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 | Intelligence Accident Detection and U-Turn Safety System using IOT |
|---|---|
| ABSTRACT | Due to sharp curves, narrow roads, poor visibility, and delayed access to emergency services, road accidents in hilly areas and dangerous hairpin bends pose a major threat to public safety. Signboards and mirrors are examples of conventional safety measures that are frequently insufficient to stop accidents or offer prompt assistance. This article describes an Intelligent Accident Detection and U-Turn Safety System Using IoT that was created especially for high-risk hairpin bend areas in hilly terrain in order to address these issues. The suggested system uses an Arduino Uno and an ESP8266 board to track road conditions and vehicle motion in real time. An MPU6050 IMU accelerometer is used to identify abnormal vehicle movements or abrupt impacts that point to an accident. Following the detection of an accident, the system uses a NEO-6M GPS module to obtain precise location data and sends emergency alerts via a SIM900A GSM module in the form of call and SMS notifications. |
| AUTHOR | P. PRATHAP, DR. N. SUMATHI, S. SANTHOSH Department of Information Technology, Sri Ramakrishna College of Arts & Science, Coimbatore, India |
| VOLUME | 182 |
| DOI | DOI: 10.15680/IJIRCCE. 2026.1403028 |
| pdf/28_Intelligence Accident Detection and U-Turn Safety System using IOT.pdf | |
| KEYWORDS | |
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