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Smart city article details

Title Spontaneous Traffic Management System For Counting Vehicle Using Iot And Image Processing Techniques
ID_Doc 52787
Authors Sreelatha R.; Mahalakshmi B.S.; Supriya G.V.; Sushmitha R.; Chiranjeevi Nayak B.
Year 2024
Published EAI/Springer Innovations in Communication and Computing
DOI http://dx.doi.org/10.1007/978-3-031-54696-9_1
Abstract Road traffic management is an essential component of smart city administration. To effectively mitigate traffic congestion, one might use a proactive approach by accurately determining the volume of cars traversing heavily trafficked crossroads in advance. The technology employs image processing methods to forecast vehicle numbers prior to reaching the designated traffic junction. Moreover, the collected data is sent over the Internet to a centralized control center located anywhere inside the city. The device seamlessly incorporates itself into the current traffic control systems, using strategically positioned cameras to capture images of vehicles. Subsequently, these photographs are subjected to image processing methods in order to accurately quantify the number of vehicles. The gathered data is sent to a central administration system for immediate monitoring and analysis of traffic. In addition, the system improves the timing of traffic signals and offers drivers up-to-date information, leading to significant decrease in congestion, improved traffic flow, and valuable traffic management data. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Author Keywords Computer vision; Image processing; IoT; Traffic control; Vehicle count


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