Design of intelligent carpooling program based on big data analysis and multi-information perception

Carpool platform provides users with efficient service by making full use of the accurate mass data, which plays an important role in promoting carpool travel. The program builds a carpool web platform and mobile client. The backstage comprehensively uses GPS, GSM, WIFI and RFID technology of the internet of things to perceive the exact the user’s position information and realizes to monitor and manage user action trajectory in order to ensure the efficiency and security of carpool. The system is connected with the Amap interface to notify the real-time road condition and the information of the surrounding parking. Based on big data analysis, it also proposes data collaboration to eliminate the effect of data differences from mobile client and web platform, retrieve and filter valuable carpool information and recommend extra information based on carpool travel records. The scheme builds a real-time carpool module based on fixed time and route to meet the uncertain demands. The experimental results show that the driving time and distance of carpool could be saved by 25.7 and 12.4% respectively, which has preliminarily realized the intelligent, simple, flexible, efficient, convenient, economical and safe carpool with the aid of intelligent algorithm.