Affiliation:
1. Global Academy of Technology, Bengaluru, India
Abstract
Individual’s safety and well-being in public settings, particularly for women, have emerged as major concerns in modern society. Enhancing public safety by analysing women’s screams and focusing on the detection of suspicious activities and timely intimating it to the nearby police station and preferred contacts. Proposing a comprehensive system that integrates advanced audio processing techniques, machine learning algorithms, real-time communication mechanisms, combination of geospatial technology, mobile applications and sensors connected to wearable devices provides security alerts. This comprehensive approach aims to create a safer environment and empower women to take control of their safety. It’s a wonder technology and community involvement for a greater impact. By using advanced audio processing and machine learning techniques, the system can identify specific patterns or characteristics in screams that may indicate a potential threat. This innovative approach aims to enhance public safety and provide early warning signs in emergency situations. It’s an interesting application of technology that could help improve response times and prevent incidents
Reference25 articles.
1. [1] M. S. Farooq, A. Masooma, U. Omer, R. Tehseen, S. A. M. Gilani and Z. Atal, ““The Role of IoT in Woman’s Safety: A Systematic Literature Review,” in IEEE Access, vol. 11, pp. 69807-69825,2023, DOI:10.1109/ACCESS.2023.325903
2. [2] Dr. Madhurya Saikia & Dr. Niranjan Bora Citation: Sarma P, Ahmed D, Bezbaruah P (2023) “Android-Based WomanSafety App”. IndianJournal of Science and Technology 16(SP2): 6069.https://doi.org/10.17485/IJST/v16iSP2.8767
3. [3] DR. Chanda V Reddy, Sabarish J, Samiksha S, Sathvik U M, Swagath Aithal P G, “LITERATURE SURVEY ON WOMEN SAFETY DEVICE”, International Advanced Research Journal in Science, Engineering and Technology Impact Factor 7.12Vol. 10, Issue1, January2023
4. [4] Rutuja Thore, Dhanashree Kamdi, Shravani Kalaskar, Srushti Dungarwal, “WOMEN SAFETY DEVICE WITH GPS TRACKING AND ALERTS USING ARDUINO,” e-ISSN: 2582-5208 International Research Journal of Modernization in Engineering Technology and Science Volume:05/Issue:12/December-2023 Impact Factor- 7.868 www.irjmets.com
5. [5] Bhuva, Nilamben, “HUMAN SUSPICIOUS ACTIVITY DETECTION" (2023). Electronic Theses, Projects and Dissertation.1637. https: :// scholarworks.lib.csub.edu/etd/1637