International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Human Fall Detection and Prevention System |
|---|---|
| ABSTRACT | Falls among elderly individuals are a major cause of injuries and serious health complications. To address this issue, the proposed human fall detection and prevention system integrates real-time monitoring, intelligent processing, an alert mechanism, and a mechanical stabilization feature. The system utilizes an MPU6050 sensor, which combines an accelerometer and a gyroscope, to continuously monitor human body motion. The initial stage involves analysing the pre-fall condition, followed by confirmation of a fall event. Once a pre-fall condition is detected and verified, a four-arm-based mechanical structure is automatically deployed to prevent the fall. At the same time, an SMS alert is sent to predefined emergency contacts through an Android application. By integrating detection, prevention, and communication into a single system, the proposed solution enhances safety and reduces emergency response time. The system is efficient, portable, and well-suited for real-time healthcare monitoring applications. |
| AUTHOR | GAURI M. WANKHADE, APURVA G. CHAUDHARI, AADARSH S. GAWANDE, HARSH S. THELKAR, DR. C. N. DESHMUKH Dept. of Industrial IoT, Prof. Ram Meghe Institute of Technology and Research, Badnera, Maharashtra, India |
| VOLUME | 184 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1405030 |
| pdf/30_Human Fall Detection and Prevention System.pdf | |
| KEYWORDS | |
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