Issue |
E3S Web Conf.
Volume 391, 2023
4th International Conference on Design and Manufacturing Aspects for Sustainable Energy (ICMED-ICMPC 2023)
|
|
---|---|---|
Article Number | 01145 | |
Number of page(s) | 10 | |
DOI | https://doi.org/10.1051/e3sconf/202339101145 | |
Published online | 05 June 2023 |
Motorcycle Crash Detection and Alert System using IoT
1 Department of AIMLE, GRIET, Hyderabad, Telangana, India
2 UG Student, Department of CSBS, GRIET, Hyderabad, Telangana, India
* Corresponding author: ramkumar1695@grietcollege.com
Motorcycle travel is considered the most dangerous mode of transport in the world. Reports suggest that the fatality rate of motorcycles is 212.7 deaths for every million miles travelled on motorcycles. Unlike other forms of travel like cars, buses, etc, motorcycles expose the rider to their surroundings. In cars, the frame protects the driver from hitting the road or falling out of the car. But motorcycles do not have such a possibility. Therefore, the best way to minimize fatalities in accidents is to have an alert system that can alert the emergency services when it detects an imminent crash. This is where the motorcycle crash detection and alert system comes into the picture. It uses the MPU6050 Multi-axes accelerometer to detect when the motorcycle falls to its side. It sends the impact parameters to Firebase cloud and if the values meet the crash criteria, it sends an alert to the emergency contacts as well as to the emergency response services, who can then act according to it.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.