Automated Fall Detection for Elderly Care Leveraging IoT for Safety
Year: 2024
Type: article
Abstract: With the increasing elderly population, fall detection systems have become crucial in providing timely assistance to reduce fall-related injuries and fatalities. This project presents an IoT based fall detection system designed to monitor aged individuals in real-time, identifying sudden falls through wearable sensors and environmental data. By leveraging accelerometers, gyroscopes, and sense motions, the system detects abrupt changes in posture or unusual movements indicative of a fall. Upon detection, the system immediately sends notifications to caregivers or emergencycontacts, providing real-time alerts along with location information to facilitate quick intervention. This solution makes things safer and helps families and caregivers feel more at ease and caregivers, offering a reliable, efficient, and scalable approach to elderly care using IoT technology.
Authors: Samskruthi C, Spoorthi B R, Sriram R Kashyap, Sudhanva Aathreya B M, Jagadeesh B N
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6930472587
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