Internet-of-things data correction processing method and system based on Internet-of-things platform

Abstract

The invention provides an internet-of-things data correction processing method and system based on an internet-of-things platform, and belongs to the technical field of data processing. The updating data matching module is responsible for determining the composition data of the updated Internet of Things monitoring data in different historical fault times in the region, and the updating region determining module is responsible for determining the composition data of the updated Internet of Things monitoring data in the different historical fault times in the region on the basis of the composition data of the updated Internet of Things monitoring data in the different historical fault times in the region. And the update target area in the area is determined, so that the security of Internet of Things data correction processing is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and particularly relates to an Internet of Things data correction processing method and system based on an Internet of Things platform. Background Art

[0002] In order to achieve real-time monitoring and processing of the power grid, power enterprises have established an Internet of Things platform for unified supervision of Internet of Things devices in the power grid system. However, at the same time, the Internet of Things platform lacks technical means for data standard control and does not manage the data standards of each specialty. Maintenance personnel can only check and correct data normativity through offline document verification, making it difficult to ensure the reliability and accuracy of Internet of Things data.

[0003] In order to improve the data reliability of the Internet of Things platform, in the invention patent application CN202010949123.5, "A method for improving data quality of a process-based processing mechanism", by setting data quality improvement goals and processing the acquired data according to a set data quality improvement process, the efficiency and objectivity of data quality improvement can be improved. However, there are the following technical problems: In the process of correcting and processing Internet of Things data, there are non-standard problems in data standard information such as device naming, location, region, specialty, affiliated unit, model, manufacturer, version, and description of Internet of Things monitoring data in the current Internet of Things platform. Therefore, how to screen the target area for update according to the impact of the update on the fault monitoring of the distribution network area after update processing in different distribution network areas, so as to avoid the impact on the monitoring of the distribution network when there are update defects after updating all areas has become an urgent technical problem to be solved.

[0004] To solve the above technical problems, the present application provides an Internet of Things data correction processing method and system based on an Internet of Things platform. Summary of the Invention

[0005] To achieve the object of the present invention, the present invention adopts the following technical solutions: In a first aspect, the present application provides an Internet of Things data correction processing system based on an Internet of Things platform, specifically including: A fault data acquisition module, an update data matching module, and an update area determination module; Wherein the fault data acquisition module is responsible for acquiring historical fault data of different regions; The update data matching module is responsible for determining the constituent data of the updated Internet of Things monitoring data among different historical fault times in the region; The update area determination module is responsible for determining the update target area in the area based on the constituent data of the IoT monitoring data updated in different historical failure times in the area, and first performing the update processing of the IoT monitoring data of the IoT platform in the update target area.

[0006] A further technical solution lies in that the constituent data of the IoT monitoring data updated in the historical failure times includes the quantity of the updated IoT monitoring data in the IoT monitoring data with alarms in the historical failure times.

[0007] A further technical solution lies in that the method for determining the update target area in the area is as follows: Based on the constituent data of the IoT monitoring data updated in different historical failure times in the area, determine the proportion of the quantity of the updated IoT monitoring data in the IoT monitoring data with alarms in different historical failure times, and use it as the update quantity proportion; Based on the average value of the update quantity proportions in different historical failure times, determine whether the area is an update target area.

[0008] A further technical solution lies in that when the average value of the update quantity proportions in different historical failure times is greater than the preset update quantity proportion threshold, it is determined that the area is an update target area.

[0009] In the second aspect, the present application provides an IoT data correction processing method based on an IoT platform, which is applied to the above-mentioned IoT data correction processing system based on an IoT platform, and specifically includes: S1 Divide the IoT devices of the IoT platform into multiple areas, and determine the target area and the update matching coefficient in the area based on the similarity between the types and manufacturers of the IoT devices in the area and other areas; S2 Based on the constituent data of the IoT monitoring data updated in different historical failure times in different target areas, determine the update target area in the target area; S3 Freely combine the update target areas to form multiple target area groups, and determine the update area group in the target area group based on the distribution interval distance between the update target areas of different target area groups and other areas; S4 Determine the update processing order of the IoT monitoring data of different update target areas in the update area group based on the update matching coefficient, and determine the update processing method of the IoT monitoring data of the IoT platform of different update target areas based on the similarity between the update target area and the previous update target area and the recognition result of the update defect data.

[0010] The beneficial effects of the present invention are as follows: Determine the updated area group in the target area group based on the distribution interval distance between the updated target areas of different target area groups and other areas. Fully consider the reliability of the results of the updated target areas after data update processing caused by the distribution interval distance between the updated target areas and other areas, avoid the situation where the updated target areas are too concentrated and cannot accurately reflect the anomalies in data update caused by environmental data deviations, and ensure the reliability of the update processing.

[0011] Determine the update processing method for the Internet of Things monitoring data of different updated target areas based on the similarity between the updated target areas and the previous updated target areas and the recognition results of update defect data. Not only consider the difference in the reference degree of the update processing data of the previous updated target areas caused by the similarity between the updated target areas and the previous updated target areas, but also consider the difference in the probability of defects occurring in the updated target areas caused by the difference in update defect data, and then generate a differentiated update processing method, which not only ensures the reliability of the update processing, but also reduces the impact degree on the monitoring reliability of the power equipment in the updated target areas when there are update deviations.

[0012] A further technical solution is to divide the Internet of Things devices of the Internet of Things platform into multiple areas, specifically including: Based on the location where the Internet of Things device is located, divide the Internet of Things device into the corresponding area according to the area where the location is located.

[0013] A further technical solution is that the types of the Internet of Things devices include sensing and measuring devices, control and execution devices, and communication network devices.

[0014] A further technical solution is that the method for determining the target area in the area is: Based on the similarity between the types and manufacturers of the Internet of Things devices in the area and other areas, determine the Internet of Things devices of the same manufacturer and type, and use them as the same devices; According to the proportion of the number of the same devices in other areas, determine the device matching coefficient between the area and other areas; Determine the update matching coefficient based on the average value of the device matching coefficients between the area and other areas, and determine whether the area is a target area based on the update matching coefficient.

[0015] A further technical solution is that the value range of the update matching coefficient is between 0 and 1. When the update matching coefficient is greater than the preset matching coefficient threshold, it is determined that the area is a target area.

[0016] A further technical solution lies in that the method for determining the method for updating and processing the Internet of Things monitoring data of the Internet of Things platform in the updated target area is as follows: Based on the similarity between the updated target area and the previous updated target area, determine the number of Internet of Things devices in the updated target area whose device types or manufacturers are inconsistent with those of the previous updated target area, and use it as the number of deviation devices; Based on the recognition result of the update defect data of the previous updated target area, determine the number of update abnormal devices in the previous updated target area; According to the number of update abnormal devices and the number of deviation devices, determine the method for updating and processing the Internet of Things monitoring data of the Internet of Things platform in the updated target area.

[0017] A further technical solution lies in that the update defect data is an Internet of Things device that has an abnormality in communication with the Internet of Things platform or fails in data parsing after the update of data standard information.

[0018] Other features and advantages will be described in the following specification, and, in part, will become apparent from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention are achieved and obtained by the structures specifically pointed out in the specification and the drawings.

[0019] To make the above objectives, features, and advantages of the present invention more obvious and understandable, the following specific preferred embodiments are given, and in conjunction with the accompanying drawings, the detailed description is as follows. Description of the Drawings

[0020] By referring to the accompanying drawings and describing its exemplary embodiments in detail, the above and other features and advantages of the present invention will become more obvious.

[0021] Figure 1 is a flowchart of an Internet of Things data correction and processing system based on an Internet of Things platform; Figure 2 is a flowchart of a method for determining an updated target area in a region; Figure 3 is a flowchart of a method for correcting and processing Internet of Things data based on an Internet of Things platform; Figure 4 is a flowchart of a method for determining a target area in a region. Detailed Embodiments

[0022] Example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in various forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. Like reference numerals in the figures denote like or similar structures, and thus their detailed description will be omitted.

[0023] The terms "a", "an", "the", and "said" are used to denote the presence of one or more elements / components / etc.; the terms "comprising" and "having" are used to mean an open inclusion and mean that there may be additional elements / components / etc. in addition to the listed elements / components / etc.

[0024] Example 1 To solve the above problems, according to one aspect of the present invention, as Figure 1 shown, a thing - to - thing data correction processing system based on an Internet of Things platform is provided, specifically including: A fault data acquisition module, an updated data matching module, and an updated area determination module; Wherein the fault data acquisition module is responsible for acquiring historical fault data of different regions; The updated data matching module is responsible for determining the constituent data of the updated Internet of Things monitoring data among different historical fault counts in the region; The updated area determination module is responsible for determining the updated target area in the region based on the constituent data of the updated Internet of Things monitoring data among different historical fault counts in the region, and first performing the update processing of the Internet of Things monitoring data of the updated target area on the Internet of Things platform.

[0025] Furthermore, the constituent data of the updated Internet of Things monitoring data among the historical fault counts includes the quantity of the updated Internet of Things monitoring data in the Internet of Things monitoring data with alarms among the historical fault counts.

[0026] Specifically, as Figure 2 shown, the method for determining the updated target area in the region is as follows: Based on the constituent data of the updated Internet of Things monitoring data in the region among different historical fault counts, determine the proportion of the quantity of the updated Internet of Things monitoring data in the Internet of Things monitoring data with alarms among different historical fault counts, and use it as the updated quantity proportion; Based on the average value of the updated quantity proportions among different historical fault counts, determine whether the region is an updated target area.

[0027] Further, when the average value of the proportion of the update quantity in different historical failure times is greater than the preset update quantity proportion threshold, it is determined that the area is the update target area.

[0028] Embodiment 2 In a second aspect, as Figure 3 shown, the present application provides an IoT data correction processing method based on an IoT platform, which is applied to the above-mentioned IoT data correction processing system based on an IoT platform, and specifically includes: S1 Divide the IoT devices of the IoT platform into multiple areas, and determine the target area and the update matching coefficient in the area according to the similarity between the types and manufacturers of the IoT devices in the area and other areas; S2 Based on the constituent data of the IoT monitoring data updated in different historical failure times in different target areas, determine the update target area in the target area; S3 Combine the update target areas freely to form multiple target area groups, and determine the update area group in the target area group according to the distribution interval distance between the update target areas of different target area groups and other areas; S4 Determine the update processing order of the IoT monitoring data of different update target areas in the update area group according to the update matching coefficient, and determine the update processing method of the IoT monitoring data of the IoT platform in different update target areas according to the similarity between the update target area and the previous update target area and the recognition result of the update defect data.

[0029] Further, dividing the IoT devices of the IoT platform into multiple areas specifically includes: Based on the location where the IoT device is located, divide the IoT device into the corresponding area according to the area where the location is located.

[0030] It can be understood that the types of the IoT devices include sensing and measurement devices, control and execution devices, and communication network devices.

[0031] Specifically, as Figure 4 shown, the method for determining the target area in the area is: Determine the IoT devices of the same manufacturer and type according to the similarity between the types and manufacturers of the IoT devices in the area and other areas, and use them as the same devices; According to the proportion of the quantity of the same devices in other areas, determine the device matching coefficient between the area and other areas; Determine the update matching coefficient based on the average value of the device matching coefficients between the area and other areas, and determine whether the area is the target area based on the update matching coefficient.

[0032] Further, the value range of the updated matching coefficient is between 0 and 1. When the updated matching coefficient is greater than the preset matching coefficient threshold, the area is determined as the target area.

[0033] Optionally, the method for determining the target area in the area is as follows: Based on the similarity of the types and manufacturers of the Internet of Things devices in the area with other areas, determine the Internet of Things devices with the same manufacturer and type and regard them as the same devices. When the number of the same devices in other areas is less than the preset threshold of the number of the same devices, it is determined that the area does not belong to the target area; When there are other areas where the number of the same devices is not less than the preset threshold of the number of the same devices: According to the proportion of the number of the same devices in other areas, determine the device matching coefficient between the area and other areas. When the device matching coefficients between the area and other areas are all less than the preset device matching coefficient threshold, it is determined that the area does not belong to the target area; When there are other areas where the device matching coefficient is not less than the preset device matching coefficient threshold: Based on the average value of the device matching coefficients between the area and other areas, when it is determined that the average value is not greater than the preset matching coefficient threshold, it is determined that the area does not belong to the target area; When the average value is greater than the preset matching coefficient threshold: Based on the number of other areas where the Internet of Things devices in the area belong to the same devices, determine the update demand coefficient of different Internet of Things devices. When there is no Internet of Things device with an update demand coefficient greater than the preset update demand coefficient threshold, it is determined that the area does not belong to the target area; When there is an Internet of Things device with an update demand coefficient greater than the preset update demand coefficient threshold: Determine the updated matching coefficient based on the device matching coefficient between the area and other areas and the update demand coefficient of different Internet of Things devices, and determine whether the area is the target area based on the updated matching coefficient.

[0034] Further, the method for determining the updated target area in the target area is as follows: Based on the constituent data of the updated Internet of Things monitoring data in different historical failure times in the target area, determine the proportion of the number of the updated Internet of Things monitoring data in the Internet of Things monitoring data with alarms in different historical failure times and regard it as the updated quantity proportion; Based on the updated quantity proportion in different historical failure times, determine the update impact failure times; Determine whether the target area is an update target area based on the number of faults affected by the update.

[0035] Specifically, the number of faults affected by the update is the historical number of faults where the update quantity ratio is greater than the preset quantity ratio.

[0036] It should be noted that determining whether the target area is an update target area based on the number of faults affected by the update specifically includes: When the number of faults affected by the update in the target area is greater than the preset threshold of the number of faults affected by the update, it is determined that the target area does not belong to the update target area.

[0037] Optionally, the method for determining the update target area in the target area is as follows: Obtain the historical number of faults in the target area. When the historical number of faults in the target area does not meet the requirements, it is determined that the target area does not belong to the update target area; When the historical number of faults in the target area meets the requirements: Based on the component data of the Internet of Things monitoring data updated in different historical numbers of faults in the target area, determine the ratio of the number of updated Internet of Things monitoring data in the Internet of Things monitoring data with alarms in different historical numbers of faults, and use it as the update quantity ratio. When the update quantity ratios in different historical numbers of faults are all less than the preset update quantity ratio threshold, it is determined that the target area is the update target area; When there are historical numbers of faults where the update quantity ratio is not less than the preset update quantity ratio threshold: Obtain the historical number of faults where the update quantity ratio is not less than the preset update quantity ratio threshold. When the historical number of faults where the update quantity ratio is not less than the preset update quantity ratio threshold does not meet the requirements, it is determined that the target area does not belong to the update target area; When the historical number of faults where the update quantity ratio is not less than the preset update quantity ratio threshold meets the requirements: Take the historical number of faults where the update quantity ratio is greater than the preset quantity ratio as the number of faults affected by the update. When the number of faults affected by the update does not meet the requirements, it is determined that the target area does not belong to the update target area; When the number of faults affected by the update meets the requirements: Based on the ratio in the historical number of faults where different updated Internet of Things monitoring data exist, determine the fault-affected monitoring data. When the quantity of the fault-affected monitoring data does not meet the requirements, it is determined that the target area does not belong to the update target area; When the quantity of the fault-affected monitoring data meets the requirements: Determine the update impact coefficient of the target area according to the number and proportion of the updated IoT monitoring data in the IoT monitoring data with alarms in different historical failure times, and use the update impact coefficient to determine whether the target area is an update target area.

[0038] Further, when the update impact coefficient of the target area is greater than the preset update impact coefficient threshold, it is determined that the target area does not belong to the update target area.

[0039] Specifically, the method for determining the updated area group in the target area group is as follows: Based on the distribution interval distance between the updated target area in the target area group and other areas, determine the minimum value of the distribution interval distance between the updated target area in the target area group and other areas. The target area group with the minimum value of the distribution interval distance that all meet the requirements with other areas is used as the screened area group. Determine the updated area group in the target area group according to the number of updated target areas in different screened area groups.

[0040] Further, the screened area group is the target area group with the minimum value of the distribution interval distance that is less than the preset distance threshold with other areas.

[0041] It should be noted that the updated area group in the target area group is the screened area group with the least number of updated target areas.

[0042] It can be understood that the previous updated target area is the updated target area where the IoT monitoring data is updated before the updated target area.

[0043] It should be noted that the method for determining the update processing method of the IoT monitoring data of the IoT platform in the updated target area is as follows: Based on the similarity between the updated target area and the previous updated target area, determine the number of IoT devices in the updated target area whose device type or manufacturer is inconsistent with that of the previous updated target area, and use it as the number of deviation devices. Based on the recognition result of the update defect data of the previous updated target area, determine the number of updated abnormal devices in the previous updated target area. Determine the update processing method of the IoT monitoring data of the IoT platform in the updated target area according to the number of updated abnormal devices and the number of deviation devices.

[0044] Further, the update defect data is an IoT device that has an abnormality in communication with the IoT platform or fails in data parsing after the data standard information is updated.

[0045] It can be understood that the method for updating the Internet of Things monitoring data of the Internet of Things platform in the updated target area determined according to the number of updated abnormal devices and the number of deviated devices specifically includes: Taking the sum of the number of updated abnormal devices and the number of deviated devices as the reference number of devices; When the reference number of devices is greater than the preset reference number of devices threshold, only the Internet of Things monitoring data of the Internet of Things devices excluding the deviated devices is taken as the update target, and it is determined whether it is necessary to perform the update processing of the Internet of Things monitoring data of the remaining Internet of Things monitoring devices by using the monitoring data of the update target within a preset time period; When the reference number of devices is not greater than the preset reference number of devices threshold, the Internet of Things monitoring data of all the Internet of Things devices in the updated target area is updated.

[0046] Specifically, the preset time period is determined according to the product of the reference number of devices and the preset proportionality factor.

[0047] Optionally, the method for determining the method for updating the Internet of Things monitoring data of the Internet of Things platform in the updated target area is: S41: Based on the similarity between the updated target area and the previous updated target area, determine the number of Internet of Things devices in the updated target area whose device types or manufacturers are inconsistent with those of the previous updated target area, and take it as the number of deviated devices, and determine the data deviation coefficient based on the number of deviated devices in different previous updated target areas; S42: Based on the identification results of the update defect data in the previous updated target area, determine the number of updated abnormal devices in different previous updated target areas, and determine the update abnormal coefficient based on the number of updated abnormal devices in different previous updated target areas; S43: Determine the update requirement assessment amount according to the data deviation coefficient and the update abnormal coefficient in different previous updated target areas, and use the update requirement assessment amount to determine the method for updating the Internet of Things monitoring data of the Internet of Things platform in the updated target area.

[0048] Furthermore, using the update requirement assessment amount to determine the method for updating the Internet of Things monitoring data of the Internet of Things platform in the updated target area specifically includes: When the update requirement assessment amount is greater than the preset requirement assessment amount threshold, only the Internet of Things monitoring data of the Internet of Things devices excluding the deviated devices is taken as the update target, and it is determined whether it is necessary to perform the update processing of the Internet of Things monitoring data of the remaining Internet of Things monitoring devices by using the monitoring data of the update target within a preset time period; When the updated requirement assessment quantity is not greater than the preset requirement assessment quantity threshold, the Internet of Things monitoring data of all Internet of Things devices in the updated target area is updated.

[0049] Optionally, the above step S41 includes the following content: S411 determines the quantity of Internet of Things devices in the updated target area whose device types or manufacturers are inconsistent with those of the previous updated target area based on the similarity between the updated target area and the previous updated target area, and takes it as the deviation device quantity. When the deviation device quantity does not meet the requirements, only the Internet of Things monitoring data of the Internet of Things devices excluding the deviation devices is taken as the update target, and it is determined whether to update the Internet of Things monitoring data of the remaining Internet of Things monitoring devices using the monitoring data of the update target within a preset time period. When the deviation device quantity meets the requirements, step S412 is entered; S412 determines the data deviation coefficient based on the deviation device quantities of different previous updated target areas. When the data deviation coefficients of different previous updated target areas are all within the preset deviation coefficient range, step S413 is entered. When there is a previous updated target area where the data deviation coefficient is not within the preset deviation coefficient range, step S42 is entered; S413 When the minimum value of the data deviation coefficient of the previous updated target area is less than the preset deviation coefficient threshold, step S42 is entered. When the minimum value of the data deviation coefficient of the previous updated target area is not less than the preset deviation coefficient threshold, only the Internet of Things monitoring data of the Internet of Things devices excluding the deviation devices is taken as the update target, and it is determined whether to update the Internet of Things monitoring data of the remaining Internet of Things monitoring devices using the monitoring data of the update target within a preset time period.

[0050] Optionally, the above step S42 includes the following content: S421 determines the quantity of updated abnormal devices in different previous updated target areas based on the identification results of the updated defect data of the previous updated target area. When the sum of the quantities of updated abnormal devices in different previous updated target areas does not meet the requirements, only the Internet of Things monitoring data of the Internet of Things devices excluding the deviation devices is taken as the update target, and it is determined whether to update the Internet of Things monitoring data of the remaining Internet of Things monitoring devices using the monitoring data of the update target within a preset time period. When the sum of the quantities of updated abnormal devices in different previous updated target areas meets the requirements, step S422 is entered; S422 determines an update anomaly coefficient based on the number of update anomaly devices in the update target areas of different previous periods. When the update anomaly coefficients of the update target areas in different previous periods all meet the requirements, the IoT monitoring data of all the IoT devices in the update target area is updated. When there is an update target area in a previous period where the update anomaly coefficient does not meet the requirements, it proceeds to step S423; S423 When the number of update target areas in a previous period where the update anomaly coefficient does not meet the requirements is greater than the preset update area number threshold, only the IoT monitoring data of the IoT devices excluding the deviation devices is used as the update target, and it is determined whether to update the IoT monitoring data of the remaining IoT monitoring devices using the monitoring data of the update target within a preset duration. When the number of update target areas in a previous period where the update anomaly coefficient does not meet the requirements is not greater than the preset update area number threshold, it proceeds to step S424; S424 Obtain the data deviation coefficient between the update target area in a previous period where the update anomaly coefficient does not meet the requirements and the update target area. When there is an update target area in a previous period where the update anomaly coefficient does not meet the requirements and the data deviation coefficient from the update target area is less than the preset data deviation coefficient threshold, only the IoT monitoring data of the IoT devices excluding the deviation devices is used as the update target, and it is determined whether to update the IoT monitoring data of the remaining IoT monitoring devices using the monitoring data of the update target within a preset duration. When there is no update target area in a previous period where the update anomaly coefficient does not meet the requirements and the data deviation coefficient from the update target area is less than the preset data deviation coefficient threshold, it proceeds to step S43.

[0051] Each embodiment in this specification is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the embodiments of the device, equipment, and non - volatile computer storage medium, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiments.

[0052] The above describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be executed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0053] The above description is only for one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, various changes and modifications can be made to one or more embodiments of this specification. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included within the scope of the claims of this specification.

Claims

1. An Internet of Things data correction and processing system based on an Internet of Things platform, characterized in that, Specifically include: Fault data acquisition module, updated data matching module, updated area determination module; Among them, the fault data acquisition module is responsible for acquiring historical fault data in different regions; The updated data matching module is responsible for determining the constituent data of the updated Internet of Things monitoring data among different historical fault counts in the region; The updated area determination module is responsible for determining the updated target area in the region based on the constituent data of the updated Internet of Things monitoring data among different historical fault counts in the region, and first performing the update processing of the Internet of Things monitoring data of the Internet of Things platform in the updated target area.

2. The IoT data correction and processing system based on the IoT platform according to claim 1, wherein The constituent data of the updated Internet of Things monitoring data among the historical fault counts includes the quantity of the updated Internet of Things monitoring data in the Internet of Things monitoring data with alarms among the historical fault counts.

3. The Internet of Things data correction and processing system based on the Internet of Things platform according to claim 1, characterized in that The method for determining the updated target area in the region is as follows: Based on the constituent data of the updated Internet of Things monitoring data in different historical fault counts in the region, determine the proportion of the quantity of the updated Internet of Things monitoring data in the Internet of Things monitoring data with alarms among different historical fault counts, and use it as the updated quantity proportion; Based on the average value of the updated quantity proportions in different historical fault counts, determine whether the region is an updated target area.

4. The IoT data correction processing system based on the IoT platform according to claim 3, characterized in that, When the average value of the updated quantity proportions in different historical fault counts is greater than the preset updated quantity proportion threshold, it is determined that the region is an updated target area.

5. A method for correcting and processing Internet of Things data based on an Internet of Things platform, which is applied to an Internet of Things data correction and processing system according to any one of claims 1-4, and is characterized in that, Specifically include: Divide the Internet of Things devices of the Internet of Things platform into multiple regions, and determine the target area and the updated matching coefficient in the region based on the similarity of the types and manufacturers of the Internet of Things devices in the region to those in other regions; Based on the constituent data of the updated Internet of Things monitoring data in different historical fault counts in different target areas, determine the updated target area in the target area; Freely combine the updated target areas to form multiple target area groups, and determine the updated area group in the target area group based on the distribution interval distance between the updated target areas of different target area groups and other regions; Determine the update processing order of the Internet of Things monitoring data of different updated target areas in the updated area group based on the updated matching coefficient, and determine the update processing method of the Internet of Things monitoring data of the Internet of Things platform of different updated target areas based on the similarity of the updated target area to the previous updated target area and the recognition result of the updated defect data.

6. The method for correcting and processing IoT data based on an IoT platform according to claim 5, wherein Dividing the Internet of Things devices of the Internet of Things platform into multiple regions specifically includes: Based on the location where the Internet of Things device is located, divide the Internet of Things device into the corresponding region according to the region where the location is located.

7. The method for correcting and processing IoT data based on an IoT platform according to claim 5, wherein The types of the Internet of Things devices include sensing and measuring devices, control and execution devices, and communication network devices.

8. The method for correcting and processing IoT data based on an IoT platform according to claim 5, characterized in that, The method for determining the target area in the region is as follows: Based on the similarity of the types and manufacturers of the Internet of Things devices in the region to those in other regions, determine the Internet of Things devices of the same manufacturer and type, and use them as the same devices; Determine the device matching coefficient between the area and other areas according to the proportion of the number of the same devices in other areas; Determine the updated matching coefficient based on the average value of the device matching coefficients between the area and other areas, and determine whether the area is a target area based on the updated matching coefficient.

9. The method for correcting and processing IoT data based on an IoT platform according to claim 5, wherein The value range of the updated matching coefficient is between 0 and 1. When the updated matching coefficient is greater than the preset matching coefficient threshold, the area is determined to be a target area.

10. The method for correcting and processing IoT data based on an IoT platform according to claim 5, wherein, The method for determining the update processing method of the Internet of Things monitoring data of the updated target area's Internet of Things platform is as follows: Determine the number of Internet of Things devices in the updated target area whose device type or manufacturer is inconsistent with that of the previous updated target area based on the similarity between the updated target area and the previous updated target area, and use it as the number of deviation devices; Determine the number of updated abnormal devices in the previous updated target area based on the recognition result of the update defect data of the previous updated target area; Determine the update processing method of the Internet of Things monitoring data of the updated target area's Internet of Things platform according to the number of updated abnormal devices and the number of deviation devices.

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