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License Detection and Accident Prevention System

by P.D.R. Dewmin, P.S.H Yapa, S.D. Lokuge
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 37
Year of Publication: 2022
Authors: P.D.R. Dewmin, P.S.H Yapa, S.D. Lokuge
10.5120/ijca2022922457

P.D.R. Dewmin, P.S.H Yapa, S.D. Lokuge . License Detection and Accident Prevention System. International Journal of Computer Applications. 184, 37 ( Nov 2022), 38-44. DOI=10.5120/ijca2022922457

@article{ 10.5120/ijca2022922457,
author = { P.D.R. Dewmin, P.S.H Yapa, S.D. Lokuge },
title = { License Detection and Accident Prevention System },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2022 },
volume = { 184 },
number = { 37 },
month = { Nov },
year = { 2022 },
issn = { 0975-8887 },
pages = { 38-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number37/32559-2022922457/ },
doi = { 10.5120/ijca2022922457 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:23:26.097791+05:30
%A P.D.R. Dewmin
%A P.S.H Yapa
%A S.D. Lokuge
%T License Detection and Accident Prevention System
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 37
%P 38-44
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

From 2013 to 2019, more than 30,000 accidents happened in Sri Lanka, according to the department of census and statistics. In this time frame, more than 2000 people die [1]. Road accidents are ranked 10th out of the top 10 causes of death in Sri Lanka [2]. The main contributing factors to these accidents are drunk driving, weariness, drowsiness, distracted driving, and driving without a valid license [3]. Drivers without a legal license are to blame for 20% of collisions [4]. There is currently no automatic mechanism for IoT-built driver's license verification. The society also lacks a means to detect drunk driving, distracted driving, and sleepy driving.A smart license detection and accident prevention system was suggested after data analysis to use RFID to identify and validate driver's licenses. The suggested system also enables sub-systems that use a Raspberry Pi camera module and computer vision software called TensorFlow Lite to monitor a driver's alertness, weariness, alcohol level, and whether or not they are distracted. Using a pressure sensor, a sub-system that has been initiated determines the intensity of the brake pedal's engagement. The technology evaluates the pressure and uses the brightness of the brake light to signal the intensity level appropriately.Airbag detection subsystems, which use GSM modules and SMS Gateway API, reduce the fatality rate of accidents by detecting the deployment of airbags and notifying the closest police station and hospital of the incident. While these subsystems decrease the likelihood of an accident occurring, they also reduce the likelihood of it occurring fatally. The suggested system will lower the number of accidents that happen all year long.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Vehicle Accident IoT GPS GSM Raspberry Pi Computer Vision TensorFlow Lite Pressure Sensor RFID Accident Prevention

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