Smart Gas Pipeline IoT Maintenance with Adaptive Data Retention
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Solution Overview
Problem
Existing gas pipeline management techniques are unable to perform timely maintenance of appurtenant facilities, leading to frequent accidents and failures due to limited storage performance and inaccurate determination of maintenance needs.
Innovation Solution
A method and IoT system for maintaining smart gas pipeline networks, which includes obtaining historical maintenance data, controlling monitoring devices for data collection, determining maintenance needs, generating maintenance instructions, and adjusting storage unit parameters to optimize performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If maintenance data is collected at fixed intervals and stored in a storage unit, then historical maintenance data is available for analysis, but the storage performance is limited and cannot retain sufficient valid data for accurate maintenance determination
Solution Approach 1:
The patent extracts only the most critical and recent maintenance data from the storage unit, deleting older or less important data. This selective extraction approach retains sufficient valid data for accurate maintenance determination while adapting to limited storage capacity, directly resolving the contradiction between data quantity needed for reliability and actual storage availability.
2Loss of information
If data collection frequency is maintained at initial preset frequency, then comprehensive maintenance data is collected, but storage unit performance deteriorates due to excessive data volume
Solution Approach 1:
The patent dynamically adjusts the data collection frequency based on the current storage unit performance and historical maintenance patterns. When storage performance is sufficient, higher frequency collects more comprehensive data. When storage is constrained, frequency is reduced to preserve storage performance. This dynamic adaptation resolves the contradiction between data completeness and storage energy consumption.
Solution Approach 2:
The system changes the parameter of data collection frequency based on storage unit evaluation. By adjusting this parameter dynamically, the system optimizes the balance between collecting sufficient maintenance data and preserving storage unit performance, preventing both data loss and storage overload.
3Measurement precision
If all historical maintenance data is retained, then accurate maintenance determination is achieved, but storage unit becomes overloaded and performance degrades
Solution Approach 1:
The patent extracts and retains only the most valuable maintenance data for analysis, deleting redundant or expired data. This selective retention approach maintains measurement precision for maintenance determination while preventing storage unit overload, directly resolving the contradiction between data retention for accuracy and storage productivity.
Solution Approach 2:
Instead of retaining all historical data (excessive action), the system retains only the necessary portion of data required for accurate maintenance determination. This partial action approach achieves sufficient measurement precision without overwhelming storage unit capacity, optimizing the balance between data retention and system productivity.
Data Source
AI summary
Disclosed is a method, an IoT system, and a storage medium for maintaining an appurtenant facility of a smart gas pipeline network. The method may include: obtaining historical maintenance data and data collection information of an appurtenant monitoring device and storing the historical maintenance data and data collection information in a storage unit; determining whether the appurtenant monitoring device requires maintenance based on the historical maintenance data and data collection information; in response to determining that the appurtenant monitoring device requires maintenance, determining a maintenance parameter and generating a maintenance instruction; sending the maintenance instruction to an interactive interface; obtaining an evaluation parameter of the storage unit; in response to determining that the evaluation parameter of the storage unit satisfies a preset parameter requirement, generating an adjustment instruction and sending the adjustment instruction to the storage unit.