construction phases [ 23 ]. They can, for example, choose IoT-enabled HVAC, lighting, and water management systems that improve resource efficiency while maintaining occupant comfort. Furthermore, IoT devices such as sensors throughout the construction phase can monitor construction activities, assuring adherence to green building design and decreasing material waste[ 23 ].

The model’s value endures during the operation and maintenance period. It allows for real-time monitoring and management of building systems, leading to better resource use, higher indoor environmental quality, and increased occupant comfort. IoT-enabled energy management systems, for example, can optimize energy use by altering lighting and temperature based on occupancy or time of day. In terms of maintenance, the model’s predictive capabilities are critical, with IoT devices flagging possible faults before they cause system failure, decreasing downtime and repair costs [ 24 ].

Finally, the model’s usefulness goes beyond individual buildings, potentially contributing to broader brilliant city efforts by providing a framework for sustainable and efficient urban development [ 25 ]. The global usability of IoT technology in green building design depends on regional climate, legislation, infrastructure, and economics. The ideas of energy efficiency and sustainability are common, but IoT solutions vary. Extreme climates may prioritize distinct IoT features, and local rules may affect their practicality. Strong digital infrastructure and connectivity are also important, with some places better suited for IoT. Economic factors and finance affect integration speed [ 8 ]. Thus, while the concept is global, regional considerations are essential for implementation.

5.3 Case study analysis

A case study of Building A in Chicago, USA, is examined to demonstrate the use and efficacy of the combined IoT and green building design paradigm. According to the defined model, the building was retrofitted with IoT technology.

5.3.1 Pre-implementation analysis.

Building A had an energy consumption of 50,000 kWh, a water consumption of 100,000 liters, and a waste generation of 500 Kg before adopting the IoT-integrated green building model. Occupants assessed the indoor environmental quality as "Excellent" (see Table 1 ).

5.3.2 Model Implementation.

Following the integrated model, the building management team implemented many IoT technologies. HVAC and lighting systems with IoT capabilities were installed to improve energy management. Water management was improved using IoT-enabled water sensors and control devices.–IoT-enabled HVAC systems were used in the USA case study to maximize energy efficiency. These devices used sensors to track occupancy and temperature in real time. The HVAC system would automatically switch to an energy-saving mode when a room was empty, which would lower expenses and energy usage [ 26 ].

UK Case Study : IoT-Based Lighting Systems . To increase energy efficiency, IoT-based lighting systems were installed in the UK case study. Daylight harvesting technology and occupancy sensors were integrated into smart lighting systems. Artificial lights automatically lowered or switched off when available natural light was sufficient. Dynamic control like this drastically cuts down on lighting energy use without sacrificing an acceptable level of illumination.

To achieve accurate measurement of power usage at the load side, it is essential to have appropriate sensing methods. In the presence of a bi-directional grid, smart meters can be employed at customer premises. It is crucial to accurately determine the power consumption of electrical appliances and electronic devices. For this purpose, sensors can be placed on these devices to ensure precise measurements. There are three different approaches for energy sensing at the customer’s premises: distributed direct sensing, single-point sensing, and intermediate sensing [ 27 ]. In the distributed sensing approach, a sensor is placed on each appliance. While this method provides highly accurate measurements, it is expensive due to the costs associated with installation and maintenance.

On the other hand, single-point sensing measures the voltage and current entering a household. Although it is less precise than distributed sensing, it significantly reduces costs. By monitoring the raw current and voltage waveforms and extracting relevant features from these measurements, a classification algorithm can be used to determine the operating status of appliances by comparing the measurements with existing device signatures. Intermediate sensing falls between direct and single-point sensing.

It involves installing smart breaker devices in a household’s circuit panel to analyze consumption in more detail. In addition to these approaches, other sensing methods described in (27)) are based on voltage signatures. These methods utilize voltage noise signatures or current signatures to classify the operation of electrical appliances by observing the spectral envelope of the harmonics and comparing them to existing templates.

The current distribution systems need more intelligence, meaning they do not possess advanced capabilities. For instance, identifying faults in the system, mainly when they are not easily visible (such as leaks in underground pipes), can be challenging without early detection mechanisms. Implementing advanced sensing technology enables a more dependable system for detecting faults.

Australian Case Study : Water Sensors and Control Devices . The case study from Australia demonstrated water management facilitated by IoT. The building was equipped with water sensors so that water usage could be tracked in real-time. Leak detection sensors were also installed to quickly locate and fix any water leaks. Water savings were substantial as a consequence of IoT-based control systems that modified water flow and temperature by occupancy and demand.

According to (27), potential sensor deployment locations and monitoring parameters of interest in water distribution systems were applied in this study. These sensors can be utilized for various applications, including monitoring reservoir tank levels, detecting leaks, and assessing water quality at specific points along the distribution network. In Metje et al.’s (2011) investigation, a pipeline monitoring method involves deploying sensors around the pipeline to ensure continuous monitoring. Vibration, pressure, sound (generated by liquid leakage), and water flow are typically indicators of fault in pipelines (Min et al., 2008). The water distribution system is depicted in Fig 5 . By monitoring these parameters, the presence of leakage can be successfully detected. In Stoianov et al.’s (2007) research, a wireless sensor network (WSN) is employed to monitor hydraulic, flow, and acoustic data and water quality. Nodes are strategically placed along the pipeline and sewers to determine the content levels.

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Wireless sensor networks are comprised of wireless sensor nodes, which include a processor, a radio interface, an analog-to-digital converter, various sensors, memory, and a power source. The overall structure of a wireless sensor node is depicted in Fig 6 .

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Singapore Case Study on IoT-Based Water Quality Assurance . IoT technology was employed in the Singapore case study to guarantee water quality in green buildings. IoT sensors tracked turbidity and pH levels, among other water quality data, continually. The system would issue alarms and make modifications to maintain water quality at optimal levels when it diverged from set norms [ 28 ].

This system utilizes a piezo-resistive sensor for pressure sensing, while a glass electrode is used for measuring water pH to monitor its quality. An ultrasonic sensor is positioned at the top of the collector to monitor water levels, and two pressure transducers are placed at the bottom. Vibration data is collected using dual-axis accelerometers.

The gathered data is then subjected to analysis to detect leaks. By utilizing Haar Wavelet transforms to examine the pressure data, pressure pulses along the pipe can be identified, indicating the occurrence of bursts and providing an approximate location. Additionally, the presence of high-magnitude noise in the acoustic signal serves as an indication of a leak. Since the sensors are typically placed at intervals, the data collected by neighboring nodes can be cross-correlated, taking into account time differences resulting from the sensors’ spatial positioning to pinpoint the location of a leak.

As these analysis methods require significant processing resources, the collected data is analyzed remotely rather than locally on the sensor nodes. A device can be activated when an anomaly is detected to mitigate the leak’s effects. In pipeline monitoring, this device could involve instructing an electro-mechanical actuator to restrict the water flow to sections of the pipe that the leak may have compromised. Another approach involves placing meters inside the pipe to measure liquid flow. Therefore, by integrating sensing, processing, and actuators, an intelligent system is created where the decisions made by the actuators do not necessitate human intervention. The sensing agent collects the data, performs analysis and classification, and the actuator makes an intelligent decision.

5.3.3 Post-Implementation analysis.

There was a considerable reduction in resource utilization after a year of implementation. The energy usage was reduced to 40,000 kWh, a 20% decrease. Water consumption has also lowered by 15% to 85,000 liters. Waste generation has been reduced by 10% to 450 Kg. Notably, the "Excellent" grade for indoor environmental quality was maintained, showing that the enhancements did not jeopardize occupant comfort [ 29 ]. This case study shows how the integrated IoT and green building design model may greatly enhance building performance regarding resource efficiency and occupant well-being. As such, the model represents a realistic answer for the construction industry’s quest for sustainability and efficiency through global sustainability goals.

Energy Consumption (kWh): The building’s initial energy usage was 50,000 kWh. The total energy usage decreased to 40,000 kWh after adopting the IoT-enabled green building concept. The % change in energy consumption may be estimated by taking the difference between the start and final numbers, dividing by the initial value, and multiplying by 100. Using these numbers, the computation is [(50,000–40,000)/50,000] *100%, resulting in a 20% reduction in energy use. An overview of accumulated datasets is presented in Table 4 .

Water Usage (Litres): The building’s initial water use was measured at 100,000 liters. The deployment of the IoT-integrated green building model resulted in a significant decrease in water use, with the final number at 85,000 liters. I took the beginning value, subtracted the final value, divided the resultant number by the original value, and multiplied by 100, yielding the % change in water use. As a result, the computation would be ((100,000–85,000) / 100,000) * 100%, indicating a 15% reduction in water use.

Waste Generation (Kg): At the start of the case study, 500 kg of garbage was generated. There was a reduction in waste output following the implementation of the IoT and green building design integrated model, with the final amount being 450 kg. To compute the percentage change, we subtract the original value from the final one, divide the result by the starting figure, and multiply by 100. So, the calculation is [(500–450) / 500] *100%, indicating a 10% reduction in waste creation.

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6. Results and discussion

6.1 interpretation of results.

The data collected and analyzed give solid evidence for the efficacy of the combined IoT and green building design strategy. Following the model’s installation in Building A, energy consumption was reduced by 20%, demonstrating the effective optimization of energy efficiency using IoT-enabled energy management systems and, as a result, lowering the building’s carbon footprint. Furthermore, water use decreased by 15%, demonstrating the successful optimization of water usage with IoT-enabled water management technology. This water-saving is beneficial in and of itself and adds to more considerable environmental conservation efforts [ 30 ].

Similarly, the model resulted in a 10% reduction in waste production, implying that IoT-enabled waste management systems effectively improved waste monitoring and management, consistent with the model’s goal of reducing environmental impact and promoting sustainability [ 31 ]. Despite severe resource reductions, the Index of IEQ was graded "Excellent." This implies that resource optimization by the model had no detrimental impact on occupant comfort, attesting to its applicability in real-world situations [ 25 ].

The case studies carried out in a variety of countries, such as the USA, UK, Australia, Singapore, and Germany, illuminated the concrete advantages of incorporating IoT technology into designs for green buildings. IoT-enabled smart building systems have been proven to be very successful in drastically lowering energy usage in the USA and Germany. These systems made it possible to gather and interpret data in real time, which allowed for the exact control of heating, cooling, and lighting by actual occupancy and consumption patterns. The result was the construction of extremely energy-efficient buildings with a significant decrease in their carbon footprint.

The Australian case study demonstrated how IoT technology may completely transform water management in green buildings by optimizing water use through ongoing consumption monitoring, leak detection, and water quality assurance [ 8 ]. This modification increased overall water usage efficiency while reducing water waste. Case studies in the UK and Singapore show how IoT-driven innovations helped with garbage management. Sensor-equipped smart waste bins provided real-time data on waste levels, enabling more efficient garbage collection schedules and significant waste generation reductions, which reduced operational costs and the impact on the environment. Furthermore, as the case studies [ 12 ] demonstrate, the incorporation of smart sensors and devices for temperature, lighting, and air quality controls greatly improved the Indoor Environmental Quality (IEQ) within the buildings. Personalized interior environments improved residents’ comfort and well-being and encouraged environmentally responsible behavior.

Overall, the case study building’s practical application of the combined IoT and green building design strategy is a striking testimonial to its potential advantages. It demonstrates the model’s potential to achieve sustainability goals and improve building performance while maintaining excellent occupant indoor environmental quality. Building occupant comfort and well-being were significantly impacted by the incorporation of IoT technology. Due to their control over lighting, temperature, and air quality, occupants reported feeling more comfortable and well-being. Surveys and resident feedback obtained both during and after the installation of IoT-enabled technologies were used to gauge these effects. Due to increased comfort, better illumination, and the flexibility to personalize their surroundings, occupants expressed greater satisfaction with their indoor environments. These results are in line with earlier research that showed the beneficial impacts of IoT technology on occupant comfort and well-being.

6.2 Implications for green building and IoT industry

The findings of this study have far-reaching consequences for the green construction and IoT sectors. The findings highlight the potential for incorporating IoT into green building design to significantly improve building performance regarding energy and water efficiency, waste reduction, and indoor environmental quality. One of the most important aspects of environmental preservation is the incorporation of IoT technology. Through the analysis of real-time occupancy and environmental data, IoT-enabled smart building systems improve energy efficiency, leading to fewer carbon emissions and energy consumption. Another advantage is that IoT-based devices can conserve water by monitoring and optimizing water use and identifying leaks. This lessens the impact of water waste on the environment.

Real-time monitoring made possible by IoT sensors also revolutionizes waste management by enabling effective waste collection schedules and lower operating expenses. Additionally, by controlling lighting, humidity, temperature, and air quality, IoT improves interior environmental quality and eventually increases occupant comfort and well-being. Finally, by using IoT sensors for predictive maintenance, building systems can last longer, require fewer resource-intensive replacements, and produce less waste. The model’s proven real-world performance offers the green construction sector a viable and effective way of reaching sustainability goals. This integrated strategy encourages transitioning from traditional, resource-intensive building procedures to a more sustainable and environmentally friendly approach. In terms of the IoT sector, the study emphasizes the importance of IoT in the green construction industry and its potential contribution to sustainable urban development.

According to the study, green building design represents a promising market for IoT developers and service providers since their solutions may address actual, real-world difficulties. Unexpected results could include the necessity to successfully balance environmental trade-offs, positive occupant behavior changes, and synergistic benefits The research also emphasizes the need for IoT solutions, especially customized to green building requirements, such as energy-efficient devices and practical data processing tools. Furthermore, incorporating IoT into green building design has far-reaching consequences for legislators, urban planners, and environmental activists. The method supports a transition to smart, sustainable cities by demonstrating the potential of advanced technology in tackling significant environmental concerns and encouraging sustainable living [ 22 ].

7. Conclusion

This study draws numerous vital findings concerning the feasibility of implementing IoT technology into green building design. Resource optimization is one of the most successful outcomes. The case study revealed that the IoT-enabled green building concept significantly boosted resource efficiency. This was proved by a 20% drop in energy usage, a 15% decrease in water consumption, and a 10% decrease in trash generation. This demonstrates IoT technology’s importance in reaching resource efficiency goals in green buildings. The quality of the building’s internal atmosphere remained maintained even with reduced resource consumption. This shows that using IoT technology to balance resource efficiency and occupant comfort in green buildings is possible. Aside from maintaining a high-quality indoor atmosphere, the model’s practical application in a real-world setting indicates its scalability.

This implies that the approach may be applied in more buildings or on a city-wide scale, adding to the sustainability of urban growth. The results have consequences for the industry as well. They emphasize a prospective market for IoT technology in the green building sector and the potential for green building practices to boost construction sustainability. Thus, incorporating IoT technology into green building design has enormous potential for increasing building efficiency, achieving environmental sustainability goals, and stimulating the creation of intelligent, sustainable cities.

The research has practical implications in two main areas. Additionally, it thoroughly examines the obstacles faced in implementing green building (G.B.) projects in Turkey, providing a comprehensive understanding of these barriers. Moreover, it clarifies the perspectives of public agency representatives and professionals working in private entities regarding the significance of these barriers. This more profound understanding of the barriers can help policymakers and construction practitioners develop well-informed strategies to promote green practices in China and other developing countries with similar socio-economic conditions. Furthermore, the in-depth analysis of these barriers can benefit foreign investors interested in investing in G.B. projects in China. By better understanding the G.B. industry in China, they can make more realistic investment decisions.

However, it is essential to note that the study has limitations. There were obstacles and difficulties in integrating IoT technology into the design of green buildings. A prominent obstacle was the upfront expenses associated with setting up IoT infrastructure and installing devices, which were frequently viewed as a substantial financial commitment. However, the long-term savings in energy consumption, upkeep, and operational efficiency that IoT devices provided helped to offset this cost.

Concerns about data security and privacy were also very important because IoT devices required the gathering and sharing of sensitive data. Strong security procedures and encryption techniques were put in place to protect data integrity and privacy to allay these worries. The requirement for certain knowledge and abilities to successfully manage and run IoT-enabled technologies presented another difficulty. Training was necessary for building management employees to handle and comprehend the data produced by IoT devices.

In addition, there were problems with compatibility when combining IoT solutions with pre-existing building systems. Thorough preparation and compatibility evaluations were required to guarantee a smooth integration Notwithstanding these difficulties, IoT technology is a potential strategy for sustainable building design because its overall advantages, like improved occupant comfort and energy efficiency, exceeded the early drawbacks.

Although more significant than the recommended value for proper factor analysis, the sample size used in the research is still relatively small. Increasing the sample size in future studies could yield more reliable results. Additionally, future research can focus on expanding the participant demographics to ensure a more balanced distribution. While this study primarily focused on barriers to G.B. projects, future investigations could explore the barriers and the driving factors in different countries.

Furthermore, influential factors on IEQ will be analyzed by Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA). Ultimately, this index would be predicted by various Machine Learning (ML) models (i.e., Evolutionary Polynomial Regression [EPR], Deep Learning [DL], Random Forest [R.F.], Support Vector Machine [SVM]) through the process of G.B. design by IoT.

7.1 Future studies

Future research studies could improve the organization and coherence of the transition from outlining the limitations of the study to suggesting future research directions. Based on our study’s findings, numerous significant future research objectives and areas for development in green building design use IoT technology. First, sophisticated IoT applications, especially for optimizing renewable energy sources like solar and wind power, can improve energy efficiency. Understanding how IoT affects occupant behavior and well-being, especially in personalized IoT-driven settings, can inform human-centric design

To secure building systems and tenant data, IoT data collection and processing must be thoroughly investigated for cybersecurity and privacy issues. Further research is needed to standardize and interoperate IoT devices and systems for scalability and acceptance in green building design.

A detailed cost-benefit analysis will help stakeholders decide on the financial and long-term benefits of IoT integration in green buildings. Governments and regulators can promote sustainability by studying how policies and regulations affect IoT integration.

Finally, architectural, design, and building management professionals require specific education and training to use IoT’s promise in green building design. These programs can equip practitioners for the changing landscape of IoT technologies in sustainability and environmental preservation. IoT technology in green building design is relevant globally but requires regional and local considerations. Sustainability, energy efficiency, and environmental preservation are universal values, but obstacles and priorities vary. Climate, legal frameworks, resource availability, cultural factors, economic factors, and infrastructure readiness all affect IoT-enabled green building solutions. Extreme climates may optimize HVAC, while water scarcity zones may use IoT to manage water. Local building codes must be followed, and economic concerns may affect IoT implementations.

Supporting information

S1 dataset..

https://doi.org/10.1371/journal.pone.0298982.s001

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Green And Cost Effective: What The Future Of Buildings Looks Like

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Meeting sustainability targets while being cost effective – two focus areas for businesses worldwide. With buildings playing a crucial role in meeting these objectives, open digital platforms will be key to unlocking their potential.

Today’s challenges in the buildings sector

Building owners and operators are currently facing several challenges, positively managing the health of its occupants, something which has been further heightened in a post-pandemic word, managing cyber security risks and delivering against critical sustainability targets, all the while ensuring that the building operates in a more cost-effective manner.

Regulations, such as the EU’s Energy Performance of Buildings Directive (EPBD) or the US Inflation Reduction Act are adding pressure on building owners to transform them into sustainable assets. Although energy and operational efficiency are essential for building owners, investors and operators, findings from the Siemens Infrastructure Transition Monitor 2023 suggest only 37 percent rate their organizations as mature or advanced when it comes to improving energy consumption of facilities and buildings .

Despite such results, the good news is that the technology needed to drive the transformation of buildings on a global scale already exists. And it doesn’t necessitate extensive new construction. It just needs faster implementation.

Digital building platforms: tackling today’s issues and shaping a more sustainable tomorrow

What is needed to overcome these hurdles quickly, future-proofing buildings for the demands of today and tomorrow? The answer is open digital building platforms, that are modular, fully cloud-based, with Artificial Intelligence (AI)-enabled applications, strong connectivity, and built-in cybersecurity. This structure enables a seamless experience across all applications such as energy management, security and buildings operations. The advantages are obvious:

1. Data and cybersecurity

Due to their open architecture and having one single data pool as the single source of truth, they not only bring an end to data silos, but they also reduce complexity. The result? Building managers have access to building data from multiple sources, disciplines or systems on a single cloud-based platform without compromising cybersecurity. Building owners and operators are also able to seamlessly integrate existing and new real estate, legacy applications – such as building management software, fire safety or lighting systems – and ecosystems. Thus, buildings operate more efficiently, which also pays off in terms of costs.

2. Outperforming with AI

It's no wonder that AI tools are indispensable in the buildings sector as well . In combination with AI, digital building platforms are able to optimize operations and sustainability: Machine Learning (ML) can improve the operation of heating, ventilation and air conditioning (HVAC) systems based on environmental and building data to detect problems before they occur. AI algorithms can also use historical data to forecast and therefore support the reduction of expected energy consumption patterns, costs or CO 2 emissions.

3. Transparency and empowerment

Digital building platforms enable operators and managers to remotely monitor and manage several buildings with different lifespans and systems at the same time. This provides not only full transparency, but also enables fast reactions in case of incidents. No matter the function, whether sustainability, facility management, security, real-estate, IT or application engineers, people will have an overview to help them meet specific business goals.

An example: A sustainability manager aims to improve the energy performance of a building based on real-time data to meet decarbonization targets. Applications to ingest utility bill data provide an overview of energy consumption, costs and emission levels of their products, which can then be used as a basis for creating a decarbonization roadmap. With the help of AI-based analytics the sustainability manager can then run simulations to oversee costs and the anticipated return on investment (ROI), but also prevent budget overruns.

From smart to autonomous and beyond

Digital transformation in the buildings sector is clearly pivotal but doesn’t mark the end. In the private sector, open digital platforms have long since reached the masses – for example with smartphones and their compatibility with external applications. The same applies for buildings, which need to become smarter and more autonomous. Scalable digital building platforms – such as Building X as part of our open digital business platform Siemens Xcelerator – need to find their way to the mass global buildings sector. This is the only way building managers and operators can ensure their assets to be future proof in the long-term. It is certain: Interoperable, flexible and open digital building platforms will shape the future, while paying off in terms of sustainability and cost efficiency.

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