AI-Powered Women's Safety Ecosystem with Proactive Risk Analytics

The AI-Powered Women's Safety Ecosystem shifts the paradigm from reactive SOS alerts to proactive risk prevention. By integrating K-Means clustering for heatmaps, Random Forest for risk scoring, A* for safe routing, and on-device AI (YAMNet/LSTM) for autonomous detection, the system provides a comprehensive safety net. Future work will focus on pilot testing the application with college campuses and NGOs to validate the risk scoring accuracy and emergency response times.

[1] National Crime Records Bureau, "Crime in India 2024," Ministry of Home Affairs, New Delhi, 2024. [2] Red Elephant, "Safety App Survey," New Delhi, 2016. [3] J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd ed., vol. 2. Oxford: Clarendon, 1892, pp.68-73. (Replace with actual research papers you referenced for K-Means, A, YAMNet, etc.)* [4] R. Nicole, "Title of paper with only first word capitalized," J. Name Stand. Abbrev., in press. [5] "A Bi-Lingual Counselling Chatbot Application for Support of Gender Based Violence Victims in Kenya," 2024 5th International Conference on..., 2024. (This paper uses the Rasa framework to build a support chatbot for violence victims.) [6] "A Machine Learning Based Victim's Scream Detection System for Burning Sites Using an Autonomous Embedded System Vehicle," 2021. (This paper uses YAMNet for transfer learning to detect victim screams.) [7] "An LSTM-Based Approach for Fall Detection Using Accelerometer-Collected Data," 2021. (This paper uses LSTM for smartphone-based fall detection.) [8] "A Blockchain-based Integrity Layer for Android Forensic Chain-of-Custody Verification," 2026 IEEE International Conference on..., 2026. (This paper uses SHA-256 hashes for mobile forensic chain-of-custody.