Motion Detection using CSI from Raspberry Pi 4

TL;DR

This paper presents a novel, self-calibrating motion detection system using CSI data on a Raspberry Pi 4, accurately tracking movement duration without line-of-sight constraints.

Contribution

The authors developed a new CSI-based motion detection method that is self-calibrating and effective in real-world environments using a Raspberry Pi 4.

Findings

Accurately detects activity start and end times across various environments.

Effective in different locations and motion intensities.

Uses variance analysis of CSI frames for movement measurement.

Abstract

Monitoring behaviour in smart homes using sensors can offer insights into changes in the independent ability and long-term health of residents. Passive Infrared motion sensors (PIRs) are standard, however may not accurately track the full duration of movement. They also require line-of-sight to detect motion which can restrict performance and ensures they must be visible to residents. Channel State Information (CSI) is a low cost, unintrusive form of radio sensing which can monitor movement but also offers opportunities to generate rich data. We have developed a novel, self-calibrating motion detection system which uses CSI data collected and processed on a stock Raspberry Pi 4. This system exploits the correlation between CSI frames, on which we perform variance analysis using our algorithm to accurately measure the full period of a resident's movement. We demonstrate the effectiveness of this approach in several real-world environments. Experiments conducted demonstrate that activity start and end time can be accurately detected for motion examples of different intensities at different locations.