Abstract

Abstract The ongoing development for modern cities and quality of life, coupled with computing resources, has led to increased smart city services availability. Smart cities are committed to providing residents with a better experience while reducing resource demand and pollution. As such, considered an essential factor for sustainable growth. Of the many problems that have emerged, one of the world's most critical urban issues has been traffic, which has resulted in a massive waste of time and energy and increased pollution. One of the first steps for optimized traffic in the city is to get accurate information to understand the city's traffic flow in real time. It can be achieved by applying automated video analysis, distributed throughout the city, and through a camera group's video stream. The effect of the substance on the surface, discoloration, loss of material, and air pollution can be related to contamination of structural defects and views. Whatever discoloration and air pollution defects in the structure buildings do not matter, have many coasts involved. Both peripheral and central do the processing of the image sequence. Believe that this is due to usability. Too many of the advantages of focusing on maintenance and cost in a large city are very promising strategies for effective traffic management. However, since the computational cost is a vast, high-performance computing method that is excellent in energy efficiency, it has been required. The high-performance algorithm to effectively implement real-time traffic flow information at low energy and power costs can process camera image sequence traffic.

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