Internet of Things data interaction method and system

Abstract

The embodiment of the invention relates to the technical field of computers, and discloses an Internet of Things data interaction method and system, and the method comprises the steps: responding to a request instruction of first Internet of Things equipment for target video data; order information on the first Internet of Things equipment is acquired; extracting first sub-video data, second sub-video data and third video data shot by the second Internet of Things equipment and the third Internet of Things equipment based on the order information; performing data fusion on the first sub-video data, the second sub-video data and the third video data to obtain quasi target video data; extracting target person features in the second sub-video data; performing blurring processing on non-target person features in the quasi target video data to obtain target video data; and performing encryption processing on the target video data and then sending the target video data to the first Internet of Things equipment. Therefore, the efficiency of acquiring the target video data by the user can be improved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to an Internet of Things data interaction method and system. Background Art

[0002] With the improvement of living standards, people's pace of life is gradually accelerating. After people carry out multiple activities in different places, such as eating in a restaurant and then going out for outdoor activities, they often lose their belongings. When they realize that something is lost, they don't know when and where it was lost. At this time, the user has been away from the restaurant for a long time. For such problems, the current common practice is to immediately go to the restaurant to ask the clerk and check the surveillance. However, after users spend a lot of time to check the surveillance in the restaurant, they find that the item is not lost in the restaurant, resulting in missing the best opportunity to find the lost item. Summary of the invention

[0003] The main purpose of the present invention is to provide an Internet of Things data interaction method and system, aiming to solve the technical problem that the required target data cannot be obtained quickly and effectively in the prior art.

[0004] To achieve the above-mentioned purpose, in a first aspect, an embodiment of the present application provides an Internet of Things data interaction method, which is applied to an Internet of Things system, wherein the Internet of Things system at least includes a first Internet of Things device, a second Internet of Things device, a third Internet of Things device and a service platform, wherein the first Internet of Things device includes a user mobile terminal, and the second Internet of Things device and the third Internet of Things device include a camera device, and the method includes: Responding to a request instruction from the first IoT device for target video data; Obtaining order information on the first IoT device, wherein the order information includes an order number; Extracting the first sub-video data, the second sub-video data, and the third video data captured by the second IoT device and the third IoT device based on the order information; Performing data fusion on the first sub-video data, the second sub-video data and the third video data to obtain quasi-target video data; Extracting features of a target person in the second sub-video data; Performing blurring processing on non-target person features in the quasi-target video data to obtain target video data; The target video data is encrypted and sent to the first IoT device, wherein the decryption password after the encryption is the order number.

[0005] Preferably, the order information also includes the order time and the dining location, and the extracting of the first sub-video data, the second sub-video data and the third video data shot by the second IoT device and the third IoT device based on the order information includes: Based on the order information, estimate the user's store entry time, dining time and store exit time; According to the store entry time and the store exit time, respectively extract the video data shot by the second IoT device at the corresponding time to obtain the first sub-video data and the third video data; According to the dining time and dining location, the video data shot by the third Internet of Things device at the corresponding time and the corresponding location is extracted to obtain the second sub-video data.

[0006] Preferably, estimating the user's store entry time, dining time, and store exit time based on the order information includes: Based on the order time, a rough estimate of the store entry time, dining time, and store exit time is obtained; The rough store entry time, dining time and store exit time are respectively compensated for the length of time before and after to obtain the user's store entry time, dining time and store exit time.

[0007] Preferably, the extracting, according to the dining time and dining location, the video data shot by the third IoT device at the corresponding time and the corresponding location to obtain the second sub-video data includes: Starting from the dining start time, a target image frame of the dining location is acquired at every preset time interval; The plurality of target image frames are subjected to data fusion in chronological order to obtain second sub-video data.

[0008] Preferably, obtaining the order information on the first IoT device includes: Sending an order information request to the first IoT device; In response to the user confirming the target order information on the first IoT device; The target order information is obtained from the first IoT device.

[0009] Preferably, the fusing the first sub-video data, the second sub-video data and the third video data to obtain the quasi-target video data comprises: The quasi-target video data is obtained by performing data fusion in the order of the first sub-video data, the second sub-video data and the third sub-video data.

[0010] Preferably, extracting the target person features in the second sub-video data includes: Recognize the contour features of the target person in the second sub-video data to obtain a first contour; The first contour of the target person and its internal features are extracted to obtain the target person features.

[0011] Preferably, blurring the non-target person features in the quasi-target video data to obtain the target video data includes: Expanding the first outline of the target person to obtain a second outline; The features outside the second contour in the quasi-target video data are blurred to obtain target video data.

[0012] In a second aspect, an Internet of Things system is also provided in an embodiment of the present application, including: A first Internet of Things device, wherein the first Internet of Things device includes a user mobile terminal; A second Internet of Things device, which is disposed at an entrance and exit of a preset place and is used to obtain video data of the entrance and exit; A third IoT device, which is disposed in an internal space of a preset location and is used to obtain video data of the internal space; and A service platform, the service platform comprising a processor and a memory; wherein the memory is used to store program code, and the processor is used to call the program code to execute the method as described in the first aspect.

[0013] In a third aspect, an embodiment of the present application further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the method described in the first aspect is implemented.

[0014] Different from the prior art, the IoT data interaction method provided by the embodiment of the present application first obtains the order information on the first IoT device according to the request instruction; then extracts the first sub-video data, the second sub-video data and the third video data shot by the second IoT device and the third IoT device based on the order information; then fuses the first sub-video data, the second sub-video data and the third video data to obtain the quasi-target video data; then extracts the target person features in the second sub-video data; then blurs the non-target person features in the quasi-target video data to obtain the target video data; finally, encrypts the target video data and sends it to the first IoT device; that is, the user requests the target video data on the user terminal through the order information, and the target video data is sent to the user after being encrypted. In this way, while ensuring data security and privacy security, the efficiency of users in obtaining target video data can be improved, avoiding spending a lot of time on the road and missing the best time to find things. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0016] Figure 1 This is a flowchart of the IoT data interaction method in some embodiments of the present application; Figure 2 This is a schematic diagram of the operation interface of the first Internet of Things device in some embodiments of the present application; Figure 3 This is a schematic diagram of order information on a first IoT device in some embodiments of the present application; Figure 4 This is a schematic diagram of the hardware structure of the Internet of Things system in some embodiments of the present application.

[0017] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0020] In addition, the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, "and / or" in the full text includes three solutions. Taking A and / or B as an example, it includes technical solution A, technical solution B, and technical solution that satisfies both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in this field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0021] With the improvement of living standards, people's pace of life is gradually accelerating. After people carry out multiple activities in different places, such as eating in a restaurant and then going out for outdoor activities, they often lose their belongings (such as various bags, etc.). When users realize that something is lost, they don't know when and where it was lost. At this time, the user has been away from the restaurant for a long time. For such problems, the current common practice is to immediately go to the restaurant to ask the clerk and check the surveillance. However, users spend a lot of time to check the surveillance in the restaurant and find that the item is not lost in the restaurant, resulting in missing the best opportunity to find the lost item. In addition, when viewing the relevant video on the spot, it is inevitable to see other users' related videos, exposing the privacy of other users.

[0022] In view of the above problems, the present application embodiment provides an Internet of Things system 100. Figure 4 , Figure 4 A schematic diagram of the hardware structure of the Internet of Things system provided in the embodiment of the present application. The Internet of Things system includes a first Internet of Things device 110, which includes a user mobile terminal, such as a mobile phone, etc., and the user can scan the code on the mobile phone terminal to order food; a second Internet of Things device 120, which is set at the entrance and exit of the preset place and is used to obtain video data of the entrance and exit; a third Internet of Things device 130, which is set in the internal space of the preset place and is used to obtain video data of the internal space.

[0023] For example, a first camera may be installed at a target location such as a restaurant entrance to monitor the entry and exit of people at the restaurant entrance, and a second camera may be installed at a target location such as a dining space inside a restaurant to monitor the dining situation of people in the dining space.

[0024] The embodiment of the present application also provides an IoT data interaction method, which is applied to the IoT system 100. The method requests corresponding data on the user terminal through order information to accurately obtain target video data, and the target video data is sent to the user terminal after encryption. In this way, the efficiency of users obtaining target video data can be improved, avoiding spending a lot of time on the road and missing the best time to find things.

[0025] The following will mainly describe the specific steps of the IoT data interaction method. It should be noted that although the logical order is shown in the flowchart, in some cases, the steps shown or described can be performed in a different order from that shown here. Figure 1 , the Internet of Things data interaction method comprises the following steps: S100, responding to a request instruction of the first IoT device for target video data; When the user leaves the target place and wants to know whether the lost item is in the target place (such as the restaurant where he / she eats), the target video data can be directly acquired in the first IoT device, such as Figure 2 As shown, just click "Video Request" on a mobile phone or other terminal device.

[0026] S200, obtaining order information on the first IoT device; When the system senses that the user clicks "video request", the system obtains the order information on the first IoT device. There are many ways to obtain the order information, such as the system automatically obtaining the latest order information, or the user inputting the order information into the corresponding module to obtain the order information through manual input by the user, or the system can obtain the order information by combining automatic acquisition with manual operation by the user. In one embodiment of the present application, the order information on the first IoT device is obtained, including: S210, sending an order information request to the first IoT device; S220, responding to the user's confirmation of the target order information on the first IoT device; S230: Obtain the target order information on the first IoT device.

[0027] For example, after the system senses that the user clicks "video request", it sends an order information request to the first IoT device. At this time, the system selects the most recent order information by default and highlights it, such as Figure 2 As shown, when the user clicks "Video Request", the mobile phone interface highlights Order 3, and when the user clicks the highlighted order information (Order 3), the order information is sent to the background.

[0028] S300, extracting first sub-video data, second sub-video data, and third video data captured by the second IoT device and the third IoT device based on the order information; In the embodiment of the present application, Figure 3 As shown, the order information includes the order number, order time, dining location, etc. Therefore, the video data of the corresponding time and corresponding location can be obtained according to the order information.

[0029] In one embodiment, extracting the first sub-video data, the second sub-video data, and the third video data captured by the second IoT device and the third IoT device based on the order information includes: S310, estimating the user's store entry time, dining time, and store exit time based on the order information; Estimating the user's store entry time, dining time, and store exit time can be roughly divided into the following two steps: (1) First, a rough estimate of the store entry time, dining time, and store exit time is obtained based on the order time; (2) the rough store entry time, dining time, and store exit time are compensated for the length of time before and after the rough store entry time, dining time, and store exit time to obtain the user's store entry time, dining time, and store exit time.

[0030] For example, Figure 3 As shown, when the order payment time is 13:08, we can calculate forward 5 minutes to get that the user entered the hotel from the entrance at about 13:03, or calculate forward 3 minutes to get that the user entered the hotel from the entrance at about 13:05. The time of compensation before and after can be determined manually based on historical observations.

[0031] Similarly, dining time can be calculated from order time and meal preparation time, and check-out time can be calculated from dining time. The specific calculation process is just the addition and subtraction of time, which will not be elaborated here.

[0032] S320, extracting the video data shot by the second IoT device at the corresponding time according to the store entry time and the store exit time to obtain the first sub-video data and the third video data; Specifically, the system extracts the video data shot by the second Internet of Things device set at the entrance and exit of the hotel at the corresponding time according to the user's entry time to obtain the first sub-video data; and extracts the video data shot by the second Internet of Things device set at the entrance and exit of the hotel at the corresponding time according to the user's departure time to obtain the third sub-video data; that is, the first video data is the video data of the user's entry time, and the third video time is the video data of the user's departure time.

[0033] S330. According to the dining time and dining location, extract the video data shot by the third IoT device at the corresponding time and the corresponding location to obtain second sub-video data.

[0034] Specifically, the dining location is Figure 3 As shown, 26 tables represent dining locations; the system extracts the video data shot by the third Internet of Things device set in the internal space of the hotel at the corresponding time and corresponding location according to the dining time and dining location to obtain the second video data, that is, the second video data is the video data of the user when dining.

[0035] S400, performing data fusion on the first sub-video data, the second sub-video data and the third video data to obtain quasi-target video data; To ensure the integrity of the target video data and to facilitate users to observe the status of the user themselves (including personal belongings, such as bags, etc.) when entering, dining, and leaving the store, in an embodiment of the present application, after obtaining the video data of the user's entry time (first sub-video data), the video data of the user's dining time (second sub-video data), and the video data of the user's departure time (third sub-video data), the system performs data fusion on the first sub-video data, the second sub-video data, and the third video data to obtain quasi-target video data. Since the first sub-video data, the second sub-video data, and the third video data are video data obtained in chronological order, in order to facilitate users to observe the entire process from entering the store to leaving the store, the embodiment of the present application performs data fusion in the order of the first sub-video data, the second sub-video data, and the third video data to obtain quasi-target video data.

[0036] It is understandable that this quasi-target video data may contain other personal features besides the user. When other personal features are sent to the user terminal through the target video, the privacy of other users will be exposed, seriously affecting the privacy security of the user.

[0037] S500, extracting features of a target person in the second sub-video data; S600, blurring the non-target person features in the quasi-target video data to obtain target video data; In order to solve the problem of exposing the privacy of other users, the target video data is desensitized in the embodiment of the present application. Since the video data of the user dining (the second sub-video data) contains complete user features, the desensitization process first extracts the character features in the second sub-video data to obtain the target character features; then blurs the non-target character features in the target video data to obtain the target video data. This operation excludes other users from the target video data, and the user can only query and obtain the video data containing himself in the target video data, thereby ensuring the privacy security of other users.

[0038] S700: encrypt the target video data and send it to the first IoT device, wherein the decryption password after the encryption is the order number in the order information.

[0039] After obtaining the target video data after desensitization, the system encrypts it through the encryption system and sends it to the first IoT device that requested the video, that is, the mobile terminal such as the mobile phone of the requesting user, such as Figure 2 As shown, the user can click "View Video" on the mobile terminal device and enter the corresponding decryption password to view the video. The embodiment of the present application uses the order number in the order information as the decryption password, further ensuring the security of the target video data transmission.

[0040] In this way, users only need to request the target video data on the mobile terminal to obtain the corresponding video data, without having to go to the target location in person to view the video on site. While ensuring data security and privacy security, it can improve the efficiency of users in obtaining target video data and avoid spending a lot of time on the road and missing the best time to find things.

[0041] It is understandable that the dining time of the user depends on the amount of food ordered. The more food ordered, the longer the dining time. Since the general dining time can be as long as 10 minutes or even longer, if the video data (second sub-video data) of the dining time of 10 minutes or even longer is directly extracted, not only a more powerful data processing capability is required, but also a larger data storage space is required. Therefore, in one embodiment, the video data shot by the third IoT device at the corresponding time and corresponding location to obtain the second sub-video data is extracted according to the dining time and dining location, including: S331, starting from the dining start time, obtaining a target image frame of the dining location at every preset time interval; S332: fusing the plurality of target image frames in chronological order to obtain second sub-video data.

[0042] Specifically, during the dining time period, a target image frame of the dining location is first obtained at a preset interval (such as 2 minutes or 3 minutes), and then multiple target image frames are fused in chronological order to obtain the second sub-video data. In this way, key images are extracted to synthesize related videos based on the images, which can reduce the processing burden of the processor and the storage load of the memory while satisfying the user's need to view their own situation.

[0043] In one embodiment, extracting the target person features in the second sub-video data includes: S510, identifying contour features of a target person in the second sub-video data to obtain a first contour; S520: Extract the first outline of the target person and its internal features to obtain target person features.

[0044] Specifically, in order to effectively protect the privacy of other users in the video data, it is necessary to perform hiding and desensitization operations such as blurring other person features in the target video data. Therefore, it is necessary to identify and extract the target person features. The embodiment of the present application first obtains the contour features (first contour) of the target person through feature recognition, and then extracts the first contour of the target person and its internal features to obtain the target person features; In other embodiments, after obtaining the target person's features, the non-target person's features in the quasi-target video data may be blurred to obtain the target video data, and the blurring step includes: firstly, expanding the first outline of the target person to obtain the second outline, for example, expanding outward by 10mm or 20mm; then blurring the features outside the second outline in the quasi-target video data to obtain the target video data. That is, the target person's features are appropriately expanded (expanding operation), and the expanding operation can compensate for possible misidentification to a certain extent to ensure the integrity of the target person's features, and facilitate users to check themselves (personal belongings, including lost items) to determine whether the lost items are lost in the store.

[0045] like Figure 4 As shown, an Internet of Things system 100 provided in an embodiment of the present application further includes a service platform 140, and the service platform 140 includes a processor 141 and a memory 142; Among them, the processor 141 is used to provide computing and control capabilities so that the Internet of Things system performs corresponding tasks, for example, controlling the Internet of Things system to execute the Internet of Things data interaction method in any of the above-mentioned method embodiments, the method comprising: responding to a request instruction for target video data from a first Internet of Things device; obtaining order information on the first Internet of Things device, wherein the order information includes an order number; extracting the first sub-video data, the second sub-video data and the third video data captured by the second Internet of Things device and the third Internet of Things device based on the order information; performing data fusion on the first sub-video data, the second sub-video data and the third video data to obtain quasi-target video data; extracting target person features in the second sub-video data; blurring non-target person features in the quasi-target video data to obtain target video data; encrypting the target video data and sending it to the first Internet of Things device, wherein the decryption password after the encryption is the order number.

[0046] The processor 141 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), a hardware chip, or any combination thereof; it may also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The above-mentioned PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0047] The memory 142 is a non-transient computer-readable storage medium that can be used to store non-transient software programs, non-transient computer executable programs and modules, such as program instructions / modules corresponding to the method for determining operating parameters in the embodiment of the present application. The processor 141 can implement the IoT data interaction method in any of the above method embodiments by running the non-transient software programs, instructions and modules stored in the memory 142.

[0048] Specifically, the memory 142 may include a volatile memory (VM), such as a random access memory (RAM); the memory 142 may also include a non-volatile memory (NVM), such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD) or other non-transitory solid-state storage device; the memory 142 may also include a combination of the above types of memory.

[0049] To sum up, the Internet of Things system of the present application adopts the technical solution of any one of the above-mentioned Internet of Things data interaction method embodiments, and therefore, has at least the beneficial effects brought by the technical solutions of the above-mentioned embodiments, which will not be repeated here one by one.

[0050] The embodiment of the present application also provides a computer-readable storage medium, such as a memory including a program code, and the program code can be executed by a processor to complete the IoT data interaction method in the above embodiment. For example, the computer-readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CDROM), a magnetic tape, a floppy disk, and an optical data storage device.

[0051] The present application also provides a computer program product, which includes one or more program codes stored in a computer-readable storage medium. The processor of the Internet of Things system reads the program code from the computer-readable storage medium, and the processor executes the program code to complete the steps of the Internet of Things data interaction method provided in the above embodiment.

[0052] A person skilled in the art will appreciate that all or part of the steps for implementing the above embodiments may be accomplished by hardware or by hardware associated with a program code, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0053] It should be noted that the system embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0054] Through the description of the above embodiments, it can be clearly understood by those skilled in the art that each embodiment can be implemented by means of software plus a general hardware platform, or by hardware. It can be understood by those skilled in the art that all or part of the processes in the above embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above methods. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0055] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. All equivalent structural changes made by using the contents of the present invention specification and drawings under the inventive concept of the present invention, or directly / indirectly applied in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. A method for data interaction in the Internet of Things, characterized in that: Applied to an Internet of Things system, the Internet of Things system includes at least a first Internet of Things device, a second Internet of Things device, a third Internet of Things device and a service platform, the first Internet of Things device includes a user mobile terminal, the second Internet of Things device and the third Internet of Things device include a camera device, and the method includes: Responding to a request instruction from the first IoT device for target video data; Obtain order information on the first IoT device; Extracting the first sub-video data, the second sub-video data, and the third video data captured by the second IoT device and the third IoT device based on the order information; Performing data fusion on the first sub-video data, the second sub-video data and the third video data to obtain quasi-target video data; Extracting features of a target person in the second sub-video data; Performing blurring processing on non-target person features in the quasi-target video data to obtain target video data; The target video data is encrypted and sent to the first IoT device, wherein the decryption password after the encryption is the order number in the order information.

2. The Internet of Things data interaction method according to claim 1, characterized in that: The order information also includes the order time and the dining location, and the first sub-video data, the second sub-video data and the third video data captured by the second IoT device and the third IoT device are extracted based on the order information, including: Based on the order information, estimate the user's store entry time, dining time, and store exit time; According to the store entry time and the store exit time, respectively extract the video data shot by the second IoT device at the corresponding time to obtain the first sub-video data and the third video data; According to the dining time and dining location, the video data shot by the third Internet of Things device at the corresponding time and the corresponding location is extracted to obtain the second sub-video data.

3. The Internet of Things data interaction method according to claim 2, characterized in that: The estimating of the user's store entry time, dining time, and store exit time based on the order information includes: Based on the order time, a rough estimate of the store entry time, dining time, and store exit time is obtained; The rough store entry time, dining time and store exit time are respectively compensated for the length of time before and after to obtain the user's store entry time, dining time and store exit time.

4. The Internet of Things data interaction method according to claim 2, characterized in that: The extracting, according to the dining time and dining location, the video data shot by the third IoT device at the corresponding time and the corresponding location to obtain the second sub-video data includes: Starting from the dining start time, a target image frame of the dining location is acquired at every preset time interval; The plurality of target image frames are subjected to data fusion in chronological order to obtain second sub-video data.

5. The Internet of Things data interaction method according to claim 1, characterized in that: The obtaining of order information on the first IoT device includes: Sending an order information request to the first IoT device; In response to the user confirming the target order information on the first IoT device; The target order information is obtained from the first IoT device.

6. The Internet of Things data interaction method according to claim 1, characterized in that: The step of fusing the first sub-video data, the second sub-video data and the third video data to obtain quasi-target video data includes: The quasi-target video data is obtained by performing data fusion in the order of the first sub-video data, the second sub-video data and the third sub-video data.

7. The Internet of Things data interaction method according to claim 1, characterized in that: The extracting the target person features in the second sub-video data includes: Recognize the contour features of the target person in the second sub-video data to obtain a first contour; The first contour of the target person and its internal features are extracted to obtain the target person features.

8. The Internet of Things data interaction method according to claim 7, characterized in that: The blurring of non-target person features in the quasi-target video data to obtain target video data includes: Expanding the first outline of the target person to obtain a second outline; The features outside the second contour in the quasi-target video data are blurred to obtain target video data.

9. An Internet of Things system, characterized in that: include: A first Internet of Things device, wherein the first Internet of Things device includes a user mobile terminal; A second Internet of Things device, which is disposed at an entrance and exit of a preset place and is used to obtain video data of the entrance and exit; A third IoT device, which is disposed in an internal space of a preset location and is used to obtain video data of the internal space; as well as, A service platform, comprising a processor and a memory; wherein the memory is used to store program code, and the processor is used to call the program code to execute the method according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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