Safety Detection System using Sound

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.

Authors

Institutions

Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2025-04-02
DOI
https://doi.org/10.32628/cseit25112766
Primary Topic
Fire Detection and Safety Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Safety Detection System using Sound

H. M., Chinta Venkata Murali Krishna, G Tejaswini, A Praveena et al.
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Fire Detection and Safety Systems
article

Safety Detection System using Sound

H. M., Chinta Venkata Murali Krishna, G Tejaswini, A Praveena, Battina Sudeeshna
article en

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.

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 11(2)
Artificial Intelligence in Medicine (Canada) (CA), Great Lakes Institute of Management (IN)
Openalex Percentile: Top 93%
Fire Detection and Safety Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Safety Detection System using Sound — H. M., Chinta Venkata Murali Krishna, et al. · International Journal of Scientific Research in Computer Science Engineering and Information Technology (2025) | TGRS Research Map | TGRS