A method and apparatus for business monitoring based on Internet of Things (IoT) technology

By configuring multiple events and nesting the processing results of second events on the IoT platform, the problems of insufficient real-time performance, high frequency, and complexity in existing solutions are solved, enabling flexible business monitoring and efficient data processing, and meeting the business monitoring needs of industrial production and daily life.

CN122308965APending Publication Date: 2026-06-30HUAWEI TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
HUAWEI TECH CO LTD
Filing Date
2024-12-27
Publication Date
2026-06-30

AI Technical Summary

Technical Problem

Existing IoT data statistical analysis solutions cannot simultaneously meet the requirements of real-time performance, high frequency, and complexity, and lack flexibility, making it difficult to meet the business monitoring needs of industrial production and daily life.

Method used

By configuring multiple events on the IoT platform, users can customize the triggering conditions and processing rules of the events, nest the processing results of the second events to achieve multi-dimensional monitoring and flexible output, and support the aggregation and reprocessing of the second processing results information of multiple second events.

Benefits of technology

It enables monitoring of business operations from multiple dimensions, improving the flexibility and efficiency of business monitoring and meeting users' needs for real-time statistical analysis in complex business environments.

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Abstract

This application proposes a method and apparatus for business monitoring based on Internet of Things (IoT) technology. It allows users to configure multiple events, enabling monitoring of target data for a specific business based on these user-configured events. Furthermore, the method allows for the retrieval of secondary processing results from each secondary event within the first event, followed by further statistical analysis and filtering before output, thus improving the flexibility of business monitoring. This approach not only enables multi-dimensional monitoring of the business but also allows for the aggregation, reprocessing, and output of secondary processing results from multiple events, meeting the monitoring needs of users in their actual business operations.
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