Abstract: Worldwide, road traffic crashes continue to claim a large number of lives and cause massive economic damage. A major factor that determines survival chances is how quickly emergency services are informed after an incident. Over the past few decades, accident detection techniques have evolved from purely manual reporting to advanced automated solutions that rely on IoT devices, various sensors, computer vision, and artificial intelligence. This survey reviews the historical development, current approaches, and future trends in accident detection and notification systems, including human-dependent methods, sensor-based systems, smartphone applications, Intelligent Transportation Systems (ITS), and AI-enhanced frameworks. A comparative study reveals that modern solutions significantly outperform traditional ones by reducing response time and increasing detection accuracy. The paper concludes with remaining challenges and promising research directions for next-generation systems.
Keywords: Accelerometer, Detection, Emergency Response, IoT, Raspberry Pi, Sensors, Smart Mobility
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DOI:
10.17148/IJARCCE.2025.1411121
[1] Manasa G. K., Varsha Ranganatha, Mahalakshmi N., Maanya Arun, Ranjana S. Chakrasali, "A Comprehensive Survey of Accident Detection Methods and Their Progression," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.1411121
