Author
Listed:
- ChihKun Ke
(Department of Information Management, National Taichung University of Science and Technology, Taichung 404, Taiwan)
- MeiYu Wu
(Department of Information Management, Chung Hua University, Hsinchu 300, Taiwan)
- YuWei Chan
(College of Computing and Informatics, Providence University, Taichung 433, Taiwan)
- KeCheng Lu
(Department of Information Management, National Taichung University of Science and Technology, Taichung 404, Taiwan)
Abstract
In recent years, smart homes have begun to use various sensors to detect the location of users indoors. However, such sensors may not be stable, resulting in high detection error rates. Thus, how to improve indoor positioning accuracy has become an important topic. This study explored Bluetooth Low Energy (BLE) Beacon indoor positioning for smart home power management. A novel system framework using BLE Beacon was proposed to detect the user location, and to perform power management in the home through a mobile device application. Since the BLE Beacon may produce a multipath effect, this study used the positioning algorithm and hardware configuration to reduce the error rate. Location fingerprint positioning algorithm and filter modification were used to establish a positioning method for facilitating deployment, and to reduce the required computing resources. The experiments included an observation of the Received Signal Strength Indicators (RSSI) and selecting filters and a discussion of the relationship between the characteristics of the BLE Beacon signal accuracy and the number of the BLE Beacons deployed in the observation space. The BLE Beacon multilateration positioning was combined with the In-Snergy intelligent energy management system for smart home power management. The contribution of this study is to allow users to enjoy smart home services based on their location within the home using a mobile device application.
Suggested Citation
ChihKun Ke & MeiYu Wu & YuWei Chan & KeCheng Lu, 2018.
"Developing a BLE Beacon-Based Location System Using Location Fingerprint Positioning for Smart Home Power Management,"
Energies, MDPI, vol. 11(12), pages 1-18, December.
Handle:
RePEc:gam:jeners:v:11:y:2018:i:12:p:3464-:d:189763
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