Abstract: A method, an Internet of Things (IoT) system, and a medium for disposing emergency gas supply of smart gas are provided. The method comprises: obtaining gas data based on a data acquisition device; determining future predicted data of a gas pipeline network system based on the gas data and gas pipeline features; determining a future fault pipeline based on the future predicted data; determining target regions based on the future fault pipeline; and determining an emergency vehicle dispatch instruction based on the target regions.

Abstract: The embodiment of the present disclosure provides a method and an Internet of Things (IoT) system for gas loss control based on a smart gas platform. The method is executed by a smart gas device management platform of the IoT system. The method includes: obtaining gas delivery parameters of a preset point in a gas pipeline branch; obtaining gas data corresponding to the gas pipeline branch; determining a gas loss rate of the gas pipeline branch based on the gas delivery parameters and the gas data; and in response to the gas loss rate satisfying a first predetermined condition, adjusting a pressure of a gas pipeline network.

Abstract: A method and a smart gas Internet of Things system for maintenance scheduling and management based on gas safety are provided. The method may comprise the following operations. Gas-related features of at least one area may be obtained, alert vectors of the at least one area may be determined based on the gas-related features, the alert vectors including a leakage alert value, a count of on-call maintenance personnel in the at least one area based on the alert vectors may be determined, whether the count of on-call maintenance personnel meets a preset threshold may be determined, in response to a determination that there is at least one area where the count of on-call maintenance personnel meets the preset threshold, a real-time scheduling policy based on a scheduling capability value of the at least one area where the count of on-call maintenance personnel meets the preset threshold may be determined.

Abstract: The present disclosure provides an industrial Internet of things for monitoring a collaborative robot and a control method, a storage medium thereof, wherein the control method comprises: obtaining position data of the workpiece to be processed as first monitoring data through the sensing network platform; selecting, based on the first monitoring data, a benchmark working parameter matching the first monitoring data from a working parameter library; obtaining, via the sensing network platform, a working parameter of the target collaborative robot as second monitoring data; comparing the second monitoring data with the benchmark working parameter to determine a working state of the target collaborative robot.

Abstract: The present disclosure provides an industrial IoT for correction and regulation of a defective product, a control method, and a storage medium. The industrial IoT includes a user platform, a service platform, a management platform, and a sensing network platform that interact in sequence. The service platform, the management platform, and the sensing network platform are all arranged in a front-sub-platform layout. The control method is applied in the industrial IoT. The industrial IoT may calculate whether a defective product is correctable according to a correction cost of the defective product, and may reduce the correction cost and a time consumption of a corresponding correction device, thereby reducing correction cost of the defective product and a loss in a manufacturing process, further ensuring a normal product manufacturing efficiency of the correction device, and thus reducing a correction loss of a waste product and the defective product.

Abstract: The present disclosure provides a method and an Internet of Things (IoT) system for full-cycle management of smart gas equipment based on the big data, implemented by a smart gas equipment management platform of IoT system for full-cycle management of smart gas equipment based on big data. The method comprises obtaining operation data of gas equipment by generating a data obtaining instruction based on a preset cycle, generating a partitioning instruction based on the operation data, determining first partitioning data and second partitioning data based on the partitioning instruction, and determining a maintenance scheme for the gas equipment based on the first partitioning data and/or the second partitioning data.

Abstract: The embodiments of the present disclosure provide a method and an Internet of Things (IoT) system for gas purification management in a storage and distribution station for smart gas. The method is implemented based on the IoT system for gas purification management in the storage and distribution station for smart gas. The IoT system includes a smart gas user platform, a smart gas service platform, a smart gas device management platform, a smart gas sensor network platform, and a smart gas object platform. The method is executed by the smart gas device management platform. The method includes: obtaining a gas quality condition parameter of a raw gas, and the gas quality condition parameter being obtained based on the storage and distribution station; determining, based on the gas quality condition parameter, an operation parameter in a purification process, the operation parameter being used for a purification operation of the raw gas.

Abstract: The embodiment of the present disclosure provides a method and an Internet of Things system for controlling a gas supply cost based on smart gas. The method is implemented by a smart gas management platform of the Internet of Things system. The method includes: predicting a gas supply quantity for a future preset time period based on a planned gas supply quantity of a gas supplier; predicting a gas demand quantity for the future preset time period based on a gas usage quantity of a historical user; determining a gas gap for the future preset time period based on the gas supply quantity and the gas demand quantity; and determining a gas compensation scheme based on the gas gap, operational requirements of an end of a pipeline, and operational parameters of the end of the pipeline.

Abstract: The present disclosure discloses Industrial Internet of Things (IIoT) system for industrial production data management, control method, and storage medium. By adopting different encryption methods for different image data, and without changing the overall architecture of the cloud computing Internet of Things, the safe penetration of sensitive data on the cloud computing platform is realized, which effectively improves the security of sensitive data. In addition, it does not require additional wiring, reducing the networking cost of the Internet of Things, which has high applicability.

Abstract: A method, an Internet of Things (IoT) system, and a storage medium for smart gas abnormal data analysis are provided. The method may include: obtaining a user feature and a pipeline network transportation feature of each of a plurality of gas users; obtaining a first clustering result and a second clustering result by clustering the gas user based on the user feature and the pipeline network transportation feature respectively, the first clustering result and the second clustering result including one or more gas user clusters, respectively; for any one of the gas user clusters: determining, based on device use data and/or gas metering data of the gas user in the gas user cluster, a potential abnormal gas user; determining a target abnormal user based on the first abnormal user and the second abnormal user; and sending an early warning message to the target abnormal user.

Abstract: The present disclosure discloses an Internet of Things (IoT) system for industrial data processing, a control method, and a storage medium, and provides a technical solution for a timely adjustment of production line parameters according to image information generated during a machine vision data collection on the production line. Through a difference of the image information corresponding to different process operations, a processing situation of different process operations may be obtained, so that more accurate adjustment of the production line parameter may be achieved without increasing the system complexity, thereby effectively reducing a development cost of the IoT, and increasing accuracy of the intelligent manufacturing control.

Abstract: The present disclosure provides an Industrial Internet of Things for implementing a production task plan, including at least one user platform, a service platform, a management platform, a sensor network platform, and one or more object platforms that are interacted sequentially from top to bottom; the service platform is arranged in an independent layout, the management platform is arranged in a front sub platform layout, and the sensor network platform is arranged in a rear sub platform layout; the one or more object platforms are configured as one or more intelligent manufacturing devices or one or more manufacturing management devices.

Abstract: The embodiments of the present disclosure provide a method for safety management of a compressor in a smart gas pipeline network and an Internet of Things system thereof. The method is implemented based on a smart gas safety management platform of an Internet of Things system for safety management of a compressor in a smart gas pipeline network. The method comprises: obtaining sound data and a target vibration feature of a gas compressor, and determining a target sound feature based on the sound data; obtaining gas data and device data, and determining a standard sound feature and a standard vibration feature based on the gas data and the device data; and predicting whether there is a safety hazard in the gas compressor based on the target vibration feature and the standard vibration feature, or based on the target sound feature and the standard sound feature.

Abstract: The present disclosure provides an Industrial Internet of Things, a control method and storage medium for sheet workpiece processing. The Industrial Internet of Things includes a detecting module and a processing module; the detecting module is configured to detect a machining process of a sheet workpiece to obtain detection information; and the processing module is configured to adjust a production device based on the detection information. By detecting and adjusting a sheet workpiece, on the one hand, the present disclosure can effectively improve the subsequent processing accuracy of the sheet workpiece, on the other hand, the present disclosure can simplify an adjustment process and improve the adjustment efficiency of a bearing mechanism of a target sheet workpiece.

Abstract: Embodiments of the present disclosure provide a method for graph-based smart gas data management and an Internet of Things system. The method includes: obtaining gas data and source characteristics corresponding to the gas data from a predetermined knowledge graph; dividing the gas data based on the source characteristics to determine one or more sets of sub-gas data; determining a processing priority of the sub-gas data based on at least one of a degree of data anomaly and a degree of data completeness of the sub-gas data; determining a resource allocation strategy for computing resources and a processing strategy for the sub-gas data based on the processing priority of the one or more sets of sub-gas data; the processing strategy including a processing algorithm and the computing resources; and the processing algorithm including at least one of a data normalization algorithm, an outlier detection algorithm, and a data quality analysis algorithm.

Abstract: The embodiment of the present disclosure provides a method for smart gas personalized feedback service and an Internet of things (IoT) system thereof. The method is implemented based on a smart gas management platform. The method includes: receiving a call message of a target customer through a call center, and a content of the call message being related to a gas business; determining a service category corresponding to the call message based on the call message, and determining a feedback mode; in response to the feedback mode being manual feedback, determining a target operator through the call center to feed back a call of the target customer; and in response to the feedback mode being automatic feedback, determining, using a knowledge map, a feedback content through the call center based on the service category corresponding to the call message, and sending the feedback content to the target customer.

Abstract: The embodiments of the present disclosure provide methods and systems for natural gas data computation outside a gas IoT based on energy measuring, including establishing the gas IoT. The object platform obtains consumed gas volume data and location data of the smart gas meter as first data and second data, and sending them to the management platform through the sensor network platform. The management platform generates consumed gas preprocessing data based on the first data and the second data, and generates energy measurement data after performing the computation outside the gas IoT on the consumed gas preprocessing data by the cloud platform outside the gas IoT. The management platform sends the energy measurement data to the user platform configured in a regional pipeline network center through the service platform. The user platform performs gas energy measurement of the smart gas meter based on the energy measurement data.

Abstract: The present disclosure provides a method for smart gas pipeline life prediction based on safety. The method includes: obtaining the operation information of the target gas pipeline section within the first time period; determining, based on operation information, the first performance parameter of the target gas pipeline section of at least one moment within the first time period, the first performance parameter including at least the transport performance of the target gas pipeline section within the first time period; determining, based on the first performance parameter of at least one moment, the first performance parameter sequence of the target gas pipeline section within the first time period, the first performance parameter sequence being the sequence obtained by arranging the first performance parameters of at least one moment in chronological order; and determining, based on the first performance parameter sequence, the remaining life of the target gas pipeline section.

Abstract: A method and an Internet of Things (IoT) system for an industrial gas demand regulation based on a smart gas. The method includes: obtaining gas data and a user feature of at least one industrial user, the gas data including gas operation data and gas demand data of the at least one industrial user; determining, based on the gas data, the user feature, and an external feature, an estimated usage distribution; sending the estimated usage distribution to a smart gas user platform to obtain feedback data from the at least one industrial user; determining, based on the feedback data and the estimated usage distribution, an updated usage distribution; and determining, based on the updated usage distribution, a gas regulation program, the gas regulation program including at least one of a gas transmission volume and a gas storage volume between a region where the at least one industrial user is located.

Abstract: The present disclosure provides an industrial Internet of Things comprising a user platform, a service platform, and a management platform, wherein the management platform is configured to perform the following operations including: in response to receiving a second instruction from the service platform, determining whether a moving force of an automatic stacker satisfies the execution condition, the second instruction is determined by the service platform based on a first instruction sent by the user platform, and the first instruction includes a goods retrieval instruction; controlling the automatic stacker to execute a pick-and-place operation in response to the moving force of the automatic stacker satisfying the execution condition; and in response to the automatic stacker completing the pick-and-place operation, determining a target standby position and controlling the automatic stacker to move to the target standby position.