Header menu link for other important links
Traffic Management System Using AI and IoT
Published in Springer Science and Business Media Deutschland GmbH
Volume: 838
Pages: 285 - 296
Traffic congestion has become a major issue nowadays. Not only in metro cities even in small cities this traffic congestion is a big problem. Therefore, we have required an intelligent traffic control system that can decrease traffic. Our current traffic control system is not flexible and adaptable, and it is time-based and is unaffected by heavy traffic. Because of its static nature, it is unreliable, unpredictable, and noisy. The proposed system is the approach for traffic control. In the proposed system the image processing and IR sensors are used. IR sensors are installed at the roadside from where they detect vehicles and send results to Arduino UNO. On the other side, image processing is used to count vehicles by using camera surveillance and sends the result to the microcontroller through a serial port. Arduino UNO then analysis both the results and update green path time according to the traffic density on the road. Using technologies separately may have its disadvantages which can be overcome by considering a combination of both results for a better result. This method increases the accuracy and productivity of the system. Apart from this, the project gives prioritization to the emergency vehicles like fire trucks, ambulances. Also, this project saves basic information about vehicles, i.e. speed, vehicle colour, type, etc. This information can be used for further analysis, and as a result, it can forecast traffic congestion and road condition at various times. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About the journal
JournalLecture Notes in Electrical Engineering
PublisherSpringer Science and Business Media Deutschland GmbH
Open AccessNo