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Development of a Smart Women Safety ID with Real-Time Gas Detection and Crime-Aware Emergency Alerts System
Abstract
In many parts of the world, women’s safety in public, educational, and professional settings is still a major concern. Conventional safety measures frequently depend on wearable technology or smartphone apps, which aren’t always reliable in an emergency or covert enough to keep potential criminals from spotting them. This study proposes a clever and affordable women’s safety ID card that offers both proactive and re active protection to overcome these drawbacks. This cutting-edge gadget incorporates essential technologies like a Bluetooth module (HC-05) for short-range device pairing, a SIM900A GSM module for emergency communication, a GPS module for location tracking, and an MQ2 gas sensor for hazardous gas detection. To ensure smooth operation at companies, educational institutions, and schools, the system is controlled by an Arduino Uno (ATmega328P) and housed in a standard ID card form factor. To detect the presence of dangerous compounds, including LPG, alcohol, and an aesthetic gases, labelled gas sensor data was used to train a supervised machine learning model, more precisely, a Random Forest Classifier. The model produced dependable real-time predictions with a high classification accuracy of 98.75% and strong precision, recall, and F1 scores. Furthermore, the system classifies areas as red zones by using historical crime data, such as location, crime type, and coordinates. The Haversine distance method is used to assess the user’s real-time GPS data and calculate how close they are to these high-risk areas. An automated alert is set off if the user goes inside a predetermined danger radius of four kilo metres. A manual SOS button is another feature of the safety system that allows users to send emergency alerts via SMS with their position and threat kind right away, even when there is no internet connectivity. Only authorized users, like guardians or institution leaders, can access critical data, track user movement, and receive alerts thanks to the secure dashboard and user authentication offered by the supporting mobile and online application. The interface, which was constructed with Gradio and Folium, provides real-time viewing of red zone boundaries, position, and gas detection status. This integrated system is an effective instrument to increase women’s safety because it not only guarantees situational awareness but also makes quick emergency reaction possible. Because of its scalable architecture, open-source. technologies, and low-cost hardware, it can be widely implemented in a variety of industries. The Women Safety ID Card is a step forward in utilizing artificial intelligence and embedded systems to create safer environments and give women the freedom, security, and self-assurance they need to go about their everyday lives.
Keywords
Women safety and Smart ID Card
Machine Learning
gas sensor
gps tracking
emergency alert
Cite This Article
(2025).
Development of a Smart Women Safety ID with Real-Time Gas Detection and Crime-Aware Emergency Alerts System.
Journal of Recent Innovations in Computer Science and Technology
, 2(4)
.
https://doi.org/10.70454/jricst.2025.20402
“Development of a Smart Women Safety ID with Real-Time Gas Detection and Crime-Aware Emergency Alerts System.”
Journal of Recent Innovations in Computer Science and Technology,
vol. 2,
no. 4,
2025
.
https://doi.org/10.70454/jricst.2025.20402
“Development of a Smart Women Safety ID with Real-Time Gas Detection and Crime-Aware Emergency Alerts System.”
Journal of Recent Innovations in Computer Science and Technology
2
, no. 4
(2025)
.
https://doi.org/10.70454/jricst.2025.20402
(2025)
‘Development of a Smart Women Safety ID with Real-Time Gas Detection and Crime-Aware Emergency Alerts System’,
Journal of Recent Innovations in Computer Science and Technology
, 2
(4)
.
Available at:
https://doi.org/10.70454/jricst.2025.20402
Development of a Smart Women Safety ID with Real-Time Gas Detection and Crime-Aware Emergency Alerts System.
Journal of Recent Innovations in Computer Science and Technology.
2025
;2
(4)
.
doi:
10.70454/jricst.2025.20402