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Analyzing and Managing Various Energy-Related Environmental Factors for Providing Personalized IoT Services for Smart Buildings in Smart Environment

Author

Listed:
  • Prabhakar Krishnan

    (Center for Cybersecurity Systems and Networks, Amrita Vishwa Vidyapeetham, Amritapuri-Campus, Kollam 690525, Kerala, India)

  • A V Prabu

    (Department of Electronics and Computer Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram 522502, Guntur, Andhra Pradesh, India)

  • Sumathi Loganathan

    (Deartment of Computer Science, Thanthai Hans Roever College, Perambalur 621212, Tamil Nadu, India)

  • Sidheswar Routray

    (Department of Computer Science and Engineering, School of Engineering, Indrashil University, Rajpur, Mehsana 382740, Gujarat, India)

  • Uttam Ghosh

    (Department of CS & DS, Meharry Medical College, Nashville, TN 37203, USA)

  • Mohammed AL-Numay

    (Electrical Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia)

Abstract

More energy is consumed by domestic appliances all over the world. By reducing energy consumption, sustainability can be improved in domestic contexts. Several earlier approaches to this problem have provided a conceptual overview of green and smart buildings. This paper aims to provide a better solution for reducing energy consumption by identifying the fields of abnormal energy consumption. It creates a better environment-friendly smart building to adopt the various lifestyles of people. This paper’s main objective is to monitor and control the energy efficiency of smart buildings by integrating IoT sensors. This paper mainly analyzes various prime factors that can help to improve energy efficiency in smart buildings. Factors impacting energy consumption are analyzed, and outliers of energy consumption are predicted and optimized to save energy. Various parameters are derived from IoT devices to improve energy efficiency in lighting and HVAC controls, energy monitoring, building envelope and automation systems, and renewable energy. The parameters used in water, network convergence, and electrical and environmental monitoring are also used for improving energy efficiency. This paper uses various IoT devices for monitoring and generating data in and around a smart building and analyzes it by implementing an intelligent Information Communication Technology (ICT) model called the Dynamic Semantic Behavior Data Analysis (DSBDA) Model to analyze data concerning dynamic changes in the environment and user behavior to improve energy efficiency and provide better sustainable lifestyle-based smart buildings. From the analyzed output, the outliers of the power consumption and other abnormalities are identified and controlled manually or automatically to improve sustainability regarding energy use in smart buildings.

Suggested Citation

  • Prabhakar Krishnan & A V Prabu & Sumathi Loganathan & Sidheswar Routray & Uttam Ghosh & Mohammed AL-Numay, 2023. "Analyzing and Managing Various Energy-Related Environmental Factors for Providing Personalized IoT Services for Smart Buildings in Smart Environment," Sustainability, MDPI, vol. 15(8), pages 1-21, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6548-:d:1121956
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    References listed on IDEAS

    as
    1. Marek Dudzik, 2020. "Towards Characterization of Indoor Environment in Smart Buildings: Modelling PMV Index Using Neural Network with One Hidden Layer," Sustainability, MDPI, vol. 12(17), pages 1-37, August.
    2. César Benavente-Peces, 2019. "On the Energy Efficiency in the Next Generation of Smart Buildings—Supporting Technologies and Techniques," Energies, MDPI, vol. 12(22), pages 1-25, November.
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    Cited by:

    1. Amjad Almusaed & Ibrahim Yitmen & Asaad Almssad, 2023. "Reviewing and Integrating AEC Practices into Industry 6.0: Strategies for Smart and Sustainable Future-Built Environments," Sustainability, MDPI, vol. 15(18), pages 1-27, September.

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