An extreme depression propensity identification system

By constructing an extreme depressive tendency identification system and utilizing big data and neural network technology, we have achieved accurate identification and early warning of individuals with extreme behaviors, solving the problems of insufficient efficiency and accuracy in traditional methods and improving crime prevention capabilities.

CN122778094APending Publication Date: 2026-09-18NINGXIA POLICE OFFICER VOCATIONAL COLLEGE
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Patent Information

Application Number
CN202510039599.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-01-10
Publication Date
2026-09-18

AI Technical Summary

Technical Problem

Traditional methods of suspect tracking rely on limited eyewitness information and manual screening, which are inefficient and inaccurate. They lack systems that utilize big data to accurately screen suspects, and there are no effective means to identify extreme depressive tendencies.

Method used

Design an extreme depressive tendency identification system. The system captures and integrates information from multiple data sources through a data acquisition module, uses recurrent neural networks, long short-term memory networks and convolutional neural networks for behavioral analysis, constructs an emotion dictionary and scoring model, tracks and evaluates an individual's emotional tendency in real time, and triggers corresponding early warning and emergency measures.

Benefits of technology

It enables efficient and accurate identification and early warning of extremist behavior, reduces resource waste, provides an objective evaluation of extremist behavior and rational resource utilization, and improves the effectiveness of crime prevention.

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Abstract

This invention belongs to the field of management methods technology, specifically a system for identifying extreme depressive tendencies. It includes a data acquisition module and a behavior analysis module. The data acquisition module accesses, but is not limited to, public safety databases, internet data, and IoT data, and is responsible for capturing data from big data sources and analyzing and integrating the captured data. The behavior analysis module is responsible for analyzing the data and triggering corresponding response mechanisms. The system also includes a data interface management module, responsible for managing interfaces with various data sources to ensure stable data collection. This invention integrates multi-source big data and utilizes big data capture, analysis, and processing technologies to more accurately and efficiently track individuals, providing strong technical support for management work and playing a significant role in preventing serious crimes. Furthermore, this system allows for the rational use of resources based on scoring, reducing unnecessary resource waste.
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