Smart Gas IoT Task Allocation for Accurate Fault Dispatch
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Solution Overview
Problem
Existing gas maintenance systems randomly assign customer service staff and maintainers, leading to mismatches in work order processing scopes and abilities, resulting in reduced location accuracy and customer satisfaction.
Innovation Solution
An IoT system comprising a smart gas user platform, service platform, management platform, sensor network platform, and object platform, which uses machine learning to predict gas fault types, adjust work order processing scopes based on multi-dimensional evaluations, and allocate maintenance tasks accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If random assignment of customer service staff and maintainers is used, then the system operation is simple, but the work order processing scope mismatch occurs leading to reduced location accuracy and customer satisfaction
Solution Approach 1:
The system changes the parameter of agent-matcher pairing from random to skill-based matching. By evaluating agent capabilities (communication skills, fault identification accuracy) and matcher expertise (technical knowledge, problem-solving abilities), the system dynamically assigns work orders to optimize location accuracy and maintenance quality.
Solution Approach 2:
The patent replaces the mechanical random assignment system with an intelligent algorithmic system. The system uses data-driven evaluation metrics and automated matching algorithms to assign work orders, substituting manual or random processes with smart computational methods that consider multiple dimensions of agent and matcher capabilities.
2Productivity
If skill-based matching of agents and maintainers is implemented, then location accuracy and maintenance quality improve, but the system complexity increases
Solution Approach 1:
The system segments the evaluation process into distinct components: agent capability evaluation, matcher skill assessment, and compatibility matching. By dividing the complex matching task into separate evaluable dimensions, the system can process and compare multiple factors systematically without overwhelming complexity.
Solution Approach 2:
The patent introduces an intermediary evaluation system that acts as a mediator between agents and matchers. This intermediary component assesses capabilities, generates compatibility scores, and facilitates optimal pairing, reducing the direct complexity between users and the matching mechanism while improving overall productivity.
3Reliability
If multi-dimensional evaluation of agents and maintainers is performed, then work order allocation accuracy improves, but the data processing requirements increase
Solution Approach 1:
The system extracts and focuses on the most critical evaluation dimensions from the available data, rather than processing all possible information. By identifying and extracting key capability metrics and matching factors, the system achieves reliable work order allocation while managing data processing requirements efficiently.
Data Source
AI summary
A method and an Internet of Things (IoT) system for allocating maintenance tasks based on smart gas are provided. A smart gas management platform of the Internet of Things (IoT) system is configured to: obtain call consultation data information; generate first data information from the call consultation data information; generate one or more maintenance feature vectors of a maintainer to be evaluated; determine a first maintenance evaluation value for the one or more maintenance feature vectors; generate second data information; determine and input user-side gas feature data, gas composition features, gas entry features, and gas upstream transportation features into a gas fault prediction model to predict a gas fault type; generate a location accuracy of one or more location feature vectors; adjust a work order processing scope of the maintainer to be evaluated based on a multi-dimensional maintenance evaluation value; and allocate subsequent maintenance tasks.