Abnormal event identification and alerting method, apparatus, device, and medium

By integrating log collection, cleaning, parsing, indexing, analysis, display, and alarm processing, the problem of lagging log data processing across multiple data nodes has been solved, achieving timely and accurate anomaly identification and intuitive risk monitoring.

CN122285443APending Publication Date: 2026-06-26PING AN HEALTH INSURANCE CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
PING AN HEALTH INSURANCE CO LTD
Filing Date
2026-04-14
Publication Date
2026-06-26

AI Technical Summary

Technical Problem

Existing technologies struggle to collect, structure, and analyze log data from multiple data nodes in a unified manner, resulting in delayed anomaly identification, unintuitive display, and untimely alarm response.

Method used

By connecting multiple data nodes through log collection tools, raw log information is obtained, fields are cleaned and structured parsed to generate structured log data, and a query index is built on the data processing platform. Anomalies and their severity are analyzed using a predictive model, visualization components are called to generate and display information, and alarm information is generated and sent to the receiving terminal.

Benefits of technology

It achieves timely and accurate anomaly identification, improves the intuitiveness and response efficiency of risk monitoring, and is applicable to business scenarios such as fintech and healthcare.

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Abstract

This invention relates to the field of intelligent decision-making technology, and discloses a method, apparatus, device, and medium for anomaly event identification and alarm. The method includes: acquiring raw log information from multiple data nodes using a log collection tool; generating structured log data through field cleaning and structured parsing; transmitting the data to a data processing platform for storage and establishing a query index; using a predictive model to analyze and identify anomaly events and their severity levels; calling a visualization component to generate and display information; and generating alarm information and sending it to a receiving terminal. This invention can be applied to business scenarios such as fintech and healthcare. By integrating the collection, parsing, indexing, analysis, display, and alarm processing of log data, it enables more timely and accurate anomaly identification, improving the intuitiveness and response efficiency of risk monitoring.
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