Articles
THE ARTIFICIAL INTELLIGENCE TECHNOLOGY FOR SUSTAINABLE BUILDING

Abu Bakar Abd Hamid1 and Norashikin Rahmat2

 

1Interior Architecture Studies, School of Architecture and Interior Architecture, College of Built Environment, Universiti Teknologi MARA, 42300 Bandar Puncak Alam, Selangor Malaysia

2Centre for Postgraduate Studies, College of Built Environment, Universiti Teknologi MARA, 40450 Shah Alam, Selangor Malaysia

 

Introduction to Artificial Intelligence Technology

Nowadays, the Industrial Revolution 4.0 (IR4.0) needs to look at the reality of developments in computer technology. Present-day computer system technology has intruded numerous physical technologies and into the community’s life systems,  defined as artificial intelligence (AI). Appearances of AI are thoroughly related to a computer system programmed to maximise human behaviour and principles of life.

The rapid development of AI technology looks for more ways to operate this new technology to produce a healthier and more sustainable environment for humans. In the field of indoor architectural space design, environmentally friendly design has developed a new trending topic, and more people are starting to be alert to how indoor architectural space design can encourage environmental protection.

The application of an environmentally friendly design in indoor spaces mainly focuses on lighting, ventilation, water resources, and renewable energy. By utilising artificial intelligence technology and advanced equipment, maximum improvement of indoor environmental comfort and energy efficiency can be achieved. Beyond this, green and sustainable design can also reduce indoor air pollution, lower maintenance costs and increase the lifespan of indoor spaces. Consequently, exploring how to use artificial intelligence technology to achieve green and sustainable design in indoor building spaces has become a hot topic in the academic fields of architecture and environmental studies.

Various factors and extensive issues obviously complicate construction projects before they flourish (Ayhan et al., 2021). Generally, various construction projects face several challenges and factors, such as delaying progress, cost overruns, and safety issues. These factors usually come from human behaviour and error, inefficient resource allocation, and insufficient planning. Usually, human activities are more efficient in smart and sustainable communities (Gue et al., 2022). By applying Artificial Intelligence (AI), the potential to enhance construction processes and the development of sustainable communities is more significant. With AI, it has the potential to increase labour efficiency by 40% and economic growth rates by 2035 (Pan and Zhang, 2021).

 

Artificial Intelligence in Sustainable Building

AI is an integration between Virtual Reality (VR) and Augmented Reality (AR) technologies, which is transforming designers and clients to interact with and visualise interior spaces. Virtual reality consensuses designers and clients to think about space in a simulated environment, empowering them to ensure informed decisions regarding the layout, furniture placement, and lighting before slight physical changes are made. Augmented reality overlays virtual design elements onto the real world, offering a realistic preview of how a space would look with specific design choices (Abbas, 2023). The implementation of Artificial Intelligence (AI) technology in the field of architectural design is attractive progressively globally. There is an establishment of awareness to utilise AI technology to achieve environmentally-friendly green designs for interior building spaces.

 

The construction of sustainable buildings has significantly increased in recent years worldwide due to the numerous benefits of these types of buildings. These benefits can be assembled into the following three categories:

  1. Economic benefits. The economic benefits of green buildings are abundant, the most relevant being lower energy costs as well as health and productivity benefits, water efficiency, lower construction costs and job creation (Ahmad et al., 2018; Ahmad et al., 2019; Ahmad et al., 2020).
  2. Environmental benefits. The most significant benefits of sustainable buildings are the climate and natural environment (Aftab et al., 2017).
  3. Social benefits. The other benefits of green buildings are integrated with social benefits such as wellbeing, health and increased productivity (Aftab et al., 2017).

 

The contrast is technologically oriented as they rely more on information technology (IT) than green buildings in smart or intelligent buildings (Ahn & Cho, 2017). Those buildings in which the facilities and systems (air conditioning, lighting, electricity, and security) are subject to integrated as well as automated management and control in order to increase energy efficiency, comfort and security. Generally, smart buildings are very successful in merging with building management and IT systems to dynamically augment system performance and streamline facility operations.

  

Artificial Intelligence and Environment Design

The growth of the new generation with information technology (IT) is obviously reflected in various IT tools such as big data, the Internet of Things (IoT) and artificial intelligence, especially artificial intelligence as the principal to generate efficient processes and knowledge. Yu has mentioned the scenarios of AI in environmental design, as shown in Table 1 (Park et al., 2006).

 

Table 1. AI Application

Figure 1. Roles of AI and Machine Learning (ML) in Construction Processes

Even though the implementation of artificial intelligence in the local context of environmental design was successful, as seen in big data collection, virtual reality, architectural structure and style analysis, interior furniture furnishing and style analysis, utilisation of artificial intelligence is still far behind compared with the large task system. The outline of roles and applications of AI technologies in enabling construction processes, as presented in this study, is shown in Figure 1.

 

AI for the Interior Design Industry

AI cannot replace Interior Designers as a whole as the process is of the greatest personal and creative. A human connection and interaction is a must. However, AI can assist as an enormous serving hand to interior designers. The developments of AI are meant to aid design teams by reducing overall prime times on projects and assist in developing the creativity to discovery by memorising insights from thousands, if not millions, of previous project data, using specified computer vision. 

 

This aids designers in easily finding how they can integrate specific colours, patterns, styles, or textiles into projects, dramatically reducing time, resources, and manual labour throughout projects while also providing a perfect visualisation of the client’s needs based on the information put into its system. The interior design industry is getting a much-needed makeover towards a more accessible and smarter future where everyone can enjoy the beautiful process of creating the perfect working or living space. AI can help interior design to develop the design preliminary design, conceptual digitalise, design process and BIM documentation.

 

The growth of artificial intelligence (AI) technology has changed frequent industries, and interior design is in this game as a player industry. AI tools for interior design are redesigning the way it visualises, plan, and execute design ideas, making the process more efficient, personalised, and accessible. These tools control AI's approach to analyse patterns, understand preferences, and produce design resolutions using a professional approach. Here is some AI interior design software that can be developed for the design process, as shown in Table 2 (Alex. 2023).

  

Table 2. AI Tools for Interior Design (Alex, 2023)

Conclusion

In the modernist era, the world is looking forward to implementing new technology as a fundamental method, such as Artificial Intelligence (AI), to shift in the construction industry. Regarding the rise of using a new tool in the construction industry, the implementation of AI in spatial indoor buildings was important to ensure all the trends and needs of the communities were fulfilled. In Malaysia, AI was introduced to increase the quality and efficiency of project delivery. With AI technology, it could help to enhance the cost and project duration.

In conclusion, the significant use of artificial intelligence (AI) for environmental design in indoor buildings is our greatest approach to ensuring the environment of the building is sustainable for the surrounding communities. With AI technology, the lifestyle and efficiency of quality and products will be sustained and valuable for designers and the construction industry. Furthermore, the implementation of AI for spatial indoor building is crucial for the Malaysian construction industry despite its difficult execution.

  

References

[1]    Abbas F 2023 AI in Interior Design: Transforming Spaces with Intelligent Technology, Architectural Chronical.

[2]    Ahmad M. W. Reynolds J. and Rezgui Y 2018 Predictive modelling for solar thermal energy systems: A comparison of support vector regression, random forest, extra trees and regression trees. Journal of Cleaner Production, 203, 810–821.

[3]    Ahmad T. and Chen H. 2018 Potential of three variant machine-learning models for forecasting district level medium-term and long-term energy demand in smart grid environment. Energy, 160, 1008–1020.

[4]   Ahmad T. Zhang H. and Yan B. 2020 A review on renewable energy and electricity requirement forecasting models for smart grid and buildings. Sustainable Cities and Society, 55, 102052.

[5]   Ahmad T. Chen, H. Shair J. and Xu C. 2019 Deployment of data-mining short and medium-term horizon cooling load forecasting models for building energy optimization and management. International Journal of Refrigeration, 98, 399–409.

[6]    Aftab M. Chen C. Chau C. K. and Rahwan T. 2017 Automatic HVAC control with real-time occupancy recognition and simulation-guided model predictive control in low-cost embedded system. Energy and Buildings, 154, 141–156.

[7]    Ahn J. and Cho S. 2017 Dead-band vs. machine-learning control systems: Analysis of control benefits and energy efficiency. Journal of Building Engineering, 12, 17–25.

[8]    Alavipanah S. Schreyer J. Haase D. Lakes T. and Qureshi S. 2018 The effect of multi- dimensional indicators on urban thermal conditions. Journal of Cleaner Production, 177, 115–123.

[9]    Ayhan M. Dikmen I. Talat Birgonul M 2021 Predicting the Occurrence of Construction Disputes Using Machine Learning Techniques. J. Constr. Eng. Manag. 2021147, 04021022.

[10]  Gue I. H. V. Lopez N. S. A. Chiu A. S. F. Ubando A. T. and Tan R. R. 2022 Predicting waste management system performance from city and country attributes. J. Clean. Prod. 2022366, 132951.

[11]  Pan Y. and Zhang L. 2021 Roles of artificial intelligence in construction engineering and management: A critical review and future trends. Autom. Constr. 2021122, 103517.

[12]  Park L, Kyung A, and Lee H. A 2006 Study on the design meaning development by process of analogical design thinking - focusing on the application in apartment interior design prototype. Journal of the Korean Institute of Interior Design, 15(5):77-84.

[13]  Alex M 2023 5 Best AI Interior Design Tools, https://www.unite.ai/best-ai-interior-design-tools/

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