Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

11-2022

Abstract

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.

Keywords

Photovoltaic-based localization, Deep learning, Indoor localization, Device-free localization, Energy-free localization

Discipline

Artificial Intelligence and Robotics | Databases and Information Systems

Research Areas

Intelligent Systems and Optimization

Publication

Proceedings of the 30th International Conference on Advances in Geographic Information Systems, Seattle, Washington, USA, 2022 November 1 - 4

First Page

1

Last Page

4

ISBN

9781450395298

Identifier

10.1145/3557915.3560952

Publisher

ACM

City or Country

US

Additional URL

https://doi.org/10.1145/3557915.3560952

Download

Share

COinS