Occupancy detection and localization strategies for demand modulated appliance control in Internet of Things enabled home energy management system. (October 2022)

• Record Type: Journal Article
• Authors: Natarajan, Anisha; Krishnasamy, Vijayakumar; Singh, Munesh
• Is Part Of: Renewable & sustainable energy reviews. Volume 167(2022)
• Publication Date: 2022-10
• Subjects: Home energy management system -- Internet of Things -- Occupancy detection -- Localization; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.rser.2022.112731
• Languages: English
• ISSNs: 1364-0321

Abstract

Abstract: Smart scheduling of domestic appliances based on user demand is an important aspect of any home energy management system. Such a demand driven operation can be performed only by accurately detecting the presence and the location of users in their residence. IoT and other enabling technologies can transform a smart home into an energy aware entity by judicious utilization of the available data. This paper presents a survey of various occupancy detection and localization schemes and evaluates them on the basis of various factors that decide their suitability for home energy management system. Wireless technologies have been historically employed for detecting unknown targets in indoor environments. The pervasiveness of WiFi access points in urban buildings render it as a preferred candidate for occupancy detection and localization. Design of device-free sensing techniques, using commercially available WiFi routers can offer an affordable solution with minimum disturbance to the inhabitants. Detection accuracy maybe enhanced by combining wireless techniques with smartphone inertial sensors and other passive detection schemes that utilize smart energy meters or environmental sensors. In contrast to commercial buildings, several challenges must be addressed for occupancy detection in home energy management system. The impact of these design challenges are investigated and feasible solutions are suggested. Highlights: Occupant centric appliance control can result in energy savings up to 40%. Device-free sensing aids in non intrusive domestic occupancy detection. Diverse sensing modalities can be combined using IoT for context acquisition. An occupant centric Home Energy Management System (HEMS) design unfolds new research challenges.