Accident Detection Using Raspberry Pi In Python

March 2023
Vol-9, Issue-2
Paper ID: 19492
ISSN: 2395-4396
Downloads: 0

Abstract & Details

Research Area
Information Technology
Keywords
Accident alert CO sensor GSM GPS LCD Limit switch Raspberry pi Vibration Sensor
Abstract
One of the primary causes of fatalities is traffic accidents. The amount of time between the accident and the arrival of an emergency medical institution at the scene is a key element in the post-accident survival rates. By shortening the distance between the accident and the arrival of a medical institution, death rates are reduced. In order to save more lives. Using Accident Detection Using Raspberry Pi, which alerts if the accident happened and promptly notifies the emergency personnel, is one way to end that wait. The system is detailed, with its primary use being to identify accidents using vibration sensors and send alarm messages to the appropriate locations. The location of the collision, the amount of alcohol consumed, the seat belt use, the speed, and the number of passengers are all included in the alert message. The latitude and longitude data are first stored in this system by GPS, which continually receives input from the satellite[1]. We must transmit the message to a GSM device so that it receives it in order to track the car.. Also, it is triggered by the raspberry pi controller's vibration sensor picking up an accident. When the GSM is turned on, it gets the most recent positional data (latitude and longitude) and sends a message to the program's specified emergency server.

Author Information

# Name Institute / Affiliation
1 Neha Atul Kanade Anantrao Pawar College Of Engineering & Research. Pune
2 Aditya Ankush Gangane Anantrao Pawar College Of Engineering & Research. Pune
3 Kailash Shrirang Ghumare Anantrao Pawar College Of Engineering & Research. Pune
4 Neha Ganesh Kirad Anantrao Pawar College Of Engineering & Research. Pune
5 Prof. R. S. Lavhe. Anantrao Pawar College Of Engineering & Research. Pune

How to Cite

Use the following formats to cite this article in your research.

APA Style
Kanade, Neha Atul, Gangane, Aditya Ankush, Ghumare, Kailash Shrirang, Kirad, Neha Ganesh, & Lavhe., Prof. R. S. (2023). Accident Detection Using Raspberry Pi In Python. International Journal of Advance Research and Innovative Ideas In Education, 9(2), 949-952.
MLA Style
Kanade, Neha Atul, et al. "Accident Detection Using Raspberry Pi In Python." International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 2, 2023, pp. 949-952.
IEEE Style
Neha Atul Kanade, Aditya Ankush Gangane, Kailash Shrirang Ghumare, Neha Ganesh Kirad, and Prof. R. S. Lavhe., "Accident Detection Using Raspberry Pi In Python," International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 2, pp. 949-952, 2023.
Vancouver Style
Kanade Neha Atul, Gangane Aditya Ankush, Ghumare Kailash Shrirang, Kirad Neha Ganesh, Lavhe. Prof. R. S.. Accident Detection Using Raspberry Pi In Python. International Journal of Advance Research and Innovative Ideas In Education. 2023;9(2):949-952.
Harvard Style
Kanade, Neha Atul, Gangane, Aditya Ankush, Ghumare, Kailash Shrirang, Kirad, Neha Ganesh, & Lavhe., Prof. R. S. (2023) 'Accident Detection Using Raspberry Pi In Python', International Journal of Advance Research and Innovative Ideas In Education, 9(2), pp. 949-952.
Chicago Style
Kanade, Neha Atul, et al. "Accident Detection Using Raspberry Pi In Python." International Journal of Advance Research and Innovative Ideas In Education 9, no. 2 (2023): 949-952.
Turabian Style
Kanade, Neha Atul, et al. "Accident Detection Using Raspberry Pi In Python." International Journal of Advance Research and Innovative Ideas In Education 9, no. 2 (2023): 949-952.

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