下一代公共安全视频监控系统的大数据分析

视频监控因其可以提供丰富的、直观的以及精确的信息而成为主要的监控工具. 然而, 随着视频监控系统在世界各地的大规模建设, 由于一些诸如“有用信息和线索不能及时从视频大数据中被发现”的问题, 降低了犯罪预测和公共安全治理的检测效率. 各类公共安全信息系统被用于交通事故治理、犯罪事件和恐怖事件的预测. 但是, 大规模的系统冗余建设导致了“IT 资源”和“信息过载”的巨大浪费. 为了解决上述问题, 如大数据、云计算和虚拟化技术已被广泛应用于公共安全行业. 采用“前+后”的模式, 为下一代公安系统提出了一种新的架构.在该架构下, 介绍了云计算技术如分布式存储和计算、巨大的异构数据的检索, 并且提出了多个优化策略, 提高了资源的利用率和任务的完成效率.

Big data analysis of next generation video surveillance system for public security

Video surveillance has become an important tool due to its rich, intuitive and accurate information. However, with the large-scale construction of video surveillance systems all over the world, useful information and clues cannot be found immediately from the huge video data. The problem affects detection efficiency in crime prediction and public security governance. A great variety of public security information systems have been built for management of traffic accidents, and prediction of criminal events and terrorist attacks. However, large redundant construction of systems leads to great waste of IT resource andinformation overload. Technologies such as big data, cloud computing and virtualization have been applied in the public security industry to solve these problems. This paper describes a novel architecture for the next generation public security system in which a front-plus-back pattern is used. In the architecture, cloud technologies such as distributed storage and computing, data retrieval of huge and heterogeneous data are introduced. Multiple optimized strategies are proposed to enhance resources utilization and efficiency of tasks.