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@article{175649,
        author = {K.Kavitha and G.G.V.Sai and G.Bhanu Prasad and Sk.Nasiruddin},
        title = {INTELLIGENT ACCIDENT PREVENTION SYSTEM  USING MACHINE LEARNING AND  EMBEDDED SYSTEMS},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {3450-3459},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175649},
        abstract = {The growing number of road accidents caused by drowsiness, drinking alcohol, and sudden health conditions emphasizes the need for a new sophisticated vehicle accident prevention system. The project involves several sensors, such as an alcohol sensor and heart rate sensor, integrated with a Raspberry Pi based system. The information is processed using machine learning algorithms to predict accidents based on threshold values. When a dangerous state is detected, an alert message is generated using a GSM module, with a buzzer sounding to give an alarm. The system promotes safety on the road with monitoring and early warnings, which are expected to lower accident levels.},
        keywords = {Accident Prevention, Machine Learning, Raspberry Pi, Heartbeat Monitoring, Alcohol Detection, GPS, GSM Alert},
        month = {April},
        }