Dial It In: Rotating RF Sensors to Enhance Radio Tomography

TL;DR

This paper introduces servo-motor equipped RF sensors that autonomously adjust their position and orientation to optimize radio tomographic imaging, significantly improving localization accuracy without manual calibration.

Contribution

The paper presents a novel RTI system with servo-nodes that autonomously optimize sensor placement, enhancing localization accuracy in indoor environments.

Findings

Reduces localization error by 32% on average

Enables autonomous sensor adjustment without manual calibration

Improves RTI performance in multiple indoor settings

Abstract

A radio tomographic imaging (RTI) system uses the received signal strength (RSS) measured by RF sensors in a static wireless network to localize people in the deployment area, without having them to carry or wear an electronic device. This paper addresses the fact that small-scale changes in the position and orientation of the antenna of each RF sensor can dramatically affect imaging and localization performance of an RTI system. However, the best placement for a sensor is unknown at the time of deployment. Improving performance in a deployed RTI system requires the deployer to iteratively "guess-and-retest", i.e., pick a sensor to move and then re-run a calibration experiment to determine if the localization performance had improved or degraded. We present an RTI system of servo-nodes, RF sensors equipped with servo motors which autonomously "dial it in", i.e., change position and orientation to optimize the RSS on links of the network. By doing so, the localization accuracy of the RTI system is quickly improved, without requiring any calibration experiment from the deployer. Experiments conducted in three indoor environments demonstrate that the servo-nodes system reduces localization error on average by 32% compared to a standard RTI system composed of static RF sensors.