Abstract
Traffic pattern analysis is an emerging field of study to understand the cardinal parameters to design the archetype of modern infrastructure projects. Understanding the rudimentary factors that affect traffic will also allow the government to deploy automated traffic signal systems. This research paper will explain a unique approach to get the traffic pattern analysis information using the combination of computer vision and wireless sensor network. To deploy the solution, artificial neural network approach is used to detect the vehicles and pedestrians. Based on training the dataset of features, it can be ported to embedded systems to detect the vehicles. Later, data is being sent to cloud infrastructure using ZigBee protocols in Leach topology. It will give traffic synchronization to traffic signal systems.
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Desai, S., Trivedi, P. (2016). Traffic Signal Synchronization Using Computer Vision and Wireless Sensor Networks. In: Dash, S., Bhaskar, M., Panigrahi, B., Das, S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 394. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2656-7_68
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DOI: https://doi.org/10.1007/978-81-322-2656-7_68
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