Method and system for determining suspected vehicle involved in case

Abstract

The invention discloses a method and system for determining a suspected vehicle involved in a case. The method comprises: vehicle passing data are obtained and a vehicle passing record table and a vehicle passing index table are generated based on the vehicle passing data; the vehicle passing data are analyzed to generate a record table of vehicles with fake license plates; a suspected vehicle involved in a case is determined based on the vehicle passing record table, the vehicle passing index table, and the record table of vehicles with fake license plates, wherein determination conditions for determination includes a time-space condition and at least one of the following conditions: a sun shield state, a stealing high-risk area, a suspected vehicle with a fake license plate, frequent vehicle passing, and initial city entrance; and according to the determination result, the vehicle passing data in a suspected vehicle set are ranked based on score values in a suspected score set in a descending order, so that an involved suspected vehicle sequence table is generated. According to the method and system disclosed by the invention, the integrated analysis is carried out based on multiple features of involved vehicles, so that lots of useless data are filtered and removed; and most possible vehicles top the list, so that crime solving feasibility is improved.

Description

technical field [0001] The present invention relates to the technical field of public security, and more specifically, to a method and system for judging a suspected vehicle involved in a case. Background technique [0002] With the development of society, the number of private cars is increasing. While the popularity of private cars brings convenience to people's lives, they are also increasingly used by lawbreakers and become tools for their crimes. According to statistics, car-related cases account for about 50% of all criminal cases, and the proportion has been increasing in recent years, which has caused great difficulties for the police to detect cases. Some characteristics of criminal vehicles can be drawn from previously detected cases and the experience of the police, such as: criminals usually do not use vehicles under their own names to carry out illegal activities, and most of the vehicles they use are stolen from others or or the criminals used a deck of cards ...

AI Technical Summary

Problems solved by technology

[0003] Traditionally, there are several ways to screen suspect vehicles involved in the case: The first method is manual direct viewing and screening, where a few policemen directly browse and screen a large number of pictures of passing vehicles. , It is unrealistic to manually browse pictures one by one

The second is the various techniques and tactics often used in the police system, such as: deck car analysis, initial city entry analysis and other techniques and tactics. These methods are also based on big data and obtained from the analysis of massive traffic data However, in the real implementation environment, these single techniques and tactics cannot help the police to narrow down the scope of the search to the greatest extent.

For example: the analysis of the first entry into the city, there are tens of thousands of vehicles passing through the city for the first time in a county-level city every day (assuming that the backtracking time is one month), although it is much easier than searching from millions of data, but in this Cheng Among the tens of thousands of results, manually searching for a suspicious vehicle is tantamount to finding a needle in a haystack, and it cannot help the police save manpower and improve efficiency to the greatest extent.

In summary, the existing methods of screening suspected vehicles involved in the case are not very feasible in the detection of actual cases

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