1Assistant Professor, Department of Information Technology, Manakula Vinayagar Institute of Technology, Puducherry, India. Email: sankarancse@mvit.edu.in
2U.G Scholar, Department of Information Technology, Manakula Vinayagar Institute of Technology, Puducherry, India. Email: abinayacannan2020@gmail.com, dharshinipalani202004@gmail.com, sasipriya5454@gmail.com, vaisharanvaish@gmail.com
Title: Women Safety and Accident Detection for Mentally Challenged People
This project presents an innovative IoT-based safety and health monitoring system specifically designed to enhance the well-being of women and individuals with cognitive disabilities. The system integrates multiple smart technologies including GPS tracking, GSM communication, fall detection sensors (MPU6050), ultrasonic sensors for accident detection, and wearable devices to offer a robust safety network. The core objective is to provide real-time monitoring, emergency alerting, and continuous tracking to ensure user safety and independence. Upon detecting abnormal activities such as a fall, collision, or if the panic button is pressed, the system immediately triggers an SMS alert through the GSM module, along with the user's real-time location gathered via the GPS module. The geofencing feature adds another layer of protection by notifying caregivers if the user exits a predefined safe zone. This solution reduces response time during emergencies and ensures that assistance is available promptly.
By leveraging compact and cost-effective IoT hardware components like the ESP32 microcontroller, the proposed system is lightweight, portable, and suitable for daily use. It not only enhances the confidence and autonomy of vulnerable users but also provides peace of mind to caregivers and healthcare providers through constant monitoring. The project underscores the transformative potential of IoT in addressing critical social challenges, particularly in supporting mental health and personal safety. It promotes a multidisciplinary approach by combining principles of embedded systems, healthcare, and wireless communication technologies to create a scalable and efficient solution that can be deployed in real-world environments.
Keywords: NA
How to cite this article: Sankaran A, Abinaya C, Dharshini P, Sasipriya R, Vaishnavi V. Women Safety and Accident Detection for Mentally Challenged People. Int J Drug Deliv Technol. 2026;16(16s): 451-457. DOI: 10.25258/ijddt.16.16s.47
Source of support: Nil.
Conflict of interest: None