Elderly Fall Detection System Using mm-Wave Radar Sensor

Abstract

This project focuses on the implementation of an elderly fall detection system using millimeter-wave radar technology, prioritizing privacy preservation within indoor environments. By harnessing mm-wave radar, our system offers technical advantages over camera-based solutions. Radar operates in the radio frequency spectrum, ensuring privacy, as it does not capture visual data, addressing concerns regarding surveillance and consent. Technical aspects encompass mm-wave radar sensor deployment, signal processing algorithm development for fall detection, and real-time data analysis integration. Radar mitigates issues posed by low lighting, occlusions, and line-of- sight limitations common in camera-based systems. Additionally, machine learning enhances fall detection accuracy, reducing false alarms while maintaining high sensitivity.