Development of a Smart Floor for Target Localization with Bayesian Binary Sensing

This paper presents an encoded smart floor for multiple human localization, include binary sensor designing, space encoding and decoding scheme. This system can localize a group of people, as well as recognize associated scenarios, with high sensing efficiency and low computational complexity. The novelty of this work includes: (1) a set of code design for binary sensor deployment, (2) a Bayesian inference based decoding scheme in the context of activity and scenario recognition. The proposed scheme has been tested with pressure sensors, and the experiment results have demonstrated the superior performance of our design.