Crime Scene Danger Prediction and Police Resource Allocation
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Solution Overview
Problem
The increasing number of crimes, particularly against women and children, in previously safe areas has led to a shortage of personnel and equipment for personal protection, resulting in varying response capabilities among police officers and inadequate management of crime scene responses.
Innovation Solution
A method and apparatus for predicting the degree of danger at a crime scene by generating predicted and current danger information, calculating the range of dispatched and field police forces, and determining responses based on available resources, using report content information and deep learning models to assess suspect actions, crime types, and police force capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If more police personnel and equipment are deployed to respond to all personal protection requests, then the response capability and safety level improve, but the resource shortage and management burden worsen due to the sheer volume of requests
Solution Approach 1:
The patent applies parameter changes by transforming the response allocation from a uniform approach to a dynamic, risk-based approach. It uses danger degree parameters (calculated from crime type, suspect characteristics, location, and time) to adjust police force deployment levels. This allows the system to concentrate resources on high-risk situations while reducing deployment for low-risk cases, thereby improving overall response capability without proportionally increasing total personnel and equipment requirements.
2Reliability
If police response capabilities are standardized across all officers, then the consistency and reliability of responses improve, but the adaptability to varying crime scene complexities worsens
Solution Approach 1:
The patent implements dynamics by creating a flexible, multi-level response system that adapts to varying crime scene complexities. Instead of rigid standardization, it dynamically adjusts the response plan based on calculated danger degrees and available resources. The system can scale response intensity from minimal to maximum levels, allowing consistent procedural frameworks while adapting the actual deployment to match the specific complexity of each crime scene.
Solution Approach 2:
The patent applies segmentation by dividing the response system into multiple levels or tiers based on danger degree assessments. Crime scenes are segmented into different risk categories, and corresponding response protocols are segmented into appropriate intensity levels. This allows standardized procedures within each segment while providing overall adaptability across different segments.
3Measurement precision
If comprehensive data collection and analysis are performed to accurately predict danger degrees, then the precision of risk assessment improves, but the time and computational resources required worsen
Solution Approach 1:
The patent applies preliminary action by pre-establishing danger degree calculation models and criteria before actual crime scene responses are needed. It pre-defines the weighting of various factors (crime type, suspect characteristics, location, time) and prepares response templates in advance. When a crime occurs, the system只需 applies these pre-prepared models to the specific case data, significantly reducing real-time processing requirements while maintaining high prediction accuracy.
Data Source
AI summary
Disclosed herein are a method and apparatus for determining responses to dangerous situations based on the degrees of danger. The method includes generating predicted danger information of a crime scene and predicting current danger information of the crime scene based on pieces of report content information and pieces of field police report content information, calculating information about a range of dispatched police force based on pieces of dispatched police report content information, calculating information about a current field police force status and a range of the field police force based on the field police report content information, and determining a response to the crime scene based on supportable resource information for the crime scene, the predicted danger information, the current danger information, the dispatched police force range information, and the information about the current field police force status and the range of the field police force.