Urban road network digital monitoring system and method

Abstract

The invention discloses an urban road network digital monitoring system and method, and the system comprises a camera which is used for collecting data information of a target area in real time; an independent caching device used for caching the data information of the target area; a target comparison device used for acquiring and processing the cached data information of the target area and generating multi-dimensional data information of a plurality of target objects of the target area; and a subarea 3D modeling device used for carrying out 3D modeling on the target area by utilizing the multi-dimensional data information of the plurality of target objects to generate a three-dimensional animation video of the target area. Therefore, by adopting the embodiment of the invention, a 3D monitoring video is constructed by utilizing the camera to acquire the image to perform digital monitoring on the urban road network based on the digital retina, so that the recognition precision is improved, the storage cost is reduced, and the retrieval difficulty is reduced.

Description

Technical field [0001] The invention relates to the technical field of security monitoring, in particular to a digital monitoring system and method for urban road networks. Background technique [0002] At present, the surveillance video network based on electronic maps has been widely used in daily urban prevention and control and command and dispatch. Through electronic map applications, real-time video surveillance of designated locations on electronic maps can be carried out. Compared with traditional surveillance platforms, The electronic map monitoring platform can provide a better user experience, more real-time point monitoring, more intuitive presentation, and smarter. [0003] The existing video surveillance system is basically designed for storage considerations. When it is necessary to retrieve the video of a certain time period and a certain place, it will find it from the massive video storage, and then find it through manual or intelligent methods. Clues were found ...

AI Technical Summary

Problems solved by technology

However, there are several problems in this traditional monitoring method: 1) It is difficult to identify. The most traditional identification method is to rely on human viewing and searching. This method has strong identification ability, but it is easy to miss or ignore key content due to subjective factors. The strategy is to use artificial intelligence methods such as video and image recognition algorithms, but there are also challenges in big data processing due to the long recognition time, large amount of data to be processed, and high investment costs; 2) Retrieval is difficult, and storage is conventional video The focus of the monitoring system, so the compression and encoding during the storage process may cause data loss, and the decompression and decoding when extracting data may also cause data loss. Even if the correct retrieval is performed, the original result is often not obtained; 3) The storage cost is high. The main reason for compressing data before storage is to improve memory utilization and reduce storage costs. Even so, the amount of data stored in existing video surveillance systems is still very large, and the greater the amount of data, the higher the cost. Moreover, the amount of data will inevitably show an obvious growth trend with the extension of storage time.

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