Accident Detection and Alert System using Deep Learning
Real-Time Accident Detection System using Machine Learning model will detect and identifying the vehicle accident and sent alert text message to person or nearby police station or warning with beep sound. Python programming language is used to develop this project and Tkinter is used for developing Graphical User Interface. This ML model is trained on large dataset of images and videos. It works through laptop front camera to identifying the real time road accidents.
In today’s fast-paced world, road safety has become a paramount concern. Road accidents result in numerous fatalities and injuries, causing immense human suffering and economic losses. Hence, the development of advanced detection systems is crucial to the consequences of unfortunate events. This thesis explores the implementation and evaluation of an Accident Detection System utilizing YOLOv8 (You Only Look Once version 8) and Convolutional Neural Networks (CNN) algorithms.
Vehicle Accident Detection System using Image Processing
Software Requirements :-
- Coding Language : Python
- Implementation: Software Framework.
- Operating system : Windows 10 / 11.
- Graphical User Interface : Tkinter
Hardware Requirement:-
- Input Devices : Keyboard, Mouse.
- System : Pentium i3 Processor.
- Hard Disk : 500 GB.
- RAM : 4 GB.
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