Design And Implementation Of Escort Risk Early Warning System Based On Multi-Source Heterogeneous Data Fusion

In the prison supervision system,going out to escort is one of the most risky links.Once there are accidents such as the escape of the escorted personnel on the way of escorting,there will be panic and social instability.At present,the risk monitoring means on the way of escorting are mainly manual intervention,which relies on the experience of police officers,which costs manpower,high cost and low efficiency.With the rapid development of communication technology and artificial intelligence technology,risk early warning system based on artificial intelligence technology is gradually penetrating into all fields of society,and plays an important role in maintaining the normal operation of enterprises and ensuring the quality of people’s life.Therefore,the research on how to apply the artificial intelligence technology to the escort risk early warning system is of great help to improve the prison supervision system and promote the informatization and intellectualization of the escort task.Firstly,this paper makes an in-depth study on the risk early warning system in various fields,and summarizes two shortcomings of the existing risk early warning system:one is that the existing risk early warning system usually only models the data generated by a single data source,which leads to the bottleneck of the system’s risk early warning ability and is difficult to further improve;the other is that in order to ensure the system performance,the risk early warning model is becoming wider and wider This makes the system to hardware equipment computing resources and computing power requirements.However,due to the high precision requirement of the early warning system and the limited hardware resources,the existing models can not be directly applied to the task.Therefore,this paper proposes a multi-source heterogeneous data fusion model based on deep learning to break through the performance bottleneck of the existing risk early warning model.In addition,this paper optimizes the multi-source heterogeneous data representation model,reduces the model parameters and computational complexity on the premise of ensuring the accuracy of the model,and ensures the normal operation of the escort risk early warning system in the environment of limited computing resources.Then,through a series of comparative experiments and ablation experiments,the efficiency of the risk early warning model based on multi-source heterogeneous data fusion is verified.Finally,this paper designs and implements an escort risk early warning system based on multi-source heterogeneous data fusion.In this paper,the system is divided into data acquisition module,risk early warning module,persistence module and visualization module.The risk early warning module adopts the risk early warning model based on multi-source heterogeneous data fusion.Finally,through a series of system tests,it is verified that the system can meet the needs of the scene and meet the design expectations.