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@article{209365,
        author = {UshaDevi M B and Hitha GP Jain and Likhitha GR and Unnathi S and Hamsini V},
        title = {Ai Integrated Smart Helmet},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {5},
        pages = {2702-2706},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=209365},
        abstract = {Two-wheeler riders are exposed to multiple safety risks including non-use of helmets, alcohol-impaired riding, sudden impacts and delayed emergency response after an accident. This paper presents the design of an Al-integrated smart helmet intended to combine preventive safety, accident detection, location tracking and emergency communication in a single wearable system. The proposed architecture uses ESP32 controllers, an IR sensor for helmet-wearing verification, an alcohol sensor, an ADXL-series motion/impact sensor, RF transmitter receiver communication, a relay interface. GPS, GSM and an ESP32-CAM.'TIkamcra-bascd imaging unit. Sensor information is processed at the helmet and vehicle units. The vehicle is enabled only when the received safety status satisfies the defined conditions. When an abnormal impact or accident condition is detected, the camera captures accident evidence. GPS provides the riders location and GSM communicates an emergency alert to predefined contacts. Machine learning is included as thc intended intelligent layer for improving accident-risk recognition beyond simple threshold decisions. The proposed system therefore combines sensing, local decision making, wireless communication, visual evidence and emergency notification. The design is motivated by previous smart-helmet research showing the value of multimodal sensing, IoT connectivity and automated alerts, while addressing the need for a more integrated safety architecture.},
        keywords = {},
        month = {October},
        }