Abstract: The embodiments of the present disclosure provide methods and systems for energy measuring based on natural gas data of a smart gas meter, 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 embodiment of the present disclosure provides a method for pipeline network inspection zone generation based on smart gas and an Internet of Things system thereof. The method is implemented based on the Internet of Things system. The Internet of Things system includes a smart gas pipeline network safety management platform, a smart gas sensor network platform, and a smart gas object platform which interact in turn. The method includes: obtaining area feature information of a target inspection area of a gas network based on the smart gas object platform through the smart gas sensor network platform; generating one or more key inspection points in the target inspection area based on the area feature information of the target inspection area; and generating one or more inspection zones in the target inspection area based on the one or more key inspection points.

Abstract: The embodiment of the present disclosure provides an Industrial Internet of Things system for inspection operation management of an inspection robot and a method thereof. The system includes a user platform, a service platform, a management platform, a sensor network platform, and an object platform that are interacted sequentially from top to bottom. The management platform is configured to perform operations including: determining an inspection task, the inspection task including detecting at least one detection site; sending instructions to an inspection robot based on the inspection task to move the inspection robot to a target position to be inspected; obtaining detection data based on the inspection robot, and determining subsequent detection or processing operations based on the detection data.

Abstract: An industrial internet of things system for intelligent production control is provided, comprising: a user platform, a service platform, a management platform, a sensor network platform, and an object platform. The user platform modifies production line parameters based on an instruction of the user, generates a first instruction, and sends it to the management platform through the transformation of the service platform. The object platform collects production link data of each production link of products and transmits it to the management platform. The management platform modifies work order parameters based on a second instruction transformed by the service platform, generates a third instruction, and determines whether devices corresponding to the plurality of production links are abnormal based on the production link data.

Abstract: The embodiments of the present disclosure provide a method and smart gas Internet of Things (IoT) system for determining a gas abnormity for a safe gas use. The method is implemented by a smart gas IoT system including a smart gas user platform, a smart gas service platform, a smart gas safety management platform, a smart gas indoor device sensing network platform, and a smart gas indoor device object platform. The method is performed by the smart gas safety management platform, including: receiving request information of a target user, the request information including a request of the target user for analyzing a gas abnormity cause; extracting user data based on the request information, and extracting gas data based on the user data; and determining, based on the user data and the gas data, analysis information of the gas abnormity cause.

Abstract: The present disclosure provides a method for smart gas pipeline transportation performance prediction. The method includes: determining, based on a gas pipeline map, transportation performance of a target gas pipeline section by a transportation performance determination model, wherein the gas pipeline map reflects a connection relationship of a plurality of gas pipeline sections within a preset range of the target gas pipeline section, and the gas pipeline map is generated based on information of one or more historical gas pipeline sections; nodes of the gas pipeline map include connections between the gas pipeline sections, gas storage points, gate stations, or pipeline bends, and edges of the gas pipeline map include the gas pipeline sections; a node feature of the gas pipeline map includes whether to process gas, an edge feature of the gas pipeline map includes pipeline parameters and a pipeline maintenance situation.

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 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 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: The disclosure provides an Internet of Things system and a method for managing a people flow of a public place in a smart city. The method may comprise obtaining pedestrian distribution information in a preset area during a current time period via network from a storage device; determining, by processing the pedestrian distribution information through an area location prediction model, at least one area location in the preset area for a future time period, a population flow load of the area location being greater than a first threshold, wherein the area location prediction model includes a graph neural network model, a graph input into the graph neural network model includes at least two nodes and at least one edge; generating, based on the area location, prompt information; and feedbacking the prompt information to a user terminal of a user platform through a service platform via the network.

Abstract: The present disclosure provides a method and a system for determining a maintenance time of a pipe network of natural gas. The method may comprise: obtaining pipe network information of natural gas in at least one area, the pipe network information including a running time of the system and gas leakage information of the pipe network; extracting feature information based on the running time and the gas leakage information; generating a pipe network maintenance value through a maintenance value prediction model based on pipe network maintenance information and pipe network environment information, the pipe network maintenance value reflecting a priority of pipe network maintenance processing; and predicting the maintenance time of the pipe network based on the feature information and the pipe network maintenance value using a maintenance time prediction model, the maintenance time prediction model being a machine learning model.

Abstract: The present disclosure provides an Industrial Internet of Things system conducive to system function expansion and system adjustment and control method thereof. The system comprises a user platform, a service platform, a management platform, a sensor network platform, and an object platform. The service platform and the sensor network platform adopt independent layout, and the management platform adopts centralized layout. The management platform is configured to store a control program that drives operation of production line equipment. The management platform is configured to call the control parameters in the database through communicating with the service platform and configure the control parameters in the control program to control the operation of production line equipment; and a data interaction mode between the user platform and the service platform is modifying and deleting the control parameters in the service platform through data transmission between the user platform and the service platform.

Abstract: The embodiments of the present disclosure provide method and Internet of Things system for determining odorization parameters of smart gas device management. The method may include obtaining gas data of a first gas sample at a first position of a smart gas pipeline network, odorizing at a second position of the smart gas pipeline network based on the odorization parameters, obtaining inspection data of a second gas sample at a third position of the smart gas pipeline network, and sending the inspection data to the smart gas pipeline network device parameter management sub-platform for analysis and processing, obtaining a target odorization concentration, and determining target odorization parameters, updating the odorization parameters based on the target odorization parameters, and send updated odorization parameters to the smart gas data center, and odorizing, based on the updated odorization parameters, at the second position of the smart gas pipeline network.

Abstract: The present disclosure discloses an Industrial Internet of Things, a control method, and a medium for automatically controlling working parameters of a manufacturing device.

Abstract: The present disclosure provides an Industrial Internet of Things of an independent service platform and a control method. The method is applied to a user platform, a service platform, a management platform, a sensor network platform and an object platform that interact in sequence. The method includes receiving a monitoring value from at least one timer through the sensor network platform; according to the data source of the monitoring value, distributing the monitoring value to the corresponding service sub-platform of the service platform, which is configured to use different service sub-platforms for storage, data processing and/or data transmission for different types of data, different service sub-platforms corresponding to independent databases, processors, and information channels; and sending the data processing results to the user platform for displaying to a user based on the corresponding information channels in the service platform.

Abstract: The present disclosure relates to an Industrial Internet of Things (IoT) system for controlling a production line parameter and a control method thereof. The Industrial IoT system includes an user platform, a service platform, a management platform, a sensor network platform, and an object platform interacting in sequence, the service platform adopts a centralized arrangement, the management platform adopts an independent arrangement, and the sensor network platform adopts a rear sub-platform arrangement.

Abstract: The present disclosure discloses an Industrial Internet of Things (IIoT) system for automatic control of production line manufacturing parameters, which comprises a user platform, a service platform, a management platform, a sensor network platform and an object platform that interact in turn. The service platform adopts centralized layout, and the management platform and the sensor network platform adopt independent layout. The present disclosure also discloses a control method of the IIoT for automatic control of production line manufacturing parameters.

Abstract: The embodiments of the present disclosure provide a method and an Internet of Things (IoT) system for managing dust pollution in a smart city. The method may be executed by a management platform, the method may include: obtaining one or more environmental data of the area to be detected through the sensing network platform, and obtaining one or more street data associated with the environmental data, the environmental data at least including dust data indicating dust information in the air; determining whether there is dust pollution in the area to be detected based on the environmental data; and in response to the determining that there is dust pollution in the area to be detected, determining a position of at least one dust pollution source based on the environmental data and the street data, and treating the dust pollution.