Automated Fall Detection for Elderly Care Leveraging IoT for Safety
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.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2024-12-20
- DOI
- https://doi.org/10.5281/zenodo.14534384
- Primary Topic
- Context-Aware Activity Recognition Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00