IoT System for Smart Gas Work Order Evaluation
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Solution Overview
Problem
The evaluation of gas work order execution quality is subjective and lacks objectivity due to reliance on customer feedback, making it difficult to assess truly and reasonably.
Innovation Solution
An IoT system and method for evaluating gas work orders that classify orders based on operation data, determine evaluation parameters, and dynamically adjust scores using video recorder data and material usage records, incorporating a smart gas user platform, service platform, management platform, and sensor network to provide an objective evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If customer evaluation is used to assess work order execution quality, then the evaluation process is simple and easy to implement, but the evaluation result becomes subjective and lacks objectivity
Solution Approach 1:
The patent introduces multiple intermediary elements including video recorders, material usage recording devices, and IoT sensors as mediators between the work execution and evaluation processes. These intermediaries objectively record execution details, material consumption, and work quality metrics, replacing subjective customer evaluation with verifiable data from third-party recording devices.
Solution Approach 2:
The system implements multi-source feedback mechanisms where video recorders, material usage devices, and IoT sensors continuously provide feedback data about work execution. This feedback loop allows real-time monitoring and objective assessment of work quality, duration, and material efficiency, enabling dynamic adjustment of evaluation results based on actual performance data.
2Measurement precision
If multiple data sources and IoT devices are integrated for evaluation, then the evaluation objectivity and reliability improve, but the system complexity increases
Solution Approach 1:
The patent designs a multi-functional evaluation system where a single evaluation server performs multiple functions: collecting data from various IoT devices, processing video recordings, analyzing material usage, calculating evaluation scores, and generating reports. This universal evaluation platform consolidates multiple functions into one system, reducing overall complexity despite integrating multiple data sources.
Solution Approach 2:
The system merges multiple evaluation dimensions (work quality, duration, material efficiency) into a unified evaluation framework. By combining video analysis, sensor data, and material usage records into a single integrated evaluation process, the system achieves comprehensive objectivity without requiring separate complex systems for each evaluation aspect.
3Measurement precision
If dynamic adjustment of evaluation parameters is implemented based on execution data, then the evaluation accuracy improves, but the computational requirements and processing time increase
Solution Approach 1:
The system performs preliminary actions by pre-establishing evaluation parameter weights and thresholds before actual work execution. Evaluation criteria, scoring standards, and adjustment rules are configured in advance, allowing the system to quickly process execution data without complex real-time calculations. This preconfiguration enables fast dynamic adjustment during and after work execution.
Solution Approach 2:
The evaluation system dynamically adjusts parameters such as evaluation weights, scoring thresholds, and criterion importance based on execution data characteristics. By changing parameters rather than recalculating entire evaluation models, the system achieves high accuracy with minimal processing time, adapting evaluation strictness and focus based on work type, difficulty, and execution conditions.
Data Source
AI summary
Methods, Internet of Things (IoT) systems, and storage mediums for execution quality evaluation of a smart gas work order are provided. The method is executed by the IoT system for execution quality evaluation of a smart gas work order, including: classifying the work order based on operation data of the gas work order and determining a work order category; collecting work order execution data based on a video recorder and obtaining gas platform monitoring data through a material usage recording device; determining, based on at least one of the work order category, the work order execution data, or the gas platform monitoring data, an evaluation parameter; dynamically adjusting the evaluation parameter in response to a determination that the work order execution data or the gas platform monitoring data meets a preset condition; and determining, based on the evaluation parameter, an evaluation result.