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Safety Detection System using Sound

Author

Listed:
  • A. Praveena
  • Gorla Sneha Tejaswini
  • Hari Krishnan M
  • Battina Sudeeshna
  • Challa Vineel Krishna

Abstract

The project aims to develop an innovative women's safety system integrating voice analysis, IoT, and machine learning to efficiently detect emergency situations. A comprehensive solution is proposed, utilizing PySound for speech-to-text conversion and machine learning algorithms to identify emergency words. Integration with IoT devices like Node MCU facilitates seamless data transfer, while location tracking using GPS or Wi-Fi ensures accurate emergency response. Live streaming capabilities during emergencies, coupled with stringent security measures, enhance user safety. Realtime alerts to predefined contacts upon detecting harmful words further bolster the system's effectiveness, emphasizing swift action in critical situations. Additionally, vital parameters such as heart rate and temperature are monitored using sensors like max30100 and DHT to provide accurate assessment alongside voice analysis.

Suggested Citation

  • A. Praveena & Gorla Sneha Tejaswini & Hari Krishnan M & Battina Sudeeshna & Challa Vineel Krishna, 2025. "Safety Detection System using Sound," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(2), pages 3022-3026, March.
    • Handle: RePEc:jbh:ijsrcs:v11:y2025:i2:id:1348
    DOI: 10.32628/CSEIT25112766
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT25112766
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