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Multi-User Low Intrusive Occupancy Detection

Distributed Systems Group, Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, Groningen 9747 AG, The Netherlands
Department of Electrical Engineering and Information Technology, Universitas Gadjah Mada, Daerah Istimewa Yogyakarta 55281, Indonesia
Author to whom correspondence should be addressed.
Sensors 2018, 18(3), 796;
Received: 15 January 2018 / Revised: 28 February 2018 / Accepted: 28 February 2018 / Published: 6 March 2018
(This article belongs to the Special Issue Advances in Sensors for Sustainable Smart Cities and Smart Buildings)
Smart spaces are those that are aware of their state and can act accordingly. Among the central elements of such a state is the presence of humans and their number. For a smart office building, such information can be used for saving energy and safety purposes. While acquiring presence information is crucial, using sensing techniques that are highly intrusive, such as cameras, is often not acceptable for the building occupants. In this paper, we illustrate a proposal for occupancy detection which is low intrusive; it is based on equipment typically available in modern offices such as room-level power-metering and an app running on workers’ mobile phones. For power metering, we collect the aggregated power consumption and disaggregate the load of each device. For the mobile phone, we use the Received Signal Strength (RSS) of BLE (Bluetooth Low Energy) nodes deployed around workspaces to localize the phone in a room. We test the system in our offices. The experiments show that sensor fusion of the two sensing modalities gives 87–90% accuracy, demonstrating the effectiveness of the proposed approach. View Full-Text
Keywords: occupancy detection; low-intrusive; Bluetooth Low Energy; BLE beacons; smart meter; sensor fusion occupancy detection; low-intrusive; Bluetooth Low Energy; BLE beacons; smart meter; sensor fusion
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MDPI and ACS Style

Pratama, A.R.; Widyawan, W.; Lazovik, A.; Aiello, M. Multi-User Low Intrusive Occupancy Detection. Sensors 2018, 18, 796.

AMA Style

Pratama AR, Widyawan W, Lazovik A, Aiello M. Multi-User Low Intrusive Occupancy Detection. Sensors. 2018; 18(3):796.

Chicago/Turabian Style

Pratama, Azkario R., Widyawan Widyawan, Alexander Lazovik, and Marco Aiello. 2018. "Multi-User Low Intrusive Occupancy Detection" Sensors 18, no. 3: 796.

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