Intelligent smart city parking facility layout optimization based on intelligent IoT analysis

Research based on the utilization of big data has led to new opportunities and developments in contemporary urban planning and smart city construction. This research is based on open big data of networks, such as the website Where to Go and public comments, spatial syntax theory and technical methods using the current layout of urban parking facilities in Shinan District as a case study of the lack of parking facilities and their unreasonable layout. Based on a quantitative analysis of the distribution of the traffic network and parking facilities on the urban scale and the block scale of the Shinan District of Qingdao, we found that the thermal density of Baidu is closely related to the spatial syntactic parameters of the urban area on the large scale and local scale. A field investigation was performed to analyze the traffic network of the Southern District of Qingdao and propose comprehensive optimization strategies to provide technical support for the construction of intelligent shared parking facilities in cities. This study solves a series of problems, such as unreasonable parking facility allocation around scenic spots in tourist cities, and can also be used as a reference for the optimization of parking facility layouts in similar cities.