LAUSR

Abstract By using various Internet of Things technologies and communication technologies, smart cities can respond quickly and intelligently to various service requests of cities, thus realizing the intelligent operation and management of cities, strengthening the management of urban facilities and improving the quality of urban services. To improve the operational efficiency of smart car network systems and smart city management systems. In this paper, the authors analyse the intelligent vehicle network system and smart city management based on genetic algorithms and image perception. By using distributed and parallel computing, massive urban data can be quickly stored, processed and analyzed, useful information can be extracted, which can help smart cities make effective decisions and improve the efficiency of infrastructure and resources use. The simulation results show that the proposed coordination strategy can achieve the minimum energy consumption scheduling, thus maximizing the benefits of the data center, thus effectively improving the urban road traffic capacity and alleviating urban traffic congestion.