Dynamic Smart Gas Work Order Visualization Graph
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Solution Overview
Problem
Current work order visualization systems for smart gas platforms do not dynamically update visual data graphs, leading to inefficiencies in interaction and processing of gas work orders, as they only display geographic positions and execution degrees without predicting or displaying execution time and problems.
Innovation Solution
A method and Internet of Things system that obtains work order management and executor data to determine candidate gas work orders, generate information including type, difficulty, status, and executor position, and create a visual data graph, which is dynamically updated based on user feedback and cycle data to improve interaction and processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If work order data is displayed using static visualization techniques showing only geographic position and execution degree, then the system structure remains simple, but the interaction efficiency and processing timeliness deteriorate due to lack of dynamic updates
Solution Approach 1:
The patent transforms the static work order visualization system into a dynamic one by implementing real-time data updates. The system now dynamically refreshes the visual data graph with current work order status, executor position, and execution progress, allowing the visualization to adapt continuously rather than remaining fixed after initial display.
Solution Approach 2:
The patent introduces feedback mechanisms where the visualization system continuously receives updated work order data from the management platform and executor terminals. This feedback loop enables the system to automatically adjust and update the visual representation based on real-time changes in work order status, improving responsiveness without requiring manual intervention.
2Loss of information
If dynamic prediction and display of work order execution time and problems are added, then the information completeness improves, but the data processing complexity increases
Solution Approach 1:
The patent makes the visualization system multi-functional by enabling it to display not only basic work order information but also predicted execution times, potential problems, and real-time status updates. The same visual data graph structure is enhanced to accommodate multiple types of information simultaneously, avoiding the need for separate specialized displays for each data type.
Solution Approach 2:
The patent implements predictive functionality that calculates and displays estimated execution times and potential problems before the work order is actually completed. This preliminary action allows planners and managers to anticipate issues and prepare accordingly, adding informational value without requiring complex real-time analysis during execution.
3Loss of time
If real-time dynamic updating of visual data graph is implemented, then the timeliness of work order information improves, but the system resource consumption increases
Solution Approach 1:
The patent implements periodic updating of the visual data graph rather than continuous real-time updates. The system refreshes the visualization at predetermined intervals or when specific triggering events occur, such as changes in work order status or executor position. This periodic approach maintains information timeliness while significantly reducing the frequency of data processing and rendering operations, thereby lowering system resource consumption.
Data Source
AI summary
The present disclosure provides a method, an Internet of Things system and a storage medium for visualizing a work order of a smart gas platform. The method is executed by a smart gas management platform of an Internet of Things system for visualizing a work order of a smart gas platform, the method comprises: obtaining work order management data and executor data; determining at least one candidate gas work order based on the work order management data and the executor data; generating, based on the at least one candidate gas work order, a first information to be presented; and generating a gas work order data graph based on the first information to be presented, the gas work order data graph being a visual chart.