Smart Gas Work Order Supervision With IoT Risk Warning
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Solution Overview
Problem
Gas platforms in IoT systems lack the ability to supervise the quality of work order execution and resolve difficult gas problems, leading to delayed resolutions and potential human errors.
Innovation Solution
An IoT system for gas platforms that includes a smart gas management platform to obtain execution data, determine gas problems and their reasons, and provide targeted processing schemes to users, with feedback-based risk level adjustments and early warning notifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If gas platforms only transfer and relay work orders manually, then device complexity is reduced, but work order execution quality supervision and problem resolution are insufficient
Solution Approach 1:
The gas platform is transformed from a simple relay device into a multi-functional system that simultaneously performs work order transfer, execution quality supervision, problem diagnosis, and early warning functions. The platform integrates multiple capabilities including data collection from sensors, execution monitoring, feedback analysis, and automated warning generation, allowing one system to fulfill diverse responsibilities that previously required separate manual processes.
Solution Approach 2:
The system enables automated self-supervision of work order execution through sensors and feedback mechanisms. The platform automatically collects execution data, compares it against standards, identifies deviations, and generates warnings without requiring continuous manual intervention. This self-service capability improves reliability while maintaining manageable system complexity through automation of routine monitoring tasks.
2Productivity
If manual processing of gas work orders is used, then ease of operation is maintained, but resolution speed and accuracy decrease
Solution Approach 1:
The system implements continuous feedback loops where sensors monitor work order execution in real-time, and the platform automatically processes this data to identify issues and generate warnings. This automated feedback mechanism accelerates problem detection and resolution while maintaining ease of operation through user-friendly interfaces that present processed information clearly to operators.
Solution Approach 2:
Manual mechanical processing of work orders is replaced with automated electronic data collection, processing, and analysis systems. Sensors, communication networks, and software algorithms substitute for manual data gathering and analysis, dramatically improving resolution speed while presenting simplified digital interfaces to users that maintain operational ease.
3Reliability
If the gas platform supervises work order execution quality, then work order execution quality improves, but device complexity increases
Solution Approach 1:
The supervision function is segmented into distinct modular components including data collection modules from sensors, data processing modules that analyze execution quality, feedback analysis modules that evaluate results, and warning generation modules that alert stakeholders. This segmentation allows each component to perform its specific function efficiently while maintaining overall system manageability through clear separation of concerns.
4Measurement precision
If early warning notification system is implemented, then problem resolution accuracy improves, but loss of time for system setup increases
Solution Approach 1:
The system performs preliminary actions by pre-configuring threshold values, warning criteria, and notification protocols during system setup. Risk assessment models and decision rules are established in advance, allowing the platform to immediately begin accurate risk level assessment and early warning generation without requiring complex real-time configuration. This preliminary setup minimizes implementation time while ensuring measurement precision from the start.
Data Source
AI summary
The embodiments of the present disclosure provide a method and an Internet of Things system for processing a work order of a gas platform based on smart gas operation. The method includes: obtaining execution data of the gas work order; determining at least one gas problem corresponding to the gas work order and a reference reason of the at least one gas problem based on the execution data; determining a target processing scheme of the gas work order based on the at least one gas problem and the reference reason, and sending the target processing scheme to a user terminal of an executant; in response to that a feedback of the user terminal satisfies a feedback preset condition, improving a risk level of the gas work order and providing an early warning notification.


