A Review of Energy Efficiency Strategies in Smart Buildings: Integrating Occupant Comfort, HVAC Optimisation, and Building Automation – Research and Reviews in Sustainability | Caravel Press
The convergence of artificial intelligence and the Internet of Things technologies is transforming how smart buildings balance energy efficiency with occupant comfort. This systematic literature review synthesises research findings published between 2015 and 2025, drawing on 52 peer-reviewed studies alongside 26 additional authoritative standards and high-quality policy reports identified through a structured search across major academic databases, targeted journals, and grey literature. The synthesis examines reported approaches to heating, ventilation, and air conditioning system optimisation, building automation, digital twin technologies, and occupantcentred control strategies, with specific attention to cold climate contexts. Artificial intelligence and Internet of Things technologies such as model predictive control, deep reinforcement learning, adaptive comfort models, and integrated indoor air quality management have been reported to deliver measurable energy savings while sustaining or enhancing occupant comfort. The best performance is achieved when active AIoT-enabled systems are combined with passive measures appropriate for the climate. Persistent challenges include gaps in interoperability between systems, data governance issues, and the scalability of solutions in retrofitted buildings. The implications for professional practice highlight the need for interoperable, cyber-secure platforms aligned with retrofit standards such as the Publicly Available Specification 2035. Future research priorities include large-scale longitudinal validation, integration with renewable energy generation and district energy systems, refinement of personalised comfort control algorithms, and the development of user engagement strategies. By mapping the current evidence base and associated challenges, this review provides a reliable foundation for accelerating the adoption of artificial intelligence and Internet of Things technologies in smart buildings, supporting the pursuit of net-zero carbon emissions while enhancing occupant wellbeing.
Keywords. AIoT; energy efficiency; HVAC optimisation; occupant comfort; smart buildings
References
Abraham, D., Yayilgan, S.Y., Abomhara, M., Gebremedhin, A. and Dalipi, F. 2022. Security and Privacy Issues in IoT-Based Smart Grids: A Case Study in a Digital Substation. Holistic Approach for Decision Making Towards Designing Smart Cities, [e-journal] 18, pp. 57–74. DOI: https://doi.org/10.1007/978-3-030-85566-6_4
Abuimara, T., Hobson, B.W., Gunay, B., O’Brien, W. and Kane, M. 2021. Current state and future challenges in building management: Practitioner interviews and a literature review. Journal of Building Engineering, [e-journal] 41, pp. 102803. DOI: https://doi.org/10.1016/j.jobe.2021.102803
Aguilar, J., Garces-Jimenez, A., R-moreno, M.D. and García, R. 2021. A systematic literature review on the use of artificial intelligence in energy self-management in smart buildings. Renewable and Sustainable Energy Reviews, [e-journal] 151, pp. 111530. DOI: https://doi.org/10.1016/j.rser.2021.111530
Ait Abdelouahid, R., Debauche, O. and Marzak, A. 2021. Internet of things: a new interoperable IoT platform. Application to a smart building. Procedia Computer Science, [e-journal] 191, pp. 511–517. DOI: https://doi.org/10.1016/j.procs.2021.07.066
Al-Habaibeh, A., Sen, A. and Chilton, J. 2021. Evaluation tool for the thermal performance of retrofitted buildings using an integrated approach of deep learning artificial neural networks and infrared thermography. Energy and Built Environment, [e-journal] 2(4), pp. 345–365. DOI: https://doi.org/10.1016/j.enbenv.2020.06.004
Amma Oforiwaa Ampomah-Asiedu, and Wepea Adamwaba Buntugu. 2024. Intelligent Energy Management in Smart Buildings Using AIoT. [e-version] Capstone Project. Ashesi University. Available at: https://air.ashesi.edu.gh/server/api/core/bitstreams/109d2a93-0553-4d51-8612-0f166d333f53/content.
Arsad, F.S., Hod, R., Ahmad, N., Baharom, M. and Ja’afar, M.H. 2023. Assessment of indoor thermal comfort temperature and related behavioural adaptations: a systematic review. Environmental Science and Pollution Research, [e-journal] 30(29), pp. 73137–73149. DOI: https://doi.org/10.1007/s11356-023-27089-9
ASHRAE. 2020a. 2020 ASHRAE Handbook—Fundamentals (SI Edition). [e-book] SI Edition ed. Atlanta, GA, USA: ASHRAE. Available through: https://www.ashrae.org/technical-resources/ashrae-handbook/2020-ashrae-handbook-fundamentals.
ASHRAE. 2020b. ANSI/ASHRAE Standard 55–2020: Thermal Environmental Conditions for Human Occupancy. [e-journal] https://www.ashrae.org/technical-resources/standards-and-guidelines/read-only-versions-of-ashrae-standards.
ASHRAE-55. 2017. Thermal Environmental Conditions for Human Occupancy. ANSI/ASHRAE Standard 55–2017. Atlanta, GA: American Society of Heating, Refrigerating and Air-Conditioning Engineers. [e- ]. https://irep.ntu.ac.uk/id/eprint/28207.
Azizi, S., Rabiee, R., Nair, G. and Olofsson, T. 2021. Effects of positioning of multi-sensor devices on occupancy and indoor environmental monitoring in single-occupant offices. Energies, [e-journal] 14(19), pp. 6296. DOI: https://doi.org/10.3390/en14196296
Bourikas, L., Gauthier, S., Khor Song En, N. and Xiong, P. 2021. Effect of thermal, acoustic and air quality perception interactions on the comfort and satisfaction of people in office buildings. Energies, [e-journal] 14(2), pp. 333. DOI: https://doi.org/10.3390/en14020333
Bresa, A. 2024. Human-centered predictive control in buildings using personalized comfort data-driven models. Human-centered predictive control in buildings using personalized comfort data-driven models, [e-journal] https://urn.nsk.hr/urn:nbn:hr:235:963503.
British Standards Institution. 2023. PAS 2035:2023 – Retrofitting dwellings for improved energy efficiency – Specification and guidance[e- ]. British Standards Institution. https://www.bsigroup.com/en-SG/insights-and-media/insights/brochures/pas-2035-retrofitting-dwellings-for-improved-energy-efficiency/.
Calabrese, F., Regattieri, A., Bortolini, M. and Galizia, F.G. 2022. Data-driven fault detection and diagnosis: Challenges and opportunities in real-world scenarios. Applied Sciences, [e-journal] 12(18), pp. 9212. DOI: https://doi.org/10.3390/app12189212
Carlsson, J. 2024. Optimization of Server Room HVAC Systems for Energy Efficiency. Leveraging CFD and AI-Driven Techniques. [e-journal] http://hdl.handle.net/20.500.12380/309033.
Chartered Institution of Building Services Engineers (CIBSE). 2021. Guide A: Environmental Design. [e-book] 8th Edition (2015, updated 2021) ed. London, United Kingdom: Chartered Institution of Building Services Engineers. Available through: https://www.cibse.org/knowledge-research/knowledge-items/detail?id=a0q3Y00000JpvcRQAR.
Chen, Z., O’Neill, Z., Wen, J., Pradhan, O., Yang, T., Lu, X., Lin, G., Miyata, S., Lee, S. and Shen, C. 2023. A review of data-driven fault detection and diagnostics for building HVAC systems. Applied Energy, [e-journal] 339, pp. 121030. DOI: https://doi.org/10.1016/j.apenergy.2023.121030
Çüce, P.M. 2025. Evaporative Cooling Technologies: From Past to Present. Global Decarbonisation, [e-journal] 2025, pp. 1–40. DOI: https://doi.org/10.17184/eac.9493. https://globaldecarbonisation.com/articles/9493.
Denyer, D. and Tranfield, D. 2009. Producing a systematic review. [e-journal] https://psycnet.apa.org/record/2010-00924-039.
Department for Business, Energy & Industrial Strategy (BEIS). 2021. Net Zero Strategy: Build Back Greener. London, United Kingdom: HM Government/Department for Business, Energy & Industrial Strategy. Available through: https://assets.publishing.service.gov.uk/media/6194dfa4d3bf7f0555071b1b/net-zero-strategy-beis.pdf.
Devaraj, S.M. 2023. The future of hvac systems: ai, cloud, and the internet of things (iot). Technology (ijcet), [e-journal] 14(2), pp. 269–278. https://www.researchgate.net/profile/Reseacher-Scholar/publication/387079141_the_future_of_hvac_systems_ai_cloud_and_the_internet_of_things_iot/links/675fac1ce9427c77e91689f2/the-future-of-hvac-systems-ai-cloud-and-the-internet-of-things-iot.pdf.
Elghaish, F., Matarneh, S., Hosseini, M.R., Tezel, A., Mahamadu, A. and Taghikhah, F. 2024. Predictive digital twin technologies for achieving net zero carbon emissions: a critical review and future research agenda. Smart and Sustainable Built Environment, [e-journal]. DOI: https://doi.org/10.1108/SASBE-03-2024-0096
Gauthier, S. and Shipworth, D. 2015. Behavioural responses to cold thermal discomfort. Building Research & Information, [e-journal] 43(3), pp. 355–370. DOI: https://doi.org/10.108 0/09613218.2015.1003277
Gowda, V.D., Samal, R., Reddy, P., Marthanda, A.G., Billady, R.K. and Rajlakshmi, P.V., eds. 2024. 2024 8th International Conference on Electronics, Communication and Aerospace Technology (ICECA) [on-line] IEEE. DOI: https://doi.org/10.1109/ICECA63461.2024.10800957
Gupta, R. and Kotopouleas, A. 2018. Magnitude and extent of building fabric thermal performance gap in UK low energy housing. Applied Energy, [e-journal] 222, pp. 673–686. DOI: https://doi.org/10.1016/j.apenergy.2018.03.096
Hajian, H. 2024. Dynamic heating control in power and energy reduction and renovation of multifamily apartment buildings. [e-journal] https://urn.fi/URN:ISBN:978-952-64-1943-5.
Himeur, Y., Elnour, M., Fadli, F., Meskin, N., Petri, I., Rezgui, Y., Bensaali, F. and Amira, A. 2023. AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives. Artificial Intelligence Review, [e-journal] 56(6), pp. 4929–5021. DOI: https://doi.org/10.1007/s10462-022-10286-2
Hou, S., Patterson, J., Tallent, E., Morewood, J., Perisoglou, E. and Ionas, M. 2023. Investigation of architects’ needs for upskilling to enable efficient and effective whole house systems-based retrofit in the UK. [e-journal] https://orca.cardiff.ac.uk/id/eprint/161834.
Hussain, I., Samara, G., Ullah, I. and Khan, N., eds. 2021. 2021 22nd international arab conference on information technology (acit) [on-line] IEEE. DOI: https://doi.org/10.1109/ACIT53391.2021
International Energy Agency (IEA). 2023. World Energy Outlook 2023. Paris, France: International Energy Agency. Available through: https://iea.blob.core.windows.net/assets/ed1e4c42-5726-4269-b801-97b3d32e117c/WorldEnergyOutlook2023.pdf.
Inthasuth, T., Kaewjumras, Y. and Sahapong Somwong, W.B. 2025. Comparative analysis of ZigBee, LoRa, and NB-IoT in a smart building: advantages, limitations, and integration possibilities. Int J Reconfigurable & Embedded Syst, [e-journal] 14(1), pp. 165–175. DOI: https://doi.org/10.11591/ijres.v14.i1.pp165-175
Jia, M., Srinivasan, R.S. and Raheem, A.A. 2017. From occupancy to occupant behavior: An analytical survey of data acquisition technologies, modeling methodologies and simulation coupling mechanisms for building energy efficiency. Renewable and Sustainable Energy Reviews, [e-journal] 68, pp. 525–540. DOI: https://doi.org/10.1016/j.rser.2016.10.011
Kim, J., Bang, J., Choi, A., Moon, H.J. and Sung, M. 2023. Estimation of occupancy using IoT sensors and a carbon dioxide-based machine learning model with ventilation system and differential pressure data. Sensors, [e-journal] 23(2), pp. 585. DOI: https://doi.org/10.3390/s23020585
Kumar, A., Sharma, S., Goyal, N., Singh, A., Cheng, X. and Singh, P. 2021. Secure and energy-efficient smart building architecture with emerging technology IoT. Computer Communications, [e-journal] 176, pp. 207–217. DOI: https://doi.org/10.1016/j.comcom.2021.06.003
Lin, J., Fernández, J.A., Rayhana, R., Zaji, A., Zhang, R., Herrera, O.E., Liu, Z. and Mérida, W. 2022. Predictive analytics for building power demand: Day-ahead forecasting and anomaly prediction. Energy and Buildings, [e-journal] 255, pp. 111670. DOI: https://doi.org/10.1016/j.enbuild.2021.111670
Lohia, K., Jain, Y., Patel, C. and Doshi, N. 2019. Open communication protocols for building automation systems. Procedia Computer Science, [e-journal] 160, pp. 723–727. DOI: https://doi.org/10.1016/j.procs.2019.11.020
Lu, X., O’Neill, Z., Li, Y. and Niu, F. 2020. A novel simulation-based framework for sensor error impact analysis in smart building systems: A case study for a demand-controlled ventilation system. Applied Energy, [e-journal] 263, pp. 114638. DOI: https://doi.org/10.1016/j.apenergy.2020.114638
Markowitz, J. and Drenkow, N. 2024. Efficient HVAC Control with Deep Reinforce-ment Learning and EnergyPlus. [e-journal] https://s3.us-east-1.amazonaws.com/climate-change-ai/papers/iclr2023/58/paper.pdf.
Márquez-Sánchez, S., Calvo-Gallego, J., Erbad, A., Ibrar, M., Fernandez, J.H., Houchati, M. and Corchado, J.M. 2023. Enhancing building energy management: adaptive edge computing for optimized efficiency and inhabitant comfort. Electronics, [e-journal] 12(19), pp. 4179. DOI: https://doi.org/10.3390/electronics12194179
Masi, D., Day, S. and Godsell, J. 2017. Supply chain configurations in the circular economy: A systematic literature review. Sustainability, [e-journal] 9(9), pp. 1602. DOI: https://doi.org/10.3390/su9091602
Melo, F.C., da Graça, G.C. and Panão, M.J.O. 2023. A review of annual, monthly, and hourly electricity use in buildings. Energy and Buildings, [e-journal] 293, pp. 113201. DOI: https://doi.org/10.1016/j.enbuild.2023.113201
Osamudiamen, B.B. and Ugbodaga, M. 2024. Integration of Artificial Intelligence and Internet of Things in Smart Building Systems: a Study on Energy Efficiency and Occupant Experience. Spanish Journal of Innovation and Integrity, [e-journal] 36, pp. 73–85. https://www.sjii.es/index.php/journal/article/view/15
Page, M.J., McKenzie, J.E., Bossuyt, P.M., Boutron, I., Hoffmann, T.C., Mulrow, C.D., Shamseer, L., Tetzlaff, J.M., Akl, E.A. and Brennan, S.E. 2021. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. bmj, [e-journal] 372. DOI: https://doi.org/10.1136/bmj.n71
Pang, Z., Guo, M., Smith-Cortez, B., O’Neill, Z., Yang, Z., Liu, M. and Dong, B. 2024. Quantification of HVAC energy savings through occupancy presence sensors in an apartment setting: Field testing and inverse modeling approach. Energy and Buildings, [e-journal] 302, pp. 113752. DOI: https://doi.org/10.1016/j.enbuild.2023.113752
Rutkowski, R., Raczyński, M., Iwańkowicz, R. and Nowak, R. 2024. Digital Twin in the Design and Dynamic Assessment of Energy Performance of Multi-Family Buildings. Energies, [e-journal] 17(23), pp. 6150. DOI: https://doi.org/10.3390/en17236150
Simpeh, E.K., Pillay, J.G., Ndihokubwayo, R. and Nalumu, D.J. 2022. Improving energy efficiency of HVAC systems in buildings: a review of best practices. International Journal of Building Pathology and Adaptation, [e-journal] 40(2), pp. 165–182. DOI: https://doi.org/10.1108/IJBPA-02-2021-0019
Smith, M., Hosking, J., Woodward, A., Witten, K., MacMillan, A., Field, A., Baas, P. and Mackie, H. 2017. Systematic literature review of built environment effects on physical activity and active transport–an update and new findings on health equity. International journal of behavioral nutrition and physical activity, [e-journal] 14(1), pp. 158. DOI: https://doi.org/10.1186/s12966-017-0613-9
Suman, S., Calautit, J.K., Wei, S., Tien, P.W., Chen, X., Wang, Z. and Sun, H. 2025. Assessing the Energy-Saving Potential of Passive Strategies in Commercial Buildings in the Top Upcoming Megacities. Energy Catalyst, [e-journal] 1(1), pp. 1–21. DOI: https://doi.org/10.61552/EC.2025.001
Tapia-Brito, E. and Riffat, S. 2025. Design and performance analysis of a MopFan-based multi-stage air purification system for indoor pollution control. Green Technology & Innovation, [e-journal] 7100. https://accscience.com/journal/GTI/articles/online_first. DOI: https://doi.org/10.36922/ gti.7100
UNEP. 2020. Global Alliance for Buildings and Construction 2020 GLOBAL STATUS REPORT FOR BUILDINGS AND CONSTRUCTION [e- ]. https://globalabc.org/resources/publications/2020-global-status-report-buildings-and-construction.
Zhao, Y. and Yang, Q., eds. 2022. IOP Conference Series: Earth and Environmental Science [on-line] IOP Publishing. DOI: https://doi.org/10.1088/1755-1315/974/1/012001
How to cite this article
Onweh, C.C., Al-Habaibeh, A. and Manu, E. (2025). 'A Review of Energy Efficiency Strategies in Smart Buildings: Integrating Occupant Comfort, HVAC Optimisation, and Building Automation'. Research and Reviews in Sustainability, 1, pp. 48-60. https://doi.org/10.5334/rss.9
