CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD. (20240249048). METHOD, INTERNET OF THINGS SYSTEM, AND STORAGE MEDIUM FOR ADJUSTMENT OF PIPELINE NETWORK INSPECTION BASED ON SMART GAS GEOGRAPHIC INFORMATION SYSTEM simplified abstract
METHOD, INTERNET OF THINGS SYSTEM, AND STORAGE MEDIUM FOR ADJUSTMENT OF PIPELINE NETWORK INSPECTION BASED ON SMART GAS GEOGRAPHIC INFORMATION SYSTEM
Organization Name
CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD.
Inventor(s)
METHOD, INTERNET OF THINGS SYSTEM, AND STORAGE MEDIUM FOR ADJUSTMENT OF PIPELINE NETWORK INSPECTION BASED ON SMART GAS GEOGRAPHIC INFORMATION SYSTEM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240249048 titled 'METHOD, INTERNET OF THINGS SYSTEM, AND STORAGE MEDIUM FOR ADJUSTMENT OF PIPELINE NETWORK INSPECTION BASED ON SMART GAS GEOGRAPHIC INFORMATION SYSTEM
The embodiments of the present disclosure provide a method, an Internet of Things system, and a storage medium for adjustment of pipeline network inspection based on a Smart Gas Geographic Information System (GIS). The method involves obtaining gas monitoring data and inspection features of at least one inspection unit, determining gas inspection areas, predicting abnormality possibilities, updating inspection features, and determining updated gas inspection areas.
- Obtaining gas monitoring data and inspection features
- Dividing gas pipeline network map of Smart Gas GIS
- Predicting abnormality possibilities using prediction models
- Determining reliability of inspection results
- Updating inspection features based on reliability
- Determining updated gas inspection areas
- Potential Applications:
This technology can be applied in the gas industry for efficient inspection and maintenance of pipeline networks. It can also be used in other industries that require predictive maintenance based on monitoring data.
- Problems Solved:
This technology addresses the challenges of manual inspection processes by automating the analysis of gas monitoring data and inspection features. It helps in predicting abnormalities and updating inspection features for more accurate results.
- Benefits:
- Improved efficiency in pipeline network inspection - Early detection of abnormalities - Enhanced reliability of inspection results - Cost savings through predictive maintenance
- Commercial Applications:
Title: Smart Gas Pipeline Inspection System This technology can be commercialized by gas companies, utility providers, and infrastructure management companies for optimizing their pipeline inspection processes. It can also be integrated into IoT systems for real-time monitoring and maintenance.
- Prior Art:
Prior art related to this technology may include existing systems for pipeline inspection and predictive maintenance in the gas industry. Researchers can explore patents and publications in the field of GIS and IoT applications for infrastructure management.
- Frequently Updated Research:
Researchers in the field of predictive maintenance, GIS, and IoT systems are continuously working on improving the accuracy and efficiency of pipeline inspection technologies. Stay updated on the latest advancements in predictive modeling and data analysis for gas networks.
- Questions about Smart Gas Geographic Information System:
1. How does this technology improve the reliability of gas pipeline inspections? 2. What are the key features of the Smart Gas GIS system?
Original Abstract Submitted
the embodiments of the present disclosure provide a method, an internet of things system, and a storage medium for adjustment of pipeline network inspection based on a smart gas geographic information system (gis). the method comprises: obtaining gas monitoring data and inspection features of at least one inspection unit; determining at least one gas inspection area by dividing a gas pipeline network map of the smart gas gis and obtaining an inspection result of the at least one gas inspection area; predicting a first abnormality possibility by a first prediction model; predicting a second abnormality possibility by a second prediction model; determining reliability of the inspection result based on a consistency between the first and the second abnormality possibilities; determining updated inspection features by updating the inspection features based on the reliability of the inspection result; and determining an updated gas inspection area based on the updated inspection features.
