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Authors
Akula AnandaLakshmi,Hari Krishna Kangala,Abdul Razaq,Jeenepally Nandini,John Blessy Supriya
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Keywords
Smart traffic systems; accident detection; deep learning; YOLO; computer vision; intelligent transportation systems (ITS); emergency response automation; real-time surveillance; metadata extraction; cloud integration; Flask-based deployment; multi-camera monitoring; decision tagging; analytics dashboard; road safety.
Abstract
Road traffic accidents are a problem that causes deaths and bad injuries all over the world. When Road traffic accidents happen it is really important that people get help away. The old way of watching CCTV cameras is not very good because it mostly relies on people watching them and this can be very slow. The Smart Traffic Accident Detection and Alert System is a way to do things. It uses computer programs to look at CCTV pictures and find Road traffic accidents. This system uses a Convolutional Neural Network to figure out if a Road traffic accident happened. It also uses a YOLO-based object detection model to find the car and draw a box around it. When the Smart Traffic Accident Detection and Alert System thinks a Road traffic accident happened and it is pretty sure it writes down what happened and tells a person to check. The person has 30 seconds to look at it through a web page. If the person does not do anything the Smart Traffic Accident Detection and Alert System will send out emergency messages again and again. The Smart Traffic Accident Detection and Alert System is a way to help people who get hurt in Road traffic accidents. It can find Road traffic accidents quickly. It can get help to people who need it. The Smart Traffic Accident Detection and Alert System is an improvement, over the way of watching CCTV cameras.
IJCRT's Publication Details
Unique Identification Number - IJCRT2604636
Paper ID - 305991
Author type - Indian Author
Page Number(s) - f442-f443
Pubished in - Volume 14 | Issue 4 | April 2026
DOI (Digital Object Identifier) -
No Of Downloads - 31
Author Country - India, 522302, Mangalagiri, Mangalagiri, 522302, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
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Akula AnandaLakshmi,Hari Krishna Kangala,Abdul Razaq,Jeenepally Nandini,John Blessy Supriya, "AI - Powered CCTV Accident Alert System", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.14, Issue 4, pp.f442-f443, April 2026, Available at :http://www.ijcrt.org/papers/IJCRT2604636.pdf
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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