Smart Safety System for Physically Disabled Individuals Using IoT

Abstract

This paper presents a Smart Safety System for Physically Disabled Individuals designed using Internet of Things (IoT) technology to enhance personal safety and independence. Physically disabled individuals often face challenges such as accidental falls, unexpected obstacles, and delayed emergency assistance. To address these issues, the proposed system integrates multiple sensors including MPU6050 for fall detection, ultrasonic sensor for obstacle detection, and MQ-3 for alcohol detection. An Arduino Uno is used as the central controller to continuously monitor sensor data and identify abnormal conditions using predefined thresholds. In case of an emergency, such as a fall or unsafe environment, the system automatically sends alerts to a predefined guardian through a GSM module. A GPS module is also incorporated to provide real-time location information, enabling quick and effective response. The system operates automatically without requiring manual intervention, making it suitable for users with limited mobility. The proposed solution is cost-effective, reliable, and easy to implement. It significantly improves response time during emergencies and enhances the overall safety and confidence of physically disabled individuals.

Introduction

The proposed work presents an IoT-based Smart Safety System for physically disabled individuals to improve personal safety through continuous monitoring and real-time emergency alerts. It addresses risks such as falls, collisions, and delayed assistance by replacing traditional manual supervision with an automated sensor-driven solution.

The system integrates multiple components including an Arduino Uno as the central controller, along with an MPU6050 for fall detection, an ultrasonic sensor for obstacle detection, an MQ-3 sensor for alcohol detection, a GSM module for sending alerts, and a GPS module for location tracking. When unsafe conditions are detected, the system immediately triggers a buzzer, sends SMS alerts to guardians, and shares the user’s location.

Existing research shows that many safety systems are limited to single functions (like only fall detection or tracking), often lack real-time alerts, or are too expensive. The proposed system improves on these limitations by combining multiple safety features into one low-cost, real-time wearable solution.

Implementation involves continuous sensor monitoring, threshold-based decision-making in the microcontroller, and automatic emergency response without user intervention. Testing results show reliable detection of falls, obstacles, and alcohol presence, with fast and accurate alert delivery through GSM and GPS. Overall, the system demonstrates good performance in accuracy, response time, and usability, making it suitable for enhancing independence and safety of disabled users.

Conclusion

The proposed Smart Safety System for Physically Disabled Individuals presents an effective and reliable solution for enhancing personal safety and independence. The system integrates multiple sensors such as MPU6050 for fall detection, ultrasonic sensor for obstacle detection, and MQ-3 for alcohol detection, along with GSM and GPS modules for communication and location tracking. This combination enables the system to continuously monitor the user’s condition and respond immediately in case of emergencies. The implementation and testing results demonstrate that the system is capable of accurately detecting unsafe situations and sending timely alerts to predefined contacts. The real-time monitoring and automated response reduce the risk associated with accidents and improve the chances of quick assistance. The system is cost-effective, easy to implement, and suitable for real-world applications. It provides both preventive and emergency support, making it a valuable assistive solution for physically disabled individuals. Overall, the proposed system successfully meets its objective of improving safety, reducing response time, and enhancing user confidence in daily activities.

References

[1] J. Smith, “Internet of Things Applications in Smart Systems,” IEEE Journal of Emerging Technologies, vol. 10, no. 2, pp. 45–52, 2022. [2] A. Sharma and R. Kumar, “Smart Monitoring Systems Using IoT,” Springer International Journal of Computer Science, vol. 15, no. 3, pp. 120–128, 2023. [3] S. Patel, “Assistive Wearable Devices for Safety Applications,” Elsevier Journal of Assistive Technologies, vol. 8, no. 1, pp. 60–68, 2024. [4] M. Kumar et al., “Fall Detection System Using MPU6050 Sensor,” International Journal of Engineering Research and Technology (IJERT), vol. 11, no. 5, pp. 300–305, 2022. [5] R. Singh and P. Verma, “Obstacle Detection Using Ultrasonic Sensors,” International Journal of Electronics and Communication Engineering, vol. 9, no. 4, pp. 210–215, 2021.

Copyright

Copyright © 2026 Nikhil Gaikwad, Poorva Gawand, Vedant Jadhav, Shravani Nagale, Prof. Nilesh Patil. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.