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@article{168956,
        author = {Dr. S. MOHANA and Vijaya Varman T and Naveen M V and Sachidanandam K and Sai Prasath S},
        title = {WOMEN SAFETY ANALYSIS USING CNN & KNN ALGORITHM},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {686-693},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=168956},
        abstract = {The project titled “Kannaamma Kaaval” focuses on developing a mobile application dedicated to ensuring women's safety. Inspired by Bharathiyar’s poem "Kannaamma" symbolizing love and protection, the app empowers women with real-time assistance, emergency response tools, and community support. Key features include an emergency alert system, live location sharing, incident documentation, Surveillance cam-based route , and self-defense tutorials .The app also integrates advanced technologies like AI-powered safety companions, smart rings, and watches, and aims to use machine learning for detecting distress signals. Developed using technologies such as Android Studio, Firebase, and Google Maps API, this app seeks to bridge the gap between fear and security, enabling women to live freely and securely.},
        keywords = {Deep Learning, Convolutional Neural Networks, K- Nearest Neighbour Algorithm , Image Classification , FER Dataset, Gender Identification, Action Monitoring.},
        month = {November},
        }