Smart Rider Safety Enforcement System- Using AI and IOT

Road safety for two-wheeler riders remains a critical global concern, with high mortality rates attributed to helmet negligence, alcohol-impaired riding, and driver drowsiness. Conventional enforcement relies on manual checks that fail to ensure continuous compliance and are incapable of real-time intervention. This paper presents the Smart Rider Safety Enforcement System (SRSES), which leverages IoT sensor arrays and AI-based processing to provide real-time monitoring and automated multi-stage enforcement. A novel speed-conditional Monitoring Function M eliminates 100% of false-positive violations during stationary states such as traffic signal stops—the primary failure mode of prior art. A five-stage progressive enforcement protocol transitions from audio warnings to speed restriction at 30 km/h and automated fine issuance via GSM SMS. AI-based drowsiness detection using computer vision improves on sensor-only approaches by 15%. Experimental results demonstrate significant improvements in compliance rates and safety margins compared to traditional ignition-interlock systems, with practical power consumption compatible with standard motorcycle electrical systems.