An Internet of Things data interaction method and system

Abstract

The embodiment of the present application relates to the field of computer technology, and discloses an Internet of Things data interaction method and system. The method includes: responding to a request instruction of a first Internet of Things device for target video data; obtaining order information on the first Internet of Things device; extracting first sub-video data, second sub-video data and 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, second sub-video data and 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; encrypting the target video data and sending it to the first Internet of Things device. In this way, the efficiency of the user obtaining the target video data can be improved.

Description

Technical Field

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

[0002] With the improvement of living standards, people's life rhythm has gradually accelerated. After people carry out multiple activities in different places, such as having a meal in a restaurant first and then going outdoors for outdoor activities, they often lose the items they carry with them. When they realize that an item is lost, the user doesn't know at which time and in which place it was lost. At this time, the user has also 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 staff and check the surveillance. However, after the user spends a lot of time checking the surveillance in the restaurant, it is found that the item was not lost in the restaurant, resulting in missing the best opportunity to find the lost item. Summary of the Invention

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

[0004] To achieve the above objective, in a first aspect, an IoT data interaction method provided in an embodiment of the present application is applied to an IoT system. The IoT system includes at least a first IoT device, a second IoT device, a third IoT device, and a service platform. The first IoT device includes a user mobile terminal, and the second IoT device and the third IoT device include camera devices. The method includes:

[0005] Responding to a request instruction of the first IoT device for target video data;

[0006] Obtaining order information on the first IoT device, where the order information includes an order number;

[0007] 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;

[0008] 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;

[0009] Extracting target person features in the second sub-video data;

[0010] Performing blurring processing on non-target person features in the quasi-target video data to obtain target video data;

[0011] Encrypting the target video data and sending it to the first IoT device, where the decryption password after the encryption process is the order number.

[0012] Preferably, the order information further includes the order placing time and the dining location. 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 includes:

[0013] Estimating the user's entry time, dining time, and departure time based on the order information;

[0014] According to the entry time and the departure time, extracting the video data captured by the second Internet of Things device at the corresponding times to obtain the first sub-video data and the third video data;

[0015] According to the dining time and the dining location, extracting the video data captured by the third Internet of Things device at the corresponding time and the corresponding location to obtain the second sub-video data.

[0016] Preferably, estimating the user's entry time, dining time, and departure time based on the order information includes:

[0017] Preliminarily estimating the rough entry time, dining time, and departure time according to the order placing time;

[0018] Performing front and back duration compensation on the rough entry time, dining time, and departure time respectively to obtain the user's entry time, dining time, and departure time.

[0019] Preferably, extracting the video data captured by the third Internet of Things device at the corresponding time and the corresponding location according to the dining time and the dining location to obtain the second sub-video data includes:

[0020] Starting from the dining start time, obtaining a target image frame of the dining location every preset duration;

[0021] Fusing the multiple target image frames in chronological order to obtain the second sub-video data.

[0022] Preferably, obtaining the order information on the first Internet of Things device includes:

[0023] Sending an order information request to the first Internet of Things device;

[0024] In response to the user's confirmation of the target order information on the first Internet of Things device;

[0025] Obtaining the target order information on the first Internet of Things device.

[0026] Preferably, fusing the first sub-video data, the second sub-video data, and the third video data to obtain the quasi-target video data includes:

[0027] Fuse the first sub-video data, the second sub-video data, and the third video data in sequence to obtain quasi-target video data.

[0028] Preferably, extracting the target person features in the second sub-video data includes:

[0029] Identify the contour features of the target person in the second sub-video data to obtain the first contour;

[0030] Extract the first contour of the target person and its internal features to obtain the target person features.

[0031] Preferably, blurring the non-target person features in the quasi-target video data to obtain the target video data includes:

[0032] Perform a circle expansion process on the first contour of the target person to obtain the second contour;

[0033] Blur the features outside the second contour in the quasi-target video data to obtain the target video data.

[0034] In a second aspect, an Internet of Things system is further provided in an embodiment of the present application, including:

[0035] A first Internet of Things device, where the first Internet of Things device includes a user mobile terminal;

[0036] A second Internet of Things device, which is disposed at the entrance and exit of a preset place and is used to obtain video data of the entrance and exit;

[0037] A third Internet of Things device, which is disposed in the internal space of a preset place and is used to obtain video data of the internal space; and,

[0038] A service platform, where the service platform includes 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.

[0039] In a third aspect, a computer-readable storage medium is further provided in an embodiment of the present application, on which a computer program is stored, and when the computer program is executed by a processor, the method as described in the first aspect is implemented.

[0040] Different from the prior art, the Internet of Things data interaction method provided by the embodiments of the present application first obtains order information on a first Internet of Things device according to a request instruction; then extracts first sub-video data, second sub-video data, and third video data captured by a second Internet of Things device and a third Internet of Things device based on the order information; then performs data fusion on the first sub-video data, second sub-video data, and third video data to obtain quasi-target video data; then extracts target person features in the second sub-video data; then blurs non-target person features in the quasi-target video data to obtain target video data; finally, encrypts the target video data and sends it to the first Internet of Things device; that is, the user requests 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 the user obtaining the target video data can be improved, and the user can be prevented from missing the best lost item searching opportunity by spending a lot of time on the way. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on the structures shown in these drawings without creative efforts.

[0042] Figure 1 It is a schematic flowchart of the Internet of Things data interaction method in some embodiments of the present application;

[0043] Figure 2 It is a schematic diagram of the operation interface of the first Internet of Things device in some embodiments of the present application;

[0044] Figure 3 It is a schematic diagram of the order information on the first Internet of Things device in some embodiments of the present application;

[0045] Figure 4 It is a schematic diagram of the hardware structure of the Internet of Things system in some embodiments of the present application.

[0046] The implementation, functional features, and advantages of the objectives of the present invention will be further described in conjunction with the embodiments and with reference to the drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0047] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0048] It should be noted that all directional indications (such as up, down, left, right, front, back...) in the embodiments of the present invention are only used to explain the relative position relationship and movement conditions between components in a specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indications will also change accordingly.

[0049] In addition, the descriptions involving "first", "second", etc. in the present invention are only for descriptive purposes, and cannot be understood as indicating or implying their relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In addition, "and / or" throughout the text includes three scenarios. Taking A and / or B as an example, it includes the technical solution of A, the technical solution of B, and the technical solution that both A and B are satisfied at the same time. In addition, the technical solutions between various embodiments can be combined with each other, but it must be based on the ability of those of ordinary skill in the art to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the protection scope required by the present invention.

[0050] With the improvement of living standards, people's living rhythms are gradually accelerating. After people carry out multiple activities in different places, such as having a meal in a restaurant first and then going outdoors for outdoor activities, they often lose the items they carry with them (such as various bags, etc.). When they realize that an item is lost, the user doesn't know at which time and in which place it was lost. At this time, the user has also 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 staff and check the surveillance. However, after the user spends a lot of time checking the surveillance in the restaurant, it is found that the item was not lost in the restaurant, resulting in missing the best opportunity to find the lost item. Moreover, when viewing the relevant videos on site, it is inevitable to see the relevant videos of other users, exposing the privacy of other users.

[0051] In view of the above problems, the embodiments of the present application provide an Internet of Things system 100. Please refer to the attached Figure 4 , Figure 4This is a schematic diagram of the hardware structure of the Internet of Things system provided by an embodiment of the present application. The Internet of Things system includes a first Internet of Things device 110, and the first Internet of Things device includes a user mobile terminal, such as a mobile phone, etc., and the user can scan the code to order food on the mobile phone terminal; a second Internet of Things device 120, which is arranged at the entrance and exit of a preset place and is used to obtain video data of the entrance and exit; a third Internet of Things device 130, which is arranged in the internal space of the preset place and is used to obtain video data of the internal space.

[0052] Exemplarily, a first camera can be installed at the entrance and exit of a target place, such as a restaurant, to monitor the personnel entering and leaving the restaurant, and a second camera can be installed in the internal dining space of the target place, such as a restaurant, to monitor the dining situation of the personnel in the internal dining space.

[0053] An embodiment of the present application also provides an Internet of Things data interaction method, which is applied to the Internet of Things system 100. This method requests corresponding data on the user terminal through order information to accurately obtain the target video data, and the target video data is sent to the user terminal after being encrypted. In this way, the efficiency of the user obtaining the target video data can be improved, and the best time for finding lost items can be avoided by spending a lot of time on the way.

[0054] The following will mainly describe the specific steps based on the Internet of Things 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 executed in a different order from here. Please refer to the appendix Figure 1 The Internet of Things data interaction method includes the following steps:

[0055] S100. Respond to the request instruction of the first Internet of Things device for the target video data;

[0056] 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 they eat), they can directly obtain the target video data in the first Internet of Things device. For example, Figure 2 as shown, click "Video Request" on the terminal device such as a mobile phone.

[0057] S200. Obtain the order information on the first Internet of Things device;

[0058] When the system senses that the user clicks "Video Request", it obtains the order information on the first Internet of Things device. There are various ways to obtain the order information. For example, the system automatically obtains the latest order information. Another example is that the user inputs the order information into the corresponding module to obtain the order information through manual input by the user. It can also be a way of combining automatic acquisition and manual operation by the user to obtain the order information. In an embodiment of the present application, the obtaining of the order information on the first Internet of Things device includes:

[0059] S210. Send an order information request to the first Internet of Things device;

[0060] S220. Respond to the user's confirmation of the target order information on the first Internet of Things device;

[0061] S230. Obtain the target order information on the first Internet of Things device.

[0062] Exemplarily, after the system senses that the user clicks "Video Request", it sends an order information request to the first Internet of Things device. At this time, the system defaults to select the order information with the most recent time and highlights it. As Figure 2 shown, when the user clicks "Video Request", the mobile phone interface highlights Order 3. When the user clicks on the highlighted order information (Order 3), the order information is sent to the background.

[0063] S300. Extract the first sub-video data, second sub-video data, and third video data captured by the second Internet of Things device and the third Internet of Things device based on the order information;

[0064] In the embodiment of the present application, as Figure 3 shown, the order information includes an order number, an order placement time, a dining location, etc. Therefore, the video data corresponding to the corresponding time and location can be obtained according to the order information.

[0065] In one embodiment, extracting the first sub-video data, second sub-video data, and third video data captured by the second Internet of Things device and the third Internet of Things device based on the order information includes:

[0066] S310. Estimate the user's entry time, dining time, and departure time based on the order information;

[0067] Estimating the user's entry time, dining time, and departure time generally includes the following two steps: (1)

[0068] First, roughly estimate the rough entry time, dining time, and departure time based on the order placement time; (2) Perform front and back duration compensation on the rough entry time, dining time, and departure time respectively to obtain the user's entry time, dining time, and departure time.

[0069] Exemplarily, as Figure 3 shown, when the order payment time is 13:08, it can be inferred that the user probably entered the restaurant through the entrance at 13:03 by calculating 5 minutes forward, or it can be inferred that the user probably entered the restaurant through the entrance at 13:05 by calculating 3 minutes forward. The front and back compensation times can be determined by manual observation based on historical situations.

[0070] Similarly, the dining time can be calculated based on the order placement time and the meal preparation time, and the leaving time can be calculated based on the dining time. The specific calculation process is just a matter of addition and subtraction of time, which will not be elaborated here.

[0071] S320. According to the entering time and the leaving time, respectively extract the video data captured by the second Internet of Things device at the corresponding time to obtain the first sub-video data and the third video data;

[0072] Specifically, the system extracts the video data captured by the second Internet of Things device at the corresponding time set at the restaurant entrance and exit according to the user's entering time to obtain the first sub-video data; and extracts the video data captured by the second Internet of Things device at the corresponding time set at the restaurant entrance and exit according to the user's leaving time to obtain the third sub-video data; that is, the first video data is the video data at the user's entering time, and the third video data is the video data at the user's leaving time.

[0073] S330. According to the dining time and the dining location, extract the video data captured by the third Internet of Things device at the corresponding time and the corresponding location to obtain the second sub-video data.

[0074] Specifically, the dining location is as Figure 3 shown. 26 tables indicate the dining location; the system extracts the video data captured by the third Internet of Things device at the corresponding time and the corresponding location set in the restaurant internal space according to the dining time and the dining location to obtain the second video data, that is, the second video data is the video data when the user is dining.

[0075] S400. Perform data fusion on the first sub-video data, the second sub-video data, and the third video data to obtain the quasi-target video data;

[0076] To ensure the integrity of the target video data and facilitate the user to observe the state of the user himself (including items carried with him, such as bags, etc.) when entering the store, dining, and leaving the store, in the embodiments of the present application, after the system obtains the video data at the user's entering time (the first sub-video data), the video data when the user is dining (the second sub-video data), and the video data at the user's leaving time (the third sub-video data), it performs data fusion on the first sub-video data, the second sub-video data, and the third video data to obtain the 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, for the convenience of the user to observe the entire process from entering the store to leaving the store, the embodiments of the present application perform data fusion on the first sub-video data, the second sub-video data, and the third video data in the order before and after to obtain the quasi-target video data.

[0077] It can be understood that this quasi-target video data may contain the characteristics of other people besides the user. When the characteristics of other people are sent to the user terminal through the target video, the privacy of other users will be exposed, seriously affecting the privacy security of users.

[0078] S500. Extract the target person characteristics in the second sub-video data;

[0079] S600. Blur the non-target person characteristics in the quasi-target video data to obtain the target video data;

[0080] To solve the problem of exposing the privacy of other users, in the embodiments of the present application, the quasi-target video data is desensitized. Since the video data (second sub-video data) during the user's dining contains complete user characteristics, therefore, the desensitization process first extracts the person characteristics in the second sub-video data to obtain the target person characteristics; then blurs the non-target person characteristics in the quasi-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 the video data containing himself in the target video data, thus ensuring the privacy security of other users.

[0081] S700. Encrypt the target video data and send it to the first Internet of Things device, where the decryption password after the encryption process is the order number in the order information.

[0082] After obtaining the desensitized target video data, the system encrypts it through the encryption system and sends it to the first Internet of Things device that requests the video, that is, the mobile terminal such as the user's mobile phone. 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. In the embodiments of the present application, the order number in the order information is used as the decryption password, further ensuring the security of the transmission of the target video data.

[0083] In this way, the user only needs 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 on-site video. While ensuring data security and privacy security, it can improve the efficiency of the user to obtain the target video data and avoid missing the best opportunity to find lost items due to spending a lot of time on the road.

[0084] It can be understood that the dining time of the user depends on the amount of food ordered. The more things are ordered, the longer the dining time will be. Since the general dining time can be as long as 10 minutes or even longer, if the video data (the second sub-video data) during the dining time of 10 minutes or even longer is directly extracted, not only more powerful data processing capabilities are required, but also larger data storage spaces are needed. Therefore, in one embodiment, the extracting the video data captured by the third Internet of Things device at the corresponding time and corresponding location according to the dining time and dining location to obtain the second sub-video data includes:

[0085] S331. Start timing from the dining start time, and obtain a target image frame of the dining location every preset time interval;

[0086] S332. Perform data fusion on multiple target image frames in chronological order to obtain the second sub-video data.

[0087] Specifically, during the dining time period, first obtain a target image frame of the dining location every preset time interval (such as 2 minutes or 3 minutes), and then perform data fusion on multiple target image frames in chronological order to obtain the second sub-video data. In this way, key pictures are extracted to synthesize relevant videos according to the pictures, which can reduce the processing burden of the processor and the storage load of the memory while meeting the user's need to view their own situation.

[0088] In one embodiment, the extracting the target person features in the second sub-video data includes:

[0089] S510. Identify the contour features of the target person in the second sub-video data to obtain the first contour;

[0090] S520. Extract the first contour of the target person and its internal features to obtain the target person features.

[0091] Specifically, to effectively protect the privacy of other users in the video data, operations such as blurring and other hiding and desensitization operations need to be performed on the features of other people in the target video data. Therefore, the target person features need to be identified and extracted. In the embodiment of the present application, first, the contour features (the first contour) of the target person are obtained through feature recognition, and then the first contour of the target person and its internal features are extracted to obtain the target person features;

[0092] In other embodiments, after obtaining the target person feature, the non-target person features in the quasi-target video data may be blurred to obtain the target video data. The steps of the blurring process include: First, perform a circle expansion process on the first contour of the target person to obtain a second contour, for example, expand outward by 10 mm or 20 mm; then blur the features outside the second contour in the quasi-target video data to obtain the target video data. That is, perform an appropriate range expansion (circle expansion operation) on the target person feature, which can compensate for possible misidentifications to a certain extent to ensure the integrity of the target person feature, facilitating the user to view their own (carry-on items, including lost items) to determine whether the lost item was lost in the store.

[0093] As Figure 4 shown, an Internet of Things system 100 provided by 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;

[0094] Among them, the processor 141 is used to provide computing and control capabilities to enable the Internet of Things system to perform corresponding tasks. For example, control the Internet of Things system to execute the Internet of Things data interaction method in any of the above method embodiments. The method includes: responding to a request instruction of the first Internet of Things device for the target video data; obtaining order information on the first Internet of Things device, where 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 the target person feature in the second sub-video data; blurring the non-target person features in the quasi-target video data to obtain the target video data; encrypting the target video data and sending it to the first Internet of Things device, where the decryption password after the encryption process is the order number.

[0095] 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 Processing (DSP), an Application Specific Integrated Circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The above PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0096] The memory 142, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the method of determining operating parameters in the embodiments of the present application. By running the non-transitory software programs, instructions, and modules stored in the memory 142, the processor 141 can implement the Internet of Things data interaction method in any of the above method embodiments.

[0097] Specifically, the memory 142 may include volatile memory (VM), such as random access memory (RAM); the memory 142 may also include non-volatile memory (NVM), such as read-only memory (ROM), flash memory, a hard disk drive (HDD), or a solid-state drive (SSD), or other non-transitory solid-state storage devices; the memory 142 may further include a combination of the above types of memories.

[0098] In summary, the Internet of Things system of the present application adopts the technical solutions of any of the above embodiments of the Internet of Things data interaction method. Therefore, it has at least the beneficial effects brought by the technical solutions of the above embodiments, which will not be elaborated here one by one.

[0099] The embodiments of the present application also provide a computer-readable storage medium, such as a memory including program codes, and the above program codes can be executed by a processor to complete the Internet of Things data interaction method in the above embodiments. 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, etc.

[0100] The embodiments of the present application also provide a computer program product, which includes one or more program codes, and the program codes are stored in a computer-readable storage medium. The processor of the Internet of Things system reads the program codes from the computer-readable storage medium, and the processor executes the program codes to complete the steps of the Internet of Things data interaction method provided in the above embodiments.

[0101] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above embodiments can be completed by hardware, or can be completed by hardware related to program codes through a program. The program can be stored in a computer-readable storage medium, and the above-mentioned storage medium can be a read-only memory, a magnetic disk, or an optical disc, etc.

[0102] It should be noted that the system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0103] Through the description of the above embodiments, those of ordinary skill in the art can clearly understand that each embodiment can be implemented by means of software plus a general hardware platform, and of course, it can also be implemented by hardware. Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. 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 magnetic disk, an optical disc, a Read-Only Memory (ROM), or a Random Access Memory (RAM), etc.

[0104] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent structural transformation made under the inventive concept of the present invention by using the content of the specification and drawings of the present invention, or any direct / indirect application in other related technical fields is included in the patent protection scope of the present invention.

Claims

1. An Internet of Things data interaction method, characterized in that, Applied to the Internet of Things system, 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. 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 camera devices. The method includes: Responding to a request instruction of the first Internet of Things device for target video data; Obtaining order information on the first Internet of Things device; Extracting first sub-video data, second sub-video data, and 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, second sub-video data, and third video data to obtain quasi-target video data; Extracting target person features within the second sub-video data; Performing blurring processing on non-target person features within 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, where the decryption password after the encryption processing 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 further includes the order placement time and the dining location. The extracting the first sub-video data, second sub-video data, and third video data captured by the second Internet of Things device and the third Internet of Things device based on the order information includes: Estimating the user's entry time, dining time, and departure time based on the order information; According to the entry time and the departure time, respectively extracting the video data captured by the second Internet of Things device at the corresponding time to obtain the first sub-video data and the third video data; According to the dining time and the dining location, extracting the video data captured by the third Internet of Things device at the corresponding time and the corresponding location to obtain the second sub-video data.

3. The Internet of Things data interaction method according to claim 2, characterized in that, The estimating the user's entry time, dining time, and departure time based on the order information includes: Preliminarily estimating the rough entry time, dining time, and departure time according to the order placement time; Performing front and back duration compensation on the rough entry time, dining time, and departure time respectively to obtain the user's entry time, dining time, and departure time.

4. The Internet of Things data interaction method according to claim 2, characterized in that The extracting the video data captured by the third Internet of Things device at the corresponding time and the corresponding location to obtain the second sub-video data according to the dining time and the dining location includes: Starting to time from the dining start time, and obtaining a target image frame of the dining location every preset duration; Performing data fusion on multiple target image frames in chronological order to obtain the second sub-video data.

5. The Internet of Things data interaction method according to claim 1, characterized in that The obtaining the order information on the first Internet of Things device includes: Sending an order information request to the first Internet of Things device; Responding to the user's confirmation of the target order information on the first Internet of Things device; Obtaining the target order information on the first Internet of Things device.

6. The Internet of Things data interaction method according to claim 1, characterized in that The performing data fusion on the first sub-video data, second sub-video data, and third video data to obtain quasi-target video data includes: Performing data fusion in the front-back order of the first sub-video data, second sub-video data, and third video data to obtain quasi-target video data.

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

8. The Internet of Things data interaction method according to claim 7, wherein, Performing a blurring process on the non-target person features in the quasi-target video data to obtain the target video data, including: Performing an expanding circle process on the first contour of the target person to obtain a second contour; Performing a blurring process on the features outside the second contour in the quasi-target video data to obtain the target video data.

9. An Internet of Things system, characterized in that, Including: A first Internet of Things device, where the first Internet of Things device includes a user mobile terminal; A second Internet of Things device, which is arranged at the entrance and exit of a preset place and is used to obtain video data of the entrance and exit; A third Internet of Things device, which is arranged in the internal space of a preset place and is used to obtain video data of the internal space; And, A service platform, where the service platform includes a processor and a memory; wherein, the memory is used to store program codes, and the processor is used to call the program codes 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 the processor, it implements the method according to any one of claims 1 to 8.

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