Traffic jam avoiding prompting system based on collective intelligence network

Abstract

The invention provides a traffic jam avoiding prompting system based on a collective intelligence network. The traffic jam avoiding prompting system consists of a webpage traffic hot spot digging module, a microblog traffic hot spot digging module, a road condition rule predicting module, a jam hot spot verification and management module, a real-time traffic hot spot server, a traveling route planning module based on hot spot avoiding, a traffic hot spot and avoiding route display module and intelligent mobile phone end application software. The traffic jam avoiding prompting system faces the collective intelligence sensing network, is combined with the traditional traffic information sources, carries out digging and prediction on the urban traffic hot spots on the basis of the data activation technology, and further provides the traffic jam hot spot display and avoiding prompt service for intelligent terminal users. The traffic jam avoiding prompting system has the advantages that the data is from the multi-source collective intelligence network, the accuracy is good, the checking comprehensive rate is high, the hot spots are captured and fed back in real time, high efficiency and practicability are realized, the design is good, the operation is stable, the installation is convenient, the traffic jam avoiding prompting system can become a tool capable of providing wide and practical intelligent traffic information for urban residents, and the efficient information prompt is provided for the users to realize the smooth traveling.

Description

technical field [0001] The present invention relates to an intelligent traffic hotspot congestion hotspot discovery and avoidance prompt system, in particular to a multi-source data mining method in the field of traffic, where the mining results are provided to mobile terminals through wireless communication, and the mobile terminal uses these data to combine with the mobile terminal It uses its own location data to provide intelligent reminders for avoiding congestion hotspots. Background technique [0002] With the development of the world economy and the popularization of automobiles, traffic congestion has become a common problem in today's society. Congestion not only brings inconvenience to our travel, but also causes economic losses to individuals and society. [0003] With the rapid development of network communication technology and the rapid popularization of mobile smart terminals (such as smart phones, tablet computers, etc.), smart terminals have generally carri...

AI Technical Summary

Problems solved by technology

The effect of information transmission such as web broadcast and radio broadcast is not good, and users need to actively obtain it. The information screen can only provide partial information for vehicles in local locations. help

The bigger problem is that even if users have obtained the above-mentioned relevant information, they can only judge the impact of the information on their own travel based on their own experience, and how to avoid or deal with the traffic congestion they have learned, and most users cannot Have a clear understanding of the travel section and road network, so it is impossible to make a good avoidance judgment

[0007] In addition, the above-mentioned information is independent of each other, and there is no system that can integrate them, manage and release them in a unified manner

However, the above-mentioned information has the randomness of the information format. The traffic broadcast information and the traffic congestion news in Weibo are all colloquial texts. At present, there is no special text mining method to convert them into formatted data, and only Only after the data is formatted can it be better used and disseminated

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