Falls are a leading cause of injury among the elderly and individuals with mobility challenges, often resulting in serious health complications and a reduced quality of life. Early detection of falls is crucial for ensuring timely medical intervention and enhancing personal safety. In this work, we present a light, wearable fall detection system that leverages gait analysis to accurately monitor and identify fall events in real-time. Designed to be unobtrusive and comfortable, the device continuously tracks subtle changes in a person's walking patterns, balance, and posture using advanced sensor technology.