当前警察在执法取证过程中取证手段单一，不能实时、有效地对证据进行分析处理，不能为执法任务的侦查、抓捕等行动提供有效辅助支撑。为解决此类问题，构建了一种以多警员协同取证为主、单警员取证为辅的体系化单警执法系统。采用网络体系架构，集成先进取证设备、传输设备，应用基于深度学习算法的证据处理系统，并采用系统工程的方法，对该系统进行总体和运行流程设计，在设计过程中提出了信息集成、指挥辅助决策、特征提取等关键技术。

At present, police have only a single means of evidence collection in the process of law enforcement and can neither analyze and deal with evidence effectively in real time nor provide effective support for investigation and arrest of law enforcement tasks. To solve these problems, we propose a single police law enforcement system based on rights protection law enforcement tasks. We adopt network architecture, integrate advanced forensic equipment and transmission equipment and apply deep learning algorithm to the evidence processing system to construct a systematic single police law enforcement system based on single police evidence collection and multiple police cooperative evidence collection. We use system engineering method to design the system and the operation process. In the design process, we put forward key technologies such as information integration, command assistant decision making and feature extraction.