Analysis And Excavation Of Roadside Intelligent Parking Data

Along with the advancement of modern urban intelligent transportation,and the deepening development of big data analysis technology in the Internet era,the construction of urban road traffic intelligent supervision system has become an important prerequisite and foundation for its sustainable development.Based on the analysis of the use of urban roadside land resources,this paper takes the roadside parking ideas as the starting point.Through the investigation and comparison of the existing roadside parking patterns,a roadside charging model with video detection equipment is studied.The front end of the model realizes vehicle identification by TMS320DM8127 video detector;and it uses the Internet of Things and mobile Internet technologies to transmit and intelligently process parking information.The front-end detector automatically identifies parking information of berths and communicates with the platform through the network.The system automatically charges time according to the actual service configuration requirements.The analysis and mining of parking data is not only the key for enterprises to realize “value-added” and profitability of the data industry,but also the scientific basis for improving parking services.Therefore,this article will store all parking data in MySQL database,using big data analysis machine learning technology and statistical theory,using Python software and combining SPSS analysis and mining tools for parking on the four aspects of parking data analysis and mining.Based on the reconfiguration of user relationship management analysis FLCPA parameter model and K-Means fast clustering algorithm to achieve user value grouping;The analysis of user's activity is implemented by distinguishing parameter parameter and combining the statistical methods of classification,and finally the user pyramid model is extracted;According to the berth turnover rate,the month is used as the distinguishing indicator,and the turnover of each toll section is classified and summarized,so as to reflect theservice capacity of the parking lot,which can effectively predict the traffic flow situation;Based on the Apriori association algorithm,the relationship between parking lot and vehicle is explored.In order to realize the multidimensional cross analysis of parking data.The analysis of parking data is not only beneficial to the tracking and feedback of on-street parking business,but also the planning,development and promotion of this model provide a good reference and decision support.