International Research Journal of Engineering and Technology (IRJET) Volume: 09 Issue: 05 | May 2022
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e-ISSN: 2395-0056 p-ISSN: 2395-0072
Intelligent Accident Detection, Prevention and Reporting System Prof.S.P.Mankar1, Varda Dodke2, Samruddhi Salvi3 , Shubhangi Sanap4,Tanaya Satpute5 1
Prof. S.P.Mankar, Dept. of Information Technology ,JSCOE, Pune, Maharashtra, India 2
3 4
Varda Dodke, Dept. of Information Technology, JSCOE, Pune, Maharashtra, India
Samruddhi Salvi, Dept. of Information Technology, JSCOE, Pune, Maharashtra, India
Shubhangi Sanap, Dept. of Information Technology, JSCOE, Pune, Maharashtra, India 5
Tanaya Satpute, Dept. of Information Technology, JSCOE, Pune, Maharashtra, India
---------------------------------------------------------------------***--------------------------------------------------------------------Abstract –Accidents have been a crucial cause of deaths in India. Higher than 80% of accident-related deaths occur not due to the accident itself but the lack of timely help reaching the accident victims. The aim is to build a system to prevent ,detect and report an accident to emergency responders. To prevent the accident we have used ultrasonic sensor to measure the distance of a vehicle by using ultrasonic sound waves. An ultrasonic sensor has a transducer to send and receive ultrasonic pulses that relay back information about the distance between the vehicles. We detect an accident based on video from a CCTV camera installed on road. Our concept is to take each frame/part of a video and run it through a deep learning convolution neural network model which has been trained to classify frames of a video into normal and abnormal. CNN model has proved to be afast and accurate approach to classify images. CNN model has given accuracy's of more than 95%. The research being carried out on images and not videos. In this we detect the Accident detection or not. If the Accident is detected then system sends the SMS to police station and health care. Keywords – Accident, Accident Prevention, Accident detection, Convolution Neural Network, CCTV, frame, Ultrasonic Sensor.
Accident detection is one of the key problems in computer vision that has been studied for more than 15 years. It is important because of the sheer number of applications which can benefit from Accident detection. For example, Accident detection can be used in applications inclusive of video surveillance, animal tracking and behavior understanding, sign language detection, advanced human-computer interaction. Affordable depth sensors have limitations like limited to indoor use, and their low resolution and noise depth information make it difficult to estimate human poses from
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Impact Factor value: 7.529
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PROPOSED SYSTEM
In our proposed system, we develop a system to prevent, detect and report an accident to the nearby emergency responders. The goal of our system is to provide quick response to the victim whenever the accident takes place by using deep learningalgorithms.
1. INTRODUCTION
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depth images. Thus, weplan to use neural networks algorithms to overcome these problems. Accident detection from video surveillance is an active research area of image processing and computer vision. By the visual surveillance, human activities can be monitored insensitive and public areas such as bus stations, railway stations, airports, banks, shopping malls, school and colleges, parking lots, roads, etc. to prevent terrorism, theft, accidents and illegal parking, vandalism, fighting, chain snatching, crime and other Accident detection. It is very challenging to keep an eye on public places constantly, hence an intelligent video surveillance is required that can monitor the human activities in real time and categorize them as normal and abnormal activities; and can initiate an alert. Mostly, the research being carried out are on images and not videos. Also, none of the papers published triesto use CNNs to detect Accident. In this project we detect the Accident detection detected or not. if the Accident detection detected then system send the SMS to police station and medical health care.
We detect the accident with the use of a Convolutional Neural network model where the algorithm will train the system and then classify the images into normal and abnormal form where the normal form means no accident occurred and a normal formmeans the accident has taken place. Our device will be able to locate the accident location and send the alert message through the form of SMS(Short Message Service) to the nearby police stations and medical health care services to provide quick help tothe victim .
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