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Intelligent Sensors and Environment Driven Biological Comfort Control Based Smart Energy Consumption System

Research output: Contribution to Journal/MagazineJournal articlepeer-review

  • Muhammad Asim Nawaz
  • Bilal Khan
  • Sahibzada Muhammad Ali
  • Muhammad Awais
  • Muhammad Bilal Qureshi
  • Muhammad Jawad
  • Chaudhry Arshad Mehmood
  • Zahid Ullah
  • Sheraz Aslam
Article numbere2622
<mark>Journal publication date</mark>21/08/2022
<mark>Journal</mark>Electronics (Switzerland)
Issue number16
Number of pages26
Publication StatusPublished
<mark>Original language</mark>English


The smart energy consumption of any household, maintaining the thermal comfort level of the occupant, is of great interest. Sensors and Internet-of-Things (IoT)-based intelligent hardware setups control the home appliances intelligently and ensure smart energy consumption, considering environment parameters. However, the effects of environment-driven consumer body dynamics on energy consumption, considering consumer comfort level, need to be addressed. Therefore, an Energy Management System (EMS) is modeled, designed, and analyzed with hybrid inputs, namely environmental perturbations, and consumer body biological shifts, such as blood flows in skin, fat, muscle, and core layers (affecting consumer comfort through blood-driven-sensations). In this regard, our work incorporates 69 Multi-Node (MN) Stolwijik’s consumer body interfaced with an indoor (room) electrical system capable of mutual interactions exchange from room environmental parameters and consumer body dynamics. The mutual energy transactions are controlled with classical PID and Adaptive Neuro-Fuzzy-Type II (NF-II) systems inside the room dimensions. Further, consumer comfort, room environment, and energy consumption relations with bidirectional control are demonstrated, analyzed, and tested in MATLAB/Simulink to reduce energy consumption and energy cost. Finally, six different cases are considered in simulation settings and for performance validation, one case is validated as real-time hardware experimentation.