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@article{177303,
        author = {Rushabh Bhusanur and Vaishnav Salunke and Abhinav PAwar and Dr. V. M. Sardar},
        title = {Women Safety Multi-Point Alerts Specifying Disasters by IoT},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {574-578},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=177303},
        abstract = {Women’s safety is a growing concern worldwide, and technology plays a crucial role in ensuring security. This research paper proposes an IoT-based multi-point alert system that detects potential dangers and disasters, ensuring real-time responses. The system integrates sensors, GPS, GSM, and cloud computing to provide automated alerts in emergencies, minimizing response time and enhancing security measures. Women’s safety remains a critical concern, requiring innovative solutions to ensure quick response during emergencies. This paper presents an IoT-based Women Safety Multi-Point Alert System, designed to detect and specify disasters such as harassment, assault, accidents, or natural calamities. The system integrates wearable smart devices, GPS, and real-time monitoring to provide location tracking and distress alerts. Upon activation through voice, gesture, or panic button, the system triggers multi-point notifications to emergency contacts, law enforcement, and nearby responders via mobile networks and cloud-based services. Additionally, sensor-based environmental detection helps classify threats, ensuring precise situational awareness. This approach leverages machine learning and IoT connectivity to enhance security, reduce response time, and provide a scalable model for real world implementation.},
        keywords = {},
        month = {May},
        }