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@article{174555,
        author = {K.Komali and Panda Dinakar and N Dushyant V V Kumar and D. Durga Praveen and Regeti Suresh Kumar},
        title = {FIRE HAZARD DETECTION VIA VISION BASED MACHINE LEARNING SYSTEMS},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {4-8},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174555},
        abstract = {The objective of this project is to develop a real-time fire hazard detection system using YOLOv5, a state-of-the-art object detection algorithm. This system aims to enhance fire safety by providing timely alerts and accurate detection of fire hazards. Key features of the system include: Early detection of fire hazards, allowing for prompt action. Real-time alerts for users, ensuring immediate awareness of potential threats. High accuracy with minimal false positives, reducing unnecessary alarms. Robust performance in diverse environments, adapting to various conditions. The anticipated outcome is a reliable system for fire detection that can be effectively utilized in industrial, residential, and forest environments, ultimately contributing to enhanced safety and risk management},
        keywords = {},
        month = {March},
        }