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A Smart Building Resource Prediction, Navigation and Management System Supported by Radio Tomography and Computational Intelligence

Author

Listed:
  • Michał Styła

    (Research and Development Center of Information Technologies (CBRTI), 35-326 Rzeszów, Poland)

  • Przemysław Adamkiewicz

    (Research and Development Center of Information Technologies (CBRTI), 35-326 Rzeszów, Poland
    Faculty of Transport and Information Technology, University of Economics and Innovation in Lublin, 20-209 Lublin, Poland)

  • Tomasz Cieplak

    (Faculty of Management, Lublin University of Technology, 20-502 Lublin, Poland)

  • Stanisław Skowron

    (Faculty of Management, Lublin University of Technology, 20-502 Lublin, Poland)

  • Artur Dmowski

    (Faculty of Transport and Information Technology, University of Economics and Innovation in Lublin, 20-209 Lublin, Poland)

  • Józef Stokłosa

    (Faculty of Transport and Information Technology, University of Economics and Innovation in Lublin, 20-209 Lublin, Poland)

Abstract

This article presents research results on a smart building prediction, navigation and asset management system. The main goal of this work was to combine all comfort subsystems, such as lighting, heating or air conditioning control, into one coherent management system supported by navigation using radio tomographic imaging techniques and computational intelligence in order to improve the building’s ability to track users and then maximize the energy efficiency of the building by analyzing their behavior. In addition, the data obtained in this way were used to increase the quality of navigation services, improve the safety and ergonomics of using the room access control system and create a centralized control panel enriched with records of the working time of individual people. The quality of the building’s user habit learning is ensured by a network of sensors collecting environmental data and thus the setting values of the comfort modules. The advantage of such a complex solution is an increase in the accuracy of navigation services provided, an improvement in the energy balance, an improvement in the level of safety and faster facility diagnostics. The solution uses proprietary small device assemblies with implementation of popular wireless transmission standards such as Bluetooth, Wi-Fi, ZigBee or Z-Wave. These PANs (personal area networks) are used to update and transmit environmental and navigation data (Bluetooth), to maintain the connection of other PANs to the master server (Wi-Fi) and to communicate with specific end devices (ZigBee and Z-Wave).

Suggested Citation

  • Michał Styła & Przemysław Adamkiewicz & Tomasz Cieplak & Stanisław Skowron & Artur Dmowski & Józef Stokłosa, 2021. "A Smart Building Resource Prediction, Navigation and Management System Supported by Radio Tomography and Computational Intelligence," Energies, MDPI, vol. 14(24), pages 1-31, December.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:24:p:8260-:d:697696
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    References listed on IDEAS

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    1. Friedman, Jerome H. & Hastie, Trevor & Tibshirani, Rob, 2010. "Regularization Paths for Generalized Linear Models via Coordinate Descent," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i01).
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