Photovoltaic Cells for Energy Harvesting and Indoor Positioning

被引:0
|
作者
Rizk, Hamada [1 ,2 ]
Ma, Dong [3 ]
Hassan, Mahbub [4 ]
Youssef, Moustafa [5 ,6 ]
机构
[1] Osaka Univ, Osaka, Japan
[2] Tanta Univ, Tanta, Egypt
[3] Singapore Management Univ, Singapore, Singapore
[4] Univ New South Wales, Sydney, NSW, Australia
[5] AUC, Cairo, Egypt
[6] Alexandria Univ, Cairo, Egypt
基金
日本学术振兴会; 澳大利亚研究理事会;
关键词
photovoltaic-based localization; deep learning; indoor localization; device-free localization; energy-free localization;
D O I
10.1145/3557915.3560952
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We propose SoLoc, a lightweight probabilistic fingerprinting-based technique for energy-free device-free indoor localization. The system harnesses photovoltaic currents harvested by the photovoltaic cells in smart environments for simultaneously powering digital devices and user positioning. The basic principle is that the location of the human interferes with the lighting received by the photovoltaic cells, thus producing a location fingerprint on the generated photocurrents. To ensure resilience to noisy measurements, SoLoc constructs probability distributions as a photovoltaic fingerprint at each location. Then, we employ a probabilistic graphical model for estimating the user location in the continuous space. Results show that SoLoc can localize the user at sub-meter accuracy in a real indoor environment.
引用
收藏
页码:129 / 132
页数:4
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