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Lightitude

Authors :
Xufei Mao
Yanan Zhang
Panlong Yang
Xiang-Yang Li
Yan Xiong
Yiqing Hu
Wenchao Huang
Source :
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 2:1-25
Publication Year :
2018
Publisher :
Association for Computing Machinery (ACM), 2018.

Abstract

In this paper, we propose an indoor positioning system, Lightitude, which utilizes the already existed, uneven indoor light intensity distribution established by densely deployed indoor lights as the medium. As common indoor lights cannot act as landmarks due to lack of unique features (e.g., unique intensity or flicker frequency), systems that exploiting the received light intensity (RLI) usually impose strong constraints on user's motion and make ideal assumptions about the indoor environment. Different from these approaches, we first propose a realistic light intensity model to reconstruct the RLI distribution given any motion (position, orientation) of the receiver, thus RLI collected with every motion of the receiver could be used for positioning. Then we design a particle-filter-based positioning module, which harnesses user's natural mobility to eliminate the ambiguity of a single RLI. Experiment results show that Lightitude achieves mean accuracy 1.93m and 1.98m in an office (720m2) and a library (960m2) respectively. Lightitude is still robust against interferences like sunlight, shading of human-body and several user behaviors.

Details

ISSN :
24749567
Volume :
2
Database :
OpenAIRE
Journal :
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Accession number :
edsair.doi...........1dff2b927a5c5fef0892b2c8102d47d4