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Stream/Area:
-
Subject:
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Paper ID:
IJSREM65427
Volume:
10 |
6 |
Jun 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Electrical Engineering
Rajiv Gandhi Collage of Engineering
Department of Electrical Engineering
Rajiv Gandhi Collage of Engineering
Department of Electrical Engineering
Rajiv Gandhi Collage of Engineering
Department of Electrical Engineering
Rajiv Gandhi Collage of Engineering
Department of Electrical Engineering
Rajiv Gandhi Collage of Engineering
Road accidents involving motorcycle riders remain one of the leading causes of injuries and fatalities worldwide. Factors such as drunk driving, delayed emergency response, and the inability to detect accidents in real time significantly increase the risk to riders. To address these challenges, this paper presents an IoT-Based Smart Helmet with Accident Detection and Alert System designed to improve rider safety through continuous monitoring, intelligent decision-making, and automated emergency notification. The proposed system is developed using the ESP32 microcontroller, which provides high processing capability and integrated Wi-Fi communication for seamless real-time data transmission. The helmet incorporates an MPU6050 accelerometer and gyroscope sensor to monitor sudden impacts, abnormal tilting, and rapid changes in motion that may indicate an accident. Additionally, an MQ3 alcohol sensor is used to detect the presence of alcohol and identify unsafe riding conditions before a journey begins. To enhance reliability and minimize false alarms, an automatic calibration process is performed during system startup. This calibration establishes baseline values for both motion and alcohol measurements, allowing the system to adapt to environmental conditions and sensor variations. During operation, sensor data is continuously analyzed and compared with predefined safety thresholds. When abnormal motion patterns, severe impacts, or alcohol levels exceeding permissible limits are detected, the ESP32 immediately activates a buzzer and OLED display to provide local alerts to the rider. Simultaneously, critical information is transmitted to a Firebase cloud database, enabling real-time monitoring and remote notification through connected applications.
KEYWORDS
The proposed IoT-Based Smart Helmet with Accident Detection and Alert System provides an effective solution for enhancing motorcycle rider safety. By integrating ESP32, MQ3, and MPU6050 sensors, the system continuously monitors rider behaviour and environmental conditions. The automatic calibration process improves detection accuracy while minimizing false alarms. The developed system successfully identifies alcohol consumption and accident events in real time and immediately generates warnings through buzzer and OLED notifications. Firebase-based communication enables remote monitoring and emergency response. The system is cost-effective, scalable, and suitable for deployment in intelligent transportation safety applications.
[1] P. Asha, A. C. V., A. S., L. P. Suresh, D. Usha Nandini and M. P. Selvan, “Ensuring Safety Drive Through a Smart Helmet Design Using IoT,” in 2024 International Conference on Smart Systems and Communication Technologies, IEEE, 2024. [2] M. S. Karthik, R. Vignesh, S. Harish and P. Naveen, “Smart Helmet for Riders to Avoid Accidents Using IoT,” in IEEE Conference Proceedings, 2024. [3] S. Ramesh, K. Pradeep, A. Kumar and R. Rajesh, “Enhancing Human Safety Through IoT-Integrated Smart Helmet Technology,” in IEEE Conference Proceedings, 2024. [4] A. Sharma, P. Gupta, R. Singh and M. Verma, “Smart Helmet with IoT Integration: Enhancing Rider Safety with Real-Time Hazard Alerts,” in IEEE Conference Proceedings, 2024. [5] R. Kumar, S. Patil, A. Deshmukh and V. Kulkarni, “IoT Based Smart Helmet for Road Accident Detection,” International Journal of Research Publication and Reviews, vol. 5, no. 4, pp. 1–6, 2024. [6] N. Prakash, M. Arun, K. Karthikeyan and P. Dinesh, “IoT Based Smart Headgear for Motorbike,” in IEEE Conference Proceedings, 2024. [7] V. Mehta, R. Sharma, A. Patel and S. Joshi, “An IoT-Based Smart Helmet for Riding Security and Emergency Notification,” in IEEE Conference Proceedings, 2024. [8] P. Raj, K. Mishra, S. Yadav and M. Singh, “Smart Helmet with Automatic Braking Using IoT,” in IEEE Conference Proceedings, 2024. [9] D. Anitha Maheswari, K. Surendar Reddy, M. Dimple Laya and P. Srinivas Kumar, “IoT-Based Smart Helmet for Accident Detection and Rider Safety,” IJNRD, vol. 10, no. 4, pp. 1–7, 2025. [10] N. J. Bhamare, H. N. Sonawane, H. S. Pedhekar and S. S. Malunjkar, “Smart Helmet for Electrical Line Workers with Accident Detection and Live Location,” IJTRD, vol. 12, no. 2, pp. 15–20, 2025.
Publication Date
6/24/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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