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Drug rehabilitation place security situation analysis method and system based on big data

A technology of security situation and analysis method, which is applied in the field of safety situation analysis of drug rehabilitation centers based on big data. It can solve the problem of reducing the management efficiency of drug rehabilitation centers and the ability to deal with emergencies, the inability to perceive and obtain the security situation of sites in a timely manner, and the difficulty of knowing drug rehabilitation Issues such as the safety level of places, to achieve the effect of eliminating information islands, reducing crime, and ensuring social stability

Pending Publication Date: 2020-05-12
ANHUI SUN CREATE ELECTRONICS
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The security system, emergency system, production system, and education system in the site are all built independently, failing to achieve effective integration of resources, resulting in isolated islands of information, the site security situation cannot be sensed and acquired in a timely manner, and the data of each system can only be obtained from the site information
[0003] The data of each system is isolated from each other, making it difficult for the staff of the drug rehabilitation center to know the safety level of the drug rehabilitation center, which reduces the management efficiency of the drug rehabilitation center and the ability to deal with emergencies

Method used

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  • Drug rehabilitation place security situation analysis method and system based on big data
  • Drug rehabilitation place security situation analysis method and system based on big data
  • Drug rehabilitation place security situation analysis method and system based on big data

Examples

Experimental program
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Effect test

Embodiment 1

[0046] A method for analyzing the safety situation of drug rehabilitation centers based on big data, such as figure 1 shown, including the following steps:

[0047] S1. Real-time extraction of relevant data from the equipment library, site space data, site alarm data, and video database by ETL. Hierarchical analysis screens out available data factors and establishes historical information data. In this embodiment, historical information data includes at least education safety information data, medical safety information data, regulatory safety information data, safety prevention information data, and diagnosis and evaluation information data.

[0048] Correction safety information includes escape information, death information, case information, drug use information, and return rate information in drug rehabilitation centers;

[0049] Medical safety information includes HIV infection information, medical information after leaving a drug rehabilitation center, key disease info...

Embodiment 2

[0078] A security situation analysis system for drug rehabilitation centers based on big data, such as figure 2 As shown, the system includes a data acquisition module 1, a data storage module 2, a data processing module 3, and an application module 4 that are electrically connected in sequence, wherein the application module 4 is used for alarming.

[0079] The data storage module 2 includes a management safety information data storage unit 20 , a medical safety information data storage unit 21 , a diagnostic assessment information data storage unit 22 , a safety protection information data storage unit 23 , and a supervisory safety information data storage unit 24 .

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Abstract

The invention relates to the technical field of big data prediction and analysis, in particular to a drug rehabilitation place safety situation analysis method based on big data. The method comprisessteps of acquiring historical information data of the drug rehabilitation place from a database; performing normalization processing on each piece of historical information data; respectively inputting each piece of historical information data after normalization processing into a neural network model, training each piece of historical information data by the neural network model, and after training, outputting the weight of the historical information data by the neural network model; acquiring real-time information data of the drug rehabilitation place; normalizing the real-time information data of the drug rehabilitation place, and performing weighted calculation to obtain a score of the security situation of the drug rehabilitation place; and obtaining the safety level of the drug rehabilitation place according to the score of the safety situation of the drug rehabilitation place. The data of each system is fully utilized, so that workers in the drug rehabilitation place can know the safety level of the drug rehabilitation place in time, and the drug rehabilitation place is convenient to manage.

Description

technical field [0001] The invention relates to the technical field of big data predictive analysis, in particular to a method for analyzing the safety situation of drug rehabilitation centers based on big data. Background technique [0002] At present, with the support of a series of policies from the state, the Ministry of Justice, the government, the Department of Justice, and related units, the drug rehabilitation system is promoting the information construction of the drug rehabilitation center's security system, emergency response system, production system, and education system. The security system, emergency system, production system, and education system in the site are all built independently, failing to achieve effective integration of resources, resulting in isolated islands of information, the site security situation cannot be sensed and acquired in a timely manner, and the data of each system can only be obtained from the site information. [0003] The data of ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/25G06Q10/06G06Q50/26
CPCG06F16/254G06Q10/0639G06Q50/26
Inventor 李环寰范联伟王卫马韵洁杨春合陈昌健孙威蔚张时雄徐小兵张金良范留洋叶能锋熊飞江建宇
Owner ANHUI SUN CREATE ELECTRONICS
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