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@article{178874,
        author = {Yogith M and Dr. Malatesh S H and Vedamitra G M and Sunil Bhandari},
        title = {Autonomous Night Safety Patrolling Car},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {4646-4651},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178874},
        abstract = {This paper presents the development and implementation of an Autonomous Night Safety Patrolling Car, designed to enhance nighttime surveillance using artificial intelligence, IoT, and embedded systems. The vehicle autonomously navigates pre-defined paths, detects obstacles using ultrasonic sensors, and captures visual data with a night vision camera. A machine learning-based audio classifier enables real-time scream detection, activating alerts and logging GPS locations upon distress events. The system is powered by Raspberry Pi 5 and integrates modules for vision, sound processing, location tracking, and motion control. Tested under low-light and noisy conditions, the prototype demonstrated reliable performance, real-time responsiveness, and operational efficiency. The proposed solution aims to augment traditional security systems in environments such as campuses, industrial zones, and residential areas, offering a scalable, cost-effective, and human-independent alternative for continuous night patrolling.},
        keywords = {Autonomous surveillance, Raspberry Pi, night patrolling robot, scream detection, IoT security, GPS tracking, machine learning, night vision, obstacle avoidance.},
        month = {May},
        }