Sustainable Smart Buildings with AI-Based Energy Management

  • Authors

    • Dr. Meena Krishnan Assistant Professor, Anna University, India. Author

    DOI:

    https://doi.org/10.67228/30715628/IJMIET-2018PI8WQ1

    Published 05-04-2018

  • Sustainable Buildings, Smart Buildings, Artificial Intelligence, Energy Management Systems, Machine Learning, Iot, Energy Optimization, Green Buildings, Predictive Analytics

    Issue

    Vol. 1 No. 1 (2018)

    Section

    Articles

    How to Cite

    [1]
    M. Krishnan, “Sustainable Smart Buildings with AI-Based Energy Management”, ijmiet, vol. 1, no. 1, pp. 01–13, May 2018, doi: 10.67228/30715628/IJMIET-2018PI8WQ1.

  • Abstract

    Sustainable solutions in the built environment have become essential due to rapid urbanization and rising energy demands. Buildings account for nearly 40% of global energy consumption, making them a critical focus for energy efficiency and environmental sustainability. This paper explores AI-driven energy management systems in smart buildings, highlighting their ability to optimize energy use, reduce costs, and minimize environmental impact while maintaining occupant comfort. By integrating technologies such as IoT, machine learning, predictive analytics, and automation, these systems enable real-time monitoring and adaptive energy optimization. The study reviews traditional building management systems and identifies their limitations, proposing a layered architecture involving data acquisition, processing, prediction, and control. Machine learning techniques like ANN, SVM, and Reinforcement Learning are evaluated for energy forecasting and optimization. Findings indicate that AI-based systems can significantly improve energy efficiency, reduce carbon emissions, and enhance comfort, though challenges such as data privacy, system complexity, and initial costs remain. The research provides a practical framework for developing sustainable, energy-efficient smart buildings.

  • References

    [1] D. Kolokotsa, “The role of smart grids in the building sector,” Energy and Buildings, vol. 116, pp. 703–708, 2016.

    [2] G. Levermore, Building Energy Management Systems: Applications to Low-Energy HVAC and Natural Ventilation Control, 2nd ed. London, U.K.: CRC Press, 2000.

    [3] S. Wang and Z. Ma, “Supervisory and optimal control of building HVAC systems: A review,” HVAC&R Research, vol. 14, no. 1, pp. 3–32, 2008.

    [4] A. Afram and F. Janabi-Sharifi, “Theory and applications of HVAC control systems – A review of model predictive control (MPC),” Building and Environment, vol. 72, pp. 343–355, 2014.

    [5] L. Atzori, A. Iera, and G. Morabito, “The Internet of Things: A survey,” Computer Networks, vol. 54, no. 15, pp. 2787–2805, 2010.

    [6] J. Gubbi, R. Buyya, S. Marusic, and M. Palaniswami, “Internet of Things (IoT): A vision, architectural elements, and future directions,” Future Generation Computer Systems, vol. 29, no. 7, pp. 1645–1660, 2013.

    [7] M. Pipattanasomporn, H. Feroze, and S. Rahman, “Multi-agent systems in a distributed smart grid: Design and implementation,” IEEE PES General Meeting, 2009.

    [8] Y. Agarwal et al., “Occupancy-driven energy management for smart building automation,” Proceedings of ACM BuildSys, pp. 1–10, 2010.

    [9] K. P. Lam, M. Höynck, B. Dong, B. Andrews, Y. Chiou, and D. Benitez, “Occupancy detection through an extensive environmental sensor network in an open-plan office building,” IBPSA Conference, 2009.

    [10] H. B. Gunay, W. O’Brien, and I. Beausoleil-Morrison, “A critical review of observation studies, modeling, and simulation of adaptive occupant behaviors in offices,” Building and Environment, vol. 70, pp. 31–47, 2013.

    [11] V. Vapnik, The Nature of Statistical Learning Theory. New York, NY, USA: Springer, 1995.

    [12] L. A. Zadeh, “Fuzzy sets,” Information and Control, vol. 8, no. 3, pp. 338–353, 1965.

    [13] X. Zhao and S. Magoulès, “A review on the prediction of building energy consumption,” Renewable and Sustainable Energy Reviews, vol. 16, no. 6, pp. 3586–3592, 2012.

  • Downloads

Similar Articles

61-70 of 83

You may also start an advanced similarity search for this article.