A Room-Level Indoor Localization Using an Energy-Harvesting BLE Tag

Abstract

Energy-efficient and cost-effective localization systems are attractive for large-scale tracking and localization of goods. In this paper, we propose a room-level localization system using energy-harvesting BLE tags to track the targets. We introduce the Dempster–Shafer (D–S) evidence theory combined with fingerprinting technology for location estimation. To reduce the estimation complexity, we divide the indoor environment into clear areas and fuzzy areas. The D–S algorithm is employed to locate the target in the clear areas when the targets are only detected by the anchor nodes within a single room. Conversely, fuzzy areas are characterized by RSSI signals detected by anchor nodes across multiple rooms. Then, the system integrates fingerprint matching to ensure superior positioning accuracy across the deployment. Extensive experiments demonstrate that the proposed system maintains a room-level positioning accuracy above 99% under standard test conditions within an area of approximately 2000 m2 with lots of rooms.