Cloud data cleaning method and device, storage medium and cloud server

Abstract

This application discloses a cloud data cleanup method, apparatus, storage medium, and cloud server. When offline devices are detected in a device group, the method determines the first and second device information of all devices in the device group. Based on the first and second device information, it determines whether all offline devices are invalid devices. If so, it clears the invalid device data corresponding to each invalid device. Since the cloud server records all connected devices, and the actual devices in the device group may be modified or deleted, when offline devices are present, by comparing the actual information in the device group with the device information recorded in the cloud server, it is possible to accurately determine whether all offline devices are invalid devices, and further directly clean up the invalid device data of invalid devices. This achieves automatic calibration of the accuracy of device information in the cloud server, reduces the cost of manual inspection and correction, and facilitates the subsequent use of the device group in the Internet of Things.

Description

Technical Field

[0001] This application relates to the field of Internet of Things (IoT) control technology, and in particular to a cloud data cleaning method, apparatus, storage medium, and cloud server. Background Technology

[0002] With the development of IoT technology, various common machines and devices can receive and respond to commands through IoT network access, enabling users to easily control multiple devices centrally via the network. However, since device information is cached on cloud servers after a device has been connected to a centralized control system, and cloud servers do not clean up this information, some expired device information remains on the cloud servers. Therefore, to ensure the correctness and accuracy of device information in the cloud, a cloud data cleanup method is needed to promptly remove invalid device information. Summary of the Invention

[0003] This application provides a cloud data cleaning method, apparatus, storage medium, and cloud server, which can solve the technical problems of redundant invalid data and inaccurate device information in the cloud in related technologies.

[0004] In a first aspect, embodiments of this application provide a cloud data cleaning method applied to a cloud server, the method comprising:

[0005] When at least one offline device is detected in the equipment group, the first device information and the second device information of all devices in the equipment group are determined. The first device information is the actual connection information of all devices in the equipment group, and the second device information is the address identification information of all devices recorded in the cloud server.

[0006] Based on the first device information and the second device information, determine whether all offline devices are invalid devices;

[0007] If all offline devices are invalid devices, then clear the invalid device data corresponding to each invalid device.

[0008] Secondly, embodiments of this application provide a cloud data cleaning device applied to a cloud server, the device comprising:

[0009] The status monitoring module is used to determine the first device information and the second device information of all devices in the equipment group when at least one offline device is detected in the equipment group. The first device information is the actual connection information of all devices in the equipment group, and the second device information is the address identification information of all devices recorded in the cloud server.

[0010] The equipment verification module is used to determine whether all offline devices are invalid devices based on the first device information and the second device information;

[0011] The data cleaning module is used to clear the invalid device data corresponding to each invalid device if all offline devices are invalid devices.

[0012] Thirdly, embodiments of this application provide a computer storage medium storing a plurality of instructions adapted for loading by a processor and executing the steps of the method described above.

[0013] Fourthly, embodiments of this application provide a cloud server, including a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being adapted to be loaded by the processor and to execute the steps of the above-described method.

[0014] The beneficial effects of the technical solutions provided in some embodiments of this application include at least the following:

[0015] This application provides a cloud data cleanup method applied to a cloud server. When at least one offline device is detected in a device group, the method determines first device information and second device information for all devices in the device group. The first device information is the actual connection information of all devices in the device group, and the second device information is the address identification information of all devices recorded in the cloud server. Based on the first and second device information, it is determined whether all offline devices are invalid devices. If all offline devices are invalid devices, the invalid device data corresponding to each invalid device is cleared. Since the cloud server records the address information of all connected devices, and the actual devices in the device group may be modified or deleted, when the cloud server detects offline devices, by comparing the actual connection information in the device group with the device address information recorded in the cloud server, it can accurately determine whether the offline devices are invalid devices in the actual scenario, and further directly clean up the invalid device data of invalid devices in the cloud server. This achieves automatic calibration of the accuracy of device information in the cloud server, reduces the cost of manual inspection and correction, and facilitates the subsequent use of the device group in the Internet of Things. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1An exemplary system architecture diagram of a cloud-based data cleaning method provided in this application embodiment;

[0018] Figure 2 A network logic diagram of a multi-split air conditioning unit provided in this application embodiment;

[0019] Figure 3 A flowchart illustrating a cloud-based data cleaning method provided in this application embodiment;

[0020] Figure 4 A flowchart illustrating a cloud-based data cleaning method provided in this application embodiment;

[0021] Figure 5 This application provides an implementation logic flowchart for a cloud-based data cleaning method.

[0022] Figure 6 A flowchart illustrating a cloud-based data cleaning method provided in this application embodiment;

[0023] Figure 7 A structural block diagram of a cloud data cleaning device provided in an embodiment of this application;

[0024] Figure 8 This is a schematic diagram of the structure of a cloud server provided in an embodiment of this application. Detailed Implementation

[0025] To make the features and advantages of this application more apparent and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] In the following description, when referring to the accompanying drawings, the same numbers in different drawings denote the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0027] In recent years, with the development of IoT technology, various common machines and devices can receive and respond to commands through IoT network access, enabling users to easily control multiple devices in a unified and centralized manner via the network. For example, among various IoT scenarios, the home scenario is one of the most common application scenarios. In smart home scenarios, IoT technology connects various devices in the user's home, including audio-visual equipment, lighting equipment, curtain equipment, air conditioning equipment, security equipment, digital cinema equipment, network equipment, and so on, providing a variety of functions and means such as appliance control, lighting control, terminal remote control, indoor and outdoor remote control, burglar alarms, environmental monitoring, and HVAC control. Moreover, with the development of technology, the types of smart devices are becoming increasingly diverse.

[0028] When centrally controlling IoT device units, the operational data of the unit is typically uploaded to a cloud server for real-time monitoring or centralized control. Currently, cloud server configurations primarily utilize caching technology. This means that once a device has been connected to the centralized control system and recognized by the cloud server, its information is cached there. Since the cloud server doesn't actively clean up this information, some device information remains even after it has expired. For example, information about devices that have been used but removed from the system, or devices whose information has been modified, will persist, resulting in redundant and inefficient information on the cloud server. Furthermore, when the device information on the cloud server doesn't match the actual situation, technicians may be misled by inaccurate information when debugging and repairing IoT devices based on cloud server data. This can lead to misunderstandings about the current state of the IoT devices and hinder technicians' work efficiency.

[0029] Therefore, this application provides a cloud data cleanup method. When at least one offline device is detected in a device group, the method determines the first device information and the second device information of all devices in the device group. The first device information is the actual connection information of all devices in the device group, and the second device information is the address identification information of all devices recorded in the cloud server. Based on the first device information and the second device information, the method determines whether all offline devices are invalid devices. If all offline devices are invalid devices, the invalid device data corresponding to each invalid device is cleared to solve the above-mentioned technical problems of redundant invalid data and inaccurate device information in the cloud.

[0030] Please see Figure 1 , Figure 1 This is an exemplary system architecture diagram of a cloud-based data cleaning method provided in an embodiment of this application.

[0031] like Figure 1As shown, the system architecture may include a cloud server 101, a network 102, and an IoT device group 103. The network 102 serves as the medium for providing a communication link between the cloud server 101 and the IoT device group 103. The network 102 may include various types of wired or wireless communication links, such as wired communication links including fiber optic cables, twisted-pair cables, or coaxial cables, and wireless communication links including Bluetooth communication links, Wireless-Fidelity (Wi-Fi) communication links, or microwave communication links, etc.

[0032] Cloud server 101 can interact with IoT device group 103 via network 102 to receive or send messages to IoT device group 103. Alternatively, cloud server 101 can interact with IoT device group 103 via network 102 to receive messages or data sent to IoT device group 103 by other users. Cloud server 101 can be a business server providing various services. It should be noted that cloud server 101 can be hardware or software. When cloud server 101 is hardware, it can be implemented as a distributed server cluster composed of multiple servers or as a single server. When cloud server 101 is software, it can be implemented as multiple software programs or software modules (e.g., used to provide distributed services) or as a single software program or software module; no specific limitation is made here.

[0033] In this embodiment, when the cloud server 101 detects that at least one offline device exists in the device group, it determines the first device information and the second device information of all devices in the device group. The first device information is the actual connection information in the device group, and the second device information is the address identification information recorded in the cloud server. Then, based on the first device information and the second device information, the cloud server 101 determines whether all offline devices are invalid devices. Finally, if the cloud server 101 determines that all offline devices are invalid devices, it clears the invalid device data corresponding to each invalid device.

[0034] The IoT device unit 103 includes at least two IoT hardware devices, and interacts with the cloud server 101 via network 102. For example, the IoT device unit may include, but is not limited to, a multi-split air conditioning unit, which includes at least one external host, and each external host is connected to at least two internal hosts. Please refer to [link / details] for further information. Figure 2 , Figure 2 This is a schematic diagram illustrating the network logic of a multi-split air conditioning unit, provided as an embodiment of this application. Figure 2As shown, the multi-split air conditioning unit 210 includes a main outdoor unit 2101 and N (N is a positive integer greater than 1) indoor air conditioning units 2102 controlled by the main outdoor unit 2101. The main outdoor unit 2101 can send and receive information from the indoor air conditioning units 2102 via RS485 communication. The main outdoor unit 2101 in the multi-split air conditioning unit 210 is connected to the network module 220 via a communication line, and the network module 220 communicates with the cloud platform 230 via the network. The cloud platform 230 is a platform built on the cloud server 101. The main outdoor unit 2101 can upload the real-time operating information of each indoor air conditioning unit 2102 to the cloud platform 230 through the network module 220, and can send control commands from the cloud platform 230 to each indoor air conditioning unit 2102 to achieve the centralized control effect of multiple IoT devices.

[0035] Alternatively, the system architecture may not include the IoT device unit 103. In other words, the IoT device unit 103 may be an optional device in the embodiments of this specification. That is, the method provided in the embodiments of this specification can be applied to a system structure that only includes the cloud server 101. The embodiments of this application do not limit this.

[0036] It should be understood that Figure 1 The number of cloud servers, networks, and IoT devices shown is only illustrative; the number can be any number of cloud servers, networks, and IoT devices as needed.

[0037] Please see Figure 3 , Figure 3 This is a flowchart illustrating a cloud data cleanup method provided in an embodiment of this application. The execution entity in this embodiment can be a cloud server performing cloud data cleanup, a processor within the cloud server performing the cloud data cleanup method, or a cloud data cleanup service within the cloud server performing the cloud data cleanup method. For ease of description, the following example uses a processor within a cloud server as the execution entity to illustrate the specific execution process of the cloud data cleanup method.

[0038] like Figure 3 As shown, cloud-based data cleaning methods, applied to cloud servers, may include at least:

[0039] S302. When at least one offline device is detected in the equipment unit, determine the first device information and the second device information of all devices in the equipment unit. The first device information is the actual connection information of all devices in the equipment unit, and the second device information is the address identification information of all devices recorded in the cloud server.

[0040] Optionally, since cloud servers record all connected IoT devices but do not clean up invalid device information based on actual device removal or information modification in real-world scenarios, this not only increases the storage burden on cloud servers but also makes the number of devices recorded in the cloud servers inaccurate. Consequently, when technicians perform device debugging and maintenance in real-world scenarios based on the device information recorded in the cloud servers, they are easily influenced by the inaccurate number of devices in the cloud servers, leading to misunderstandings about the status of IoT devices in the current scenario and hindering the work efficiency of technicians.

[0041] Alternatively, for example, in the case of a multi-split air conditioning unit, if the signal cable of the indoor unit is connected incorrectly during installation and commissioning, it may cause an indoor unit originally in the B unit system to be connected to the A unit system and then removed. However, after the indoor unit is connected to the A unit system, it will be assigned a new address by the A unit system. This new address can be directly transmitted to the cloud server corresponding to the A unit system. However, when the incorrectly connected indoor unit is removed, the address identification information of the indoor unit in the cloud server corresponding to the A unit system will not be processed. Similarly, in another scenario, after the A unit system is installed and commissioned, the user may modify or change the original address information of some indoor units in the A unit system through wired / remote control. When the indoor unit has new address identification information, it will be uploaded to the cloud server corresponding to the A unit system, but the original address information of the indoor unit that no longer exists will not be processed.

[0042] Furthermore, considering that situations including but not limited to the examples mentioned above occur frequently in real-world scenarios, the address identification information of devices recorded in the cloud server may not match the actual device situation. Therefore, when it is necessary to determine whether there is invalid device information that can be cleaned up in the address identification information recorded in the cloud server, invalid address identification information that does not correspond to the real device can be determined based on the actual connection information of all devices in the device group and the address identification information of all devices recorded in the cloud server. The device corresponding to the invalid address identification information is the invalid device in the cloud server, thereby enabling automatic cleanup of invalid device data and ensuring the accuracy of device data in the cloud server.

[0043] Optionally, as the cloud server continuously receives and saves device operation data uploaded by IoT device groups, each device is identified by its address identifier in the cloud server. Therefore, the device operation data of each device corresponds to its address identifier. For some devices without address identifiers corresponding to real devices in the actual scenario, no corresponding device operation data will be uploaded for that address identifier. The cloud server will treat devices that have not uploaded device operation data as offline devices. This means that if invalid devices exist, then the invalid device data corresponding to the invalid device must exist among the offline devices.

[0044] Furthermore, in order for the cloud server to automatically clean up invalid device data, the invalid devices corresponding to the invalid device data must first be identified. Since invalid devices must exist among offline devices, the online status of all devices in the IoT device group can be monitored. When at least one offline device is detected in the device group, it is further determined whether all offline devices are invalid devices. If so, the invalid device data corresponding to the invalid device can be cleaned up; otherwise, the status quo can be maintained.

[0045] That is, when offline devices are detected, the first device information and the second device information of all devices in the device group are determined. The first device information is the actual connection information of all devices in the device group, so the first device information can reflect the effective device information actually used in the real device group scenario; the second device information is the address identification information of all devices recorded in the cloud server, so the second device information can reflect the device information of the devices that the cloud server believes exist.

[0046] S304. Based on the first device information and the second device information, determine whether all offline devices are invalid devices.

[0047] Optionally, as can be understood from the above embodiments, the first device information is the actual connection information in the device group, which indicates the valid device information actually used in the real device group scenario; the second device information is the address identification information recorded in the cloud server, which reflects the device information of the devices that the cloud server believes exist. Based on the actual connection information of all devices in the device group and the address identification information of all devices recorded in the cloud server, invalid address identification information that does not correspond to real devices is determined. The devices corresponding to invalid address identification information are invalid devices in the cloud server, thereby enabling automatic cleanup of invalid device data and ensuring the accuracy of device data in the cloud server.

[0048] In this embodiment of the application, based on the first device information and the second device information, specifically based on the actual connection information of the device group and the address identification information of the device group in the cloud server, it is determined whether all offline devices are invalid devices at this time, so as to clear the invalid device data corresponding to the invalid devices after the invalid devices are identified.

[0049] S306. If all offline devices are invalid devices, then clear the invalid device data corresponding to each invalid device.

[0050] Optionally, if the final determination result is that all offline devices are invalid devices, the invalid device data corresponding to the invalid devices can be cleared. The invalid device data includes at least the address identification information recorded by the device in the cloud server, and may also include a series of related information such as the historical device operation data corresponding to the address identification information. Based on the cloud data cleaning method in this application embodiment, the cloud server can automatically identify invalid devices and clear their data after determining them. This achieves automatic calibration of the accuracy of device information in the cloud server, reduces the cost of manual inspection and correction, facilitates the subsequent use of equipment units in the Internet of Things, provides technicians with accurate device information that conforms to real-world scenarios, and improves the efficiency of subsequent operations by technicians.

[0051] This application provides a cloud data cleanup method applied to a cloud server. When at least one offline device is detected in a device group, first device information and second device information for all devices in the device group are determined. The first device information is the actual connection information of all devices in the device group, and the second device information is the address identification information of all devices recorded in the cloud server. Based on the first and second device information, it is determined whether all offline devices are invalid devices. If all offline devices are invalid devices, the invalid device data corresponding to each invalid device is cleared. Since the cloud server records the address information of all connected devices, and the actual devices in the device group may be modified or deleted, when the cloud server detects offline devices, by comparing the actual connection information in the device group with the device address information recorded in the cloud server, it can accurately determine whether the offline devices are invalid devices in the actual scenario, and further directly clean up the invalid device data of invalid devices in the cloud server. This achieves automatic calibration of the accuracy of device information in the cloud server, reduces the cost of manual inspection and correction, and facilitates the subsequent use of the device group in the Internet of Things.

[0052] Please see Figure 4 , Figure 4 This is a flowchart illustrating a cloud-based data cleaning method provided in an embodiment of this application.

[0053] like Figure 4 As shown, cloud-based data cleanup methods can include at least:

[0054] S402: Receive the equipment operation data reported by the equipment unit at a preset frequency for each device, and monitor whether there are offline devices in the equipment unit based on the operation data of each device.

[0055] Optionally, in order to determine whether invalid devices exist, the cloud server first needs to identify offline devices that may be invalid devices based on the online / offline status of all devices in the device group. In order to monitor the operating status of all devices, it can receive the device operating data corresponding to each device reported by the device group at a preset frequency, and monitor whether there are offline devices in the device group based on the operating data of each device.

[0056] Specifically, the preset frequency can be set to five minutes, meaning each device reports its own operating data every five minutes. This operating data includes at least one of the following: device sensor data, device control data, and device status data. Taking a multi-split air conditioning unit as an example, the device sensor data includes data detected by sensors on the outdoor and indoor units (such as ambient temperature and high pressure within the air conditioning system); the device control data includes calculated data obtained by the microcontroller unit (MCU) built into the air conditioning unit (such as exhaust superheat and the real-time capability of the indoor unit); the device status data includes the air conditioning unit's own operating status parameters (such as indoor / outdoor unit operating mode, indoor unit address, set temperature, and indoor unit fan speed); and it may also include data transmitted by external components of the air conditioning unit via the air conditioning unit bus through a network module (such as device power and indoor / outdoor humidity sensor data).

[0057] Furthermore, since each device uploads its own operational data according to a preset cycle, if a device fails to report its own operational data, it indicates that the device may be offline. However, considering that there are many reasons for offline status, such as temporary network lag or disconnection, to reduce false positives for offline devices, the number of consecutive times a target device fails to report data can be recorded. When the number of consecutive failures reaches a certain threshold, the device is considered offline. In other words, when monitoring the presence of offline devices in a device group based on the operational data of each device, if a target device without operational data is detected, the number of consecutive failures to report is recorded; if the number of consecutive failures meets a preset threshold, the target device is marked as offline.

[0058] The preset consecutive number threshold can be set according to actual needs. For example, when applied to some older devices, short-term offline situations may occur more easily. In this case, if the preset frequency of device data reporting is five minutes, the preset consecutive number threshold can be set to eight times. When the target device that is offline fails to report device operation data for eight consecutive times, that is, forty minutes, the target device will be marked as an offline device.

[0059] Please see Figure 5 , Figure 5This is a flowchart illustrating the implementation logic of a cloud-based data cleaning method provided in an embodiment of this application. Figure 5 As shown, the cloud server first receives the device operation data reported by the device group based on the network module. When the number of consecutive non-reporting times of the offline target device meets the preset consecutive number threshold, the target device is marked as an offline device, and subsequent invalid device judgment can be performed at this time; if there is no offline device, the current state is maintained.

[0060] S404. When at least one offline device is detected in the equipment unit, determine the first device information and the second device information of all devices in the equipment unit.

[0061] For details regarding step S404, please refer to the description in step S302; it will not be repeated here.

[0062] S406. Compare the number of first devices corresponding to the first device information and the number of second devices corresponding to the second device information.

[0063] Optionally, the first device information is the actual connection information in the device group, and the second device information is the address identification information recorded in the cloud server. Based on the first device information, the corresponding first device count can be obtained, which is the actual number of valid devices in the device group in a real-world scenario. Similarly, based on the second device information, the corresponding second device count can be obtained, which is the number of devices currently existing and previously existing in the device group recorded in the cloud server. Furthermore, by comparing the first device count and the second device count, a discrepancy between the two counts indicates that there are invalid devices among the offline devices.

[0064] S408. If the difference between the number of the first device and the number of the second device is equal to the total number of offline devices, then all offline devices are determined to be invalid devices.

[0065] Optionally, if after comparing the data of the first number of devices and the second number of devices, it is determined that the difference between the first number of devices and the second number of devices is equal to the total number of offline devices, then it can be determined that all offline devices are currently invalid devices.

[0066] For example, taking a multi-split air conditioning unit as an example, if the actual number of devices in the multi-split air conditioning unit is set to 8, the device addresses should be 1#-8#. Among them, the address of device 2# is reassigned to 9#, and the address of device 3# is reassigned to 10#. The cloud server records 10 devices with addresses 1#-10#. Since addresses 2# and 3# will no longer report any operating data, after the number of consecutive non-reporting reaches a preset threshold, the status of these two devices will become offline. The online devices are 8 devices in total: 1#, 4#-8#, and 9#-10#. At this time, 2 = 10 - 8, that is, the number of offline devices = the number of second devices recorded by the cloud server - the actual number of first devices in the unit. This means that addresses 2# and 3# correspond to invalid devices. At this time, the automatic deletion and cleanup of invalid device data can be further realized.

[0067] Please continue reading. Figure 5 When comparing the number of the first device and the number of the second device, and the difference between the number of the first device and the number of the second device is equal to the number of offline devices of all offline devices, then all offline devices are determined to be invalid devices, and the invalid device data corresponding to each invalid device can be cleared; if the result is not equal, then the device data corresponding to the offline devices can be temporarily left unprocessed to ensure the data integrity of the valid devices.

[0068] S4010. If all offline devices are invalid devices, then clear the invalid device data corresponding to each invalid device.

[0069] For details regarding step S4010, please refer to the description in step S306; it will not be repeated here.

[0070] This application provides a cloud-based data cleanup method. It receives device operation data reported by a device group at a preset frequency, monitors the presence of offline devices in the device group based on this data, and compares the number of first devices corresponding to first device information with the number of second devices corresponding to second device information. If the difference between the first and second device numbers equals the total number of offline devices, then all offline devices are determined to be invalid. A threshold for the number of consecutive times data is not reported is set to reduce misjudgments of offline devices. By comparing the actual number of devices in the device group with the number of device addresses recorded in the cloud server, it accurately determines whether all offline devices are invalid devices in the actual scenario. Furthermore, it directly cleans up invalid device data from invalid devices in the cloud server, automatically calibrating the accuracy of device information in the cloud server, reducing manual inspection and correction costs, and facilitating the subsequent use of the device group in the Internet of Things.

[0071] Please see Figure 6 , Figure 6 This is a flowchart illustrating a cloud-based data cleaning method provided in an embodiment of this application.

[0072] like Figure 6 As shown, cloud-based data cleanup methods can include at least:

[0073] S602. When at least one offline device is detected in the equipment unit, determine the first device information and the second device information of all devices in the equipment unit.

[0074] S604. Compare the number of first devices corresponding to the first device information and the number of second devices corresponding to the second device information.

[0075] For details regarding steps S602-S604, please refer to steps S404-S406; they will not be repeated here.

[0076] S606. If the difference between the number of the first device and the number of the second device is not equal to the total number of offline devices, then it is determined that there are valid devices among all offline devices.

[0077] Optionally, as can be seen from the above embodiments, if the difference between the number of the first device and the number of the second device is not equal to the number of offline devices of all offline devices, it indicates that not all offline devices are invalid devices, that is, there are valid devices among all offline devices.

[0078] For example, taking a multi-split air conditioning unit as an example, if the actual number of devices in the multi-split air conditioning unit is set to 8, the device addresses should be 1#-8#. Among them, some devices lose power, and some devices reset their addresses. For example, device 1# loses power, device 2# is set to 9#, and device 3# is set to 10#. The cloud server will record 10 devices. Since there is no reported device operation data for addresses 1#, 2#, and 3#, after the number of consecutive non-reports reaches a preset threshold, the status of these three devices will become offline. The online devices are 7 devices in total, namely 4#-8# and 9#-10#. The number of offline devices is 3, which is not equal to (the number of second devices recorded by the cloud server 10 - the actual number of first devices in the unit 8 = 2). This means that addresses 1#, 2#, and 3# are not all invalid devices, that is, there are valid devices. Therefore, the device data corresponding to the devices at addresses 1#, 2#, and 3# will not be cleared.

[0079] In another scenario, taking a multi-split air conditioning unit as an example, if the actual number of devices in the multi-split air conditioning unit is set to 8, the device addresses should be 1#-8#. When all indoor units lose power, the cloud server will record 8 devices. Since no device operation data is reported for addresses 1#-8#, after the number of consecutive non-reporting reaches a preset threshold, the status of these 8 devices will become offline. The number of offline devices is 8 ≠ (the number of second devices recorded by the cloud server is 8 - the actual number of first devices in the unit is 8 = 0). Therefore, the device data corresponding to the devices at addresses 1#-8# will not be cleared.

[0080] S608. Determine the validity of each offline device. When there is at least one invalid device among all offline devices, identify each invalid device and clear the invalid device data corresponding to each invalid device.

[0081] Optionally, when valid devices exist among the offline devices, the validity of each offline device can be further determined one by one. If at least one invalid device exists among all offline devices, the specific invalid device is identified, and the invalid device data corresponding to each invalid device is deleted from the cloud server accordingly. This can protect the device data of valid devices in the cloud server and reduce the occurrence of accidental deletion.

[0082] Specifically, when verifying the validity of each offline device, historical device data can be used to determine the specific usage of each offline device in the actual scenario, and then the validity of each offline device can be determined based on the actual usage. It is understood that there can be multiple methods for verifying the validity of each offline device, and an appropriate validity judgment scheme can be selected based on the specific type of IoT device unit and its actual scenario requirements. This application embodiment does not impose specific limitations on this.

[0083] This application provides a cloud data cleanup method. When at least one offline device is detected in a device group, the method determines the first device information and the second device information of all devices in the device group, and compares the number of first devices corresponding to the first device information and the number of second devices corresponding to the second device information. If the difference between the number of first devices and the number of second devices is not equal to the total number of offline devices, then it is determined that there are valid devices among all offline devices. The method then determines the validity of each offline device. If at least one invalid device is found among all offline devices, each invalid device is identified and its corresponding invalid device data is cleared. If not all offline devices are invalid devices, the method further determines the specific invalid devices among the offline devices based on their validity, and then selectively clears the invalid device data corresponding to each invalid device in the cloud server, protecting the device data of valid devices in the cloud server and reducing the occurrence of false cleanup.

[0084] Please see Figure 7 , Figure 7 This is a structural block diagram of a cloud-based data cleaning device provided in an embodiment of this application. Figure 7 As shown, the cloud data cleaning device 700, applied to a cloud server, includes:

[0085] The status monitoring module 710 is used to determine the first device information and the second device information of all devices in the equipment group when at least one offline device is detected in the equipment group. The first device information is the actual connection information of all devices in the equipment group, and the second device information is the address identification information of all devices recorded in the cloud server.

[0086] The equipment inspection module 720 is used to determine whether all offline devices are invalid devices based on the first device information and the second device information;

[0087] The data cleaning module 730 is used to clear the invalid device data corresponding to each invalid device if all offline devices are invalid devices.

[0088] Optionally, the equipment inspection module 720 is further used to compare the number of first devices corresponding to the first equipment information and the number of second devices corresponding to the second equipment information; if the difference between the number of first devices and the number of second devices is equal to the number of offline devices of all offline devices, then all offline devices are determined to be invalid devices.

[0089] Optionally, the cloud data cleaning device 700 further includes: an invalid device determination module, used to determine that there are valid devices among all offline devices if the difference between the number of the first devices and the number of the second devices is not equal to the number of offline devices of all offline devices; to determine the validity of each offline device; and when there is at least one invalid device among all offline devices, to determine each invalid device and clear the invalid device data corresponding to each invalid device.

[0090] Optionally, the cloud data cleaning device 700 also includes: an operation data receiving module, used to receive the equipment operation data corresponding to each device reported by the equipment unit at a preset frequency, and to monitor whether there are offline devices in the equipment unit based on the operation data of each device.

[0091] Optionally, the equipment operation data includes at least one of equipment sensor data, equipment control data, and equipment status data.

[0092] Optionally, the data receiving module is also used to record the number of consecutive times the target device has not reported when a target device without operating data is detected in the equipment unit; if the number of consecutive times of non-reporting meets the preset consecutive number threshold, the target device is marked as an offline device.

[0093] Optionally, the invalid device data may include at least the address identifier information corresponding to each invalid device in the cloud server.

[0094] This application provides a cloud data cleaning device applied to a cloud server. The device includes a status monitoring module, used to determine first and second device information for all devices in the device group when at least one offline device is detected in the device group. The first device information is the actual connection information of all devices in the device group, and the second device information is the address identification information of all devices recorded in the cloud server. A device verification module is used to determine whether all offline devices are invalid devices based on the first and second device information. A data cleaning module is used to clear the invalid device data corresponding to each invalid device if all offline devices are invalid. Since the cloud server records the address information of all connected devices, and the actual devices in the device group may be modified or deleted, when the cloud server detects offline devices, by comparing the actual connection information in the device group with the device address information recorded in the cloud server, it can accurately determine whether the offline devices are invalid devices in the actual scenario. Furthermore, it can directly clean the invalid device data of invalid devices in the cloud server, achieving automatic calibration of the accuracy of device information in the cloud server, reducing the cost of manual inspection and correction, and facilitating the subsequent use of the device group in the Internet of Things.

[0095] This application also provides a computer storage medium that can store multiple instructions adapted for loading by a processor and executing the steps of any of the methods described in the above embodiments.

[0096] Please see Figure 8 , Figure 8 This is a schematic diagram of the structure of a cloud server provided in an embodiment of this application. Figure 8 As shown, the cloud server 800 may include: at least one cloud server processor 801, at least one network interface 804, a user interface 803, a memory 805, and at least one communication bus 802.

[0097] The communication bus 802 is used to enable communication between these components.

[0098] The user interface 803 may include a display screen and a camera. Optionally, the user interface 803 may also include a standard wired interface and a wireless interface.

[0099] The network interface 804 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0100] The cloud server processor 801 may include one or more processing cores. The cloud server processor 801 connects to various parts within the cloud server 800 using various interfaces and lines. It executes various functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 805, and by accessing data stored in the memory 805. Optionally, the cloud server processor 801 may be implemented using at least one of the following hardware forms: Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The cloud server processor 801 may integrate one or more of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content to be displayed on the screen; and the modem handles wireless communication. It is understood that the modem may also be implemented as a separate chip without being integrated into the cloud server processor 801.

[0101] The memory 805 may include random access memory (RAM) or read-only memory (ROM). Optionally, the memory 805 may include a non-transitory computer-readable storage medium. The memory 805 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 805 may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch functionality, sound playback functionality, image playback functionality, etc.), instructions for implementing the various method embodiments described above, etc.; the data storage area may store data involved in the various method embodiments described above, etc. Optionally, the memory 805 may also be at least one storage device located remotely from the aforementioned cloud server processor 801. Figure 8 As shown, the memory 805, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and a cloud data cleaning program.

[0102] exist Figure 8In the cloud server 800 shown, the user interface 803 is mainly used to provide an input interface for users and obtain user input data; while the cloud server processor 801 can be used to call the cloud data cleanup program stored in the memory 805 and specifically perform the following operations:

[0103] When at least one offline device is detected in the equipment group, the first device information and the second device information of all devices in the equipment group are determined. The first device information is the actual connection information of all devices in the equipment group, and the second device information is the address identification information of all devices recorded in the cloud server.

[0104] Based on the first device information and the second device information, determine whether all offline devices are invalid devices;

[0105] If all offline devices are invalid devices, then clear the invalid device data corresponding to each invalid device.

[0106] In some embodiments, when the cloud server processor 801 determines whether all offline devices are invalid devices based on the first device information and the second device information, it specifically performs the following steps: comparing the number of first devices corresponding to the first device information and the number of second devices corresponding to the second device information; if the difference between the number of first devices and the number of second devices is equal to the number of offline devices of all offline devices, then it is determined that all offline devices are invalid devices.

[0107] In some embodiments, after comparing the number of first devices corresponding to the first device information and the number of second devices corresponding to the second device information, the cloud server processor 801 further performs the following steps: if the difference between the number of first devices and the number of second devices is not equal to the number of offline devices of all offline devices, then it is determined that there are valid devices among all offline devices; the validity of each offline device is determined, and when there is at least one invalid device among all offline devices, each invalid device is determined and the invalid device data corresponding to each invalid device is cleared.

[0108] In some embodiments, before executing the action of detecting at least one offline device in the device group, the cloud server processor 801 further performs the following steps: receiving device operation data corresponding to each device reported by the device group at a preset frequency, and monitoring whether there are offline devices in the device group based on the device operation data.

[0109] In some embodiments, device operation data includes at least one of device sensor data, device control data, and device status data.

[0110] In some embodiments, when the cloud server processor 801 performs the following steps to monitor whether there are offline devices in the equipment group based on the operation data of each device: when a target device without operation data is detected in the equipment group, the number of consecutive non-reporting times of the target device is recorded; if the number of consecutive non-reporting times meets the preset consecutive number threshold, the target device is marked as an offline device.

[0111] In some embodiments, the invalid device data includes at least the address identification information corresponding to each invalid device in the cloud server.

[0112] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0113] The modules described as separate components may or may not be physically separate. Similarly, the components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0114] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When these computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this specification are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The aforementioned available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., Digital Versatile Discs (DVDs)), or semiconductor media (e.g., Solid State Disks (SSDs)).

[0115] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0116] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0117] The above is a description of a cloud data cleaning method, apparatus, storage medium, and cloud server provided in this application. For those skilled in the art, based on the ideas of the embodiments of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A cloud-based data cleaning method, characterized in that, Applied to cloud servers, the method includes: When at least one offline device is detected in the equipment group, the first device information and the second device information of all devices in the equipment group are determined. The first device information is the actual connection information of all real devices in the equipment group, and the second device information is the address identification information of all devices recorded in the cloud server. Based on the first device information and the second device information, determine whether all offline devices are invalid devices; If all offline devices are invalid devices, then clear the invalid device data corresponding to each invalid device; The step of determining whether all offline devices are invalid devices based on the first device information and the second device information includes: Compare the number of first devices corresponding to the first device information with the number of second devices corresponding to the second device information; If the difference between the first number of devices and the second number of devices is equal to the total number of offline devices, then all offline devices are determined to be invalid devices. After comparing the number of first devices corresponding to the first device information and the number of second devices corresponding to the second device information, the method further includes: If the difference between the first number of devices and the second number of devices is not equal to the total number of offline devices, then it is determined that there are valid devices among all offline devices. Determine the validity of each offline device. If at least one invalid device exists among all offline devices, identify each invalid device and clear the invalid device data corresponding to each invalid device.

2. The method according to claim 1, characterized in that, Before detecting that at least one offline device exists in the equipment unit, the method further includes: The system receives equipment operation data reported by the equipment unit at a preset frequency, and monitors whether there are offline devices in the equipment unit based on the equipment operation data.

3. The method according to claim 2, characterized in that, The equipment operation data includes at least one of equipment sensor data, equipment control data, and equipment status data.

4. The method according to claim 2, characterized in that, The monitoring of whether there are offline devices in the equipment unit based on the operating data of each device includes: When a target device without operational data is detected in the equipment unit, the number of consecutive times the target device fails to report is recorded. If the number of consecutive unreported times meets the preset consecutive number threshold, the target device is marked as an offline device.

5. The method according to claim 1, characterized in that, The invalid device data includes at least the address identification information corresponding to each invalid device in the cloud server.

6. A cloud-based data cleaning device, characterized in that, The device, applied to a cloud server, includes: The status monitoring module is used to determine the first device information and the second device information of all devices in the equipment group when at least one offline device is detected in the equipment group. The first device information is the actual connection information of all real devices in the equipment group, and the second device information is the address identification information of all devices recorded in the cloud server. The equipment verification module is used to determine whether all offline devices are invalid devices based on the first device information and the second device information; The data cleaning module is used to clear the invalid device data corresponding to each invalid device if all offline devices are invalid devices. The device inspection module is further configured to compare the number of first devices corresponding to the first device information with the number of second devices corresponding to the second device information; if the difference between the number of first devices and the number of second devices is equal to the number of offline devices of all offline devices, then all offline devices are determined to be invalid devices. The invalid device determination module is used to determine that there are valid devices among all offline devices if the difference between the number of the first devices and the number of the second devices is not equal to the number of offline devices of all offline devices; to determine the validity of each offline device; and to determine each invalid device and clear the invalid device data corresponding to each invalid device when there is at least one invalid device among all offline devices.

7. A computer storage medium, characterized in that, The computer storage medium stores a plurality of instructions adapted for loading by a processor and executing the steps of the method as described in any one of claims 1 to 5.

8. A cloud server, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the steps of the method as described in any one of claims 1 to 5.

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