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Multi-User Low Intrusive Occupancy Detection.

Azkario Rizky Pratama1,2, Widyawan Widyawan3, Alexander Lazovik4

  • 1Distributed Systems Group, Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, Groningen 9747 AG, The Netherlands. a.r.pratama@rug.nl.

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Summary
This summary is machine-generated.

This study introduces a non-intrusive occupancy detection system for smart buildings. By fusing power metering and mobile phone Bluetooth signals, it achieves high accuracy in determining human presence for energy savings and safety.

Keywords:
BLE beaconsBluetooth Low Energylow-intrusiveoccupancy detectionsensor fusionsmart meter

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Area of Science:

  • Computer Science
  • Building Automation
  • Human-Computer Interaction

Background:

  • Smart buildings require real-time occupancy data for energy efficiency and safety.
  • Traditional sensing methods like cameras are often intrusive and unacceptable to occupants.
  • Existing non-intrusive methods may lack sufficient accuracy or rely on specialized hardware.

Purpose of the Study:

  • To propose and evaluate a low-intrusiveness occupancy detection system for smart office buildings.
  • To leverage commonly available office equipment for sensing human presence.
  • To improve the accuracy of occupancy detection through sensor fusion.

Main Methods:

  • Utilized room-level power metering to aggregate and disaggregate device power consumption.
  • Employed Bluetooth Low Energy (BLE) Received Signal Strength (RSS) from mobile phones for localization.
  • Implemented sensor fusion combining power data and BLE signal data.
  • Tested the system in a real office environment.

Main Results:

  • The proposed system demonstrated effective occupancy detection capabilities.
  • Sensor fusion of power metering and BLE localization achieved an accuracy of 87-90%.
  • The approach proved to be a viable, low-intrusiveness alternative to camera-based systems.

Conclusions:

  • The fusion of power metering and mobile phone-based BLE sensing offers a highly accurate and non-intrusive solution for smart building occupancy detection.
  • This method effectively utilizes existing infrastructure, making it practical for widespread adoption.
  • The system supports enhanced building management for energy savings and improved safety.