Open AccessTraffic Analysis Using Artificial Neural Network
Author(s) -
B Mounica,
B. Nithya,
N Rakshitha,
M. Sirisha
Publication year - 2021
Publication title -
international journal of scientific research in science and technology
Language(s) - English
Resource type - Journals
eISSN - 2395-602X
pISSN - 2395-6011
DOI - 10.32628/cseit217494
Subject(s) - computer science , artificial neural network , image processing , traffic accident , process (computing) , artificial intelligence , image (mathematics) , floating car data , collision , deep learning , traffic generation model , computer vision , real time computing , data mining , traffic congestion , transport engineering , engineering , computer security , operating system
The vehicle traffic on the road is increasing progressively and managing such traffic on the roads are not stable by conventional method. To remove this traffic issue, we develop a project using machine learning in which we train the testing model as well as trained model of extracted traffic features. Extracted information from image sequences of testing model can give us real information to create the database which is the captured images like accident, foggy places, collision of the vehicles, traffic signal, no traffic jam, treefall etc. Choose any traffic image from the testing model, process and analyze the traffic image and the traffic image which was taken from the testing model is compared with the trained model of traffic images to determine the cause of the traffic. Image processing will be done to determine the cause of the traffic. This project is utilizing image processing methods designed to analyze and determine the cause of the traffic with the accuracy of the traffic caused. Thus, by using this project we can avoid the traffic and the time being wasted.