Wireless energy efficient occupancy-monitoring system for smart buildings

Lasla, Noureddine; Doudou, Messaoud; Djenouri, Djamel; Ouadjaout, Abdelraouf; Zizoua, Cherif

Abstract

© 2019 Elsevier B.V. Rationalizing energy consumption in smart buildings is considered in this paper, and a wireless monitoring system based on Passive Infrared sensors (PIRs) is proposed. The proposed system is pervasive and can be integrated in existing buildings without any complicated wiring or setting. Realistic constraints are considered for this purpose such as sensing-hole, battery limitation, user comfort, etc. To ensure maximum coverage in presence of holes, the optimal placement of PIRs is formulated as a mixed integer linear programming optimization problem (MILP). Experimentations have been carried out to quantify the effects of the holes on the detection accuracy and to demonstrate the impact of the optimal PIRs placement on energy consumption. To facilitate installation and integration without complicated settings, notably in existing buildings, the system is designed to be battery operated. Therefore, energy efficiency will not be limited to optimize energy consumption in buildings, but also to optimize consumption in the components of the system (sensors and actuators). Duty cycling is inevitable to extend the network lifetime of such components, but the setting of this cycle yields a trade-off in optimizing the energy consumption i) at the building level, vs., ii) that consumed by sensors and actuators. Reducing energy consumption (duty cycle) of sensors/actuators will delay non-occupancy detections and thus will increase the building energy wastage, and vice-versa. Duty cycling the radios is dealt with and modeled as a cooperative game, which allows to derive a Nash Bargaining as the optimal balancing cycle. The proposed approach is analytically investigated using realistic parameters of the existing hardware and users’ comfort. The results demonstrate that the system can survive for more than 6 years without battery replacement.

• Journal Article Type: Article
• Acceptance Date: Jun 20, 2019
• Online Publication Date: Jun 26, 2019
• Publication Date: Oct 1, 2019
• Deposit Date: Jan 21, 2020
• Publicly Available Date: Jun 27, 2020
• Journal: Pervasive and Mobile Computing
• Print ISSN: 1574-1192
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 59
• Article Number: 101037
• DOI: https://doi.org/10.1016/j.pmcj.2019.101037
• Public URL: https://uwe-repository.worktribe.com/output/5193113
• Publisher URL: https://doi.org/10.1016/j.pmcj.2019.101037