Intelligent Community Management Platform Design And Research

Intelligent community management refers to a community management technique which combined the technology such as Internet, Internet of things, big data,cloud storage. Its aim is to create a modern and intelligent community equipped with modern management and high-end technology to improve the quality of people’s daily life and provide people with a cozy and comfortable habitat. But unfortunately,it will produce a considerable amount of data with a great many of attributes such as vehicles data, urban trips survey data and statistics of property management companies. Thus, to process those data is very difficult. Worst still, recently property management companies do not make the best use of those data but just do some simple statistics. Hence, if we can manage and analyze those data efficiently by using related techniques, we can acquire the useful data that could be used to help community management. The main work of this paper is based on the above background.This paper designed and developed an intelligent community management platform based on the analysis of the requirements of current community management.The main work is divided into two parts. The first part is the implementation of the basic function module. Firstly, this paper designed the complete skeleton of the platform. Then, this paper released the basic models by utilizing JAVA and the SSH framework. The basic modules consisted of six parts:log-in module, users’ authority assignment module, property cost management module, management of vehicles and garages module, management of complaints and suggestions module, system management module. As there are many private and personal information in the property management, so this paper used MD5 and RSA to ensure the security of data.In the management of vehicles and garages module, this paper utilized the License Plate Recognition(TLPR) technique to develop this module and then adopted the Webservice techniques to complete the communication between databases and TLPR.This paper used My SQL to store data. In order to ensure the smooth operation ofdatabases, this paper configured a database connection pool and took strategies to prevent SQL injection attacks.The second part is to develop the intelligent modules of the community management platform. Firstly, this paper did study and research regarding to CURE clustering algorithm. Then this paper improved it by taking the advantage of F-distribution adaptive clustering to avoid the need of specific initial parameters. The method proposed in this paper could overcome the shortcomings of CURE successfully. Then, this paper developed intelligent modules based on the users’ travel time and satisfaction by analyzing and processing the actual data coming from the community management. Both of the two modules utilized the improved CURE and fuzzy c-means clustering algorithms, which were able to extract the hidden information to facilitate and improve the quality of the community management.