Population abnormal information detection method and system based on big data

Abstract

The embodiment of the invention provides a population abnormal information detection method and system based on big data. The method comprises the following steps: sequencing and interpolating population movement track data by taking a time sequence as a unit to form a population continuous movement track, counting geographic information of an area where each time unit of population is located through a geographic information system, and forming a population movement data set by combining basic information of the population; clustering the population action data set by adopting a clustering algorithm, calculating geographic position characteristics of each person in each time period, extracting committed geographic position type and duration rules of each person in each time period by adopting an association rule algorithm, and constructing a population action track feature set; and importing real-time population action track data, and analyzing the duration that the population stays in an abnormal geographic feature area by comparing the population real-time geographic distance deviates from the population action track feature set distance to give a population abnormal action warning. The population management efficiency is improved.

Description

technical field [0001] The present application relates to the field of population management, in particular to a method and system for detecting abnormal population information based on big data. Background technique [0002] Population anomaly detection is an important part of smart city management. It aims to improve the level of population management and danger prevention, and provide better support for the protection of people's lives and property and the development of cities. The detection of abnormal population information focuses on the discovery of accidental risks, and provides special care for special groups of people to prevent accidents. Traditional population anomaly information detection is still in the mode of manual supervision, or passively waits for relevant personnel to call the police. It has not realized the intelligence of daily detection and management, and has not realized the use of big data. It wastes a lot of manpower, material resources and finan...

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Problems solved by technology

[0004] In view of this, the purpose of this application is to propose a method and system for detecting abnormal population information based on big data, improve the detection level of abnormal population information, and solve the low efficiency and high cost of risk identification in the current detection process of abnormal population information. question

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