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@article{194949,
        author = {Vimala S and K Yacoob Sheriff and S Sudharson and Dr T Amutha},
        title = {CATS – CRISIS ALERT TECH SYSTEM},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {6310-6312},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194949},
        abstract = {Accident response delay is one of the major causes of increased fatalities in road incidents, especially in regions with limited access to immediate emergency services. This paper presents the design and implementation of CATS – Crisis Alert Tech System, an AI-driven, fully standalone accident detection and emergency response system. The proposed system integrates advanced embedded hardware with intelligent software to provide real-time accident detection, classification, and alert generation without requiring internet connectivity or smartphone dependency.  The system utilizes a high-performance ESP32-S3 microcontroller integrated with a multi-sensor IMU module to detect accidents based on dynamic motion analysis using a threshold-based and sensor fusion algorithm. Upon detection, the system acquires precise location data through a multi-constellation GNSS module supporting IRNSS/NavIC for enhanced accuracy in Indian regions. Emergency alerts are transmitted directly via LTE-based SMS using a cellular communication module, ensuring reliable communication even in low-connectivity environments.  A key innovation of the system is the integration of an AI-powered emergency assistant that enables voice-based panic triggering, hands-free false alarm cancellation, and intelligent emergency classification. The system achieves high accuracy in accident detection and emergency classification while maintaining low latency in alert delivery. Experimental results demonstrate an accident detection accuracy of 94.3% and end-to-end alert latency of under 10 seconds.  The proposed system provides a scalable, cost-effective, and efficient solution for enhancing road safety and reducing emergency response time.},
        keywords = {Accident Detection, Emergency Alert System, Artificial Intelligence, IoT, ESP32, GPS, LTE Communication, Smart Safety System},
        month = {March},
        }