Wireless sensing and the Internet of Things support real-time monitoring and data-driven control of the built environment, enabling more sustainable and responsive infrastructure. As buildings and physical structures tend to be large and complex, instrumenting them to support a wide range of applications often requires numerous sensors distributed over a large area. One impediment to this type of large-scale sensing is simply tracking where exactly devices are over time, as the physical infrastructure is updated and interacted with over time. Having low-cost but accurate localization for devices (instead of users) would enable scalable IoT network management, but current localization approaches do not provide a suitable tradeoff in terms of cost, energy, and accuracy for low power devices in unknown environments. We propose UbiTrack, a low-cost indoor positioning system that enables accurate tracking for single antenna commodity WiFi devices, without the need for a complex antenna array. UbiTrack leverages two-way channel state information (CSI) across all WiFi channels to measure the distance between nodes, and uses a new probabilistic localization algorithm based on Bayesian estimation to locate each device. We demonstrate the system on commodity $4.00 ESP32 WiFi chips and realize 1-meter level position accuracy in an indoor environment. This approach provides localization for everyday IoT devices, enabling more scalable deployments and new IoT applications.
CITATION STYLE
Wang, W., Liu, Z., Gao, J., Saoda, N., & Campbell, B. (2021). UbiTrack: Enabling scalable & low-cost device localization with onboard wifi. In BuildSys 2021 - Proceedings of the 2021 ACM International Conference on Systems for Energy-Efficient Built Environments (pp. 11–20). Association for Computing Machinery, Inc. https://doi.org/10.1145/3486611.3486646
Mendeley helps you to discover research relevant for your work.