Gesture-based cross-screen content transmission control system and method

Abstract

The invention relates to a cross-screen content transmission control system and method based on gestures. The method comprises the following steps: S1, collecting gestures and carrying out data preprocessing; s2, recognizing a gesture intention and generating an instruction; s3, positioning, extracting and packaging the content; s4, dynamically matching the target equipment; s5, executing an adaptive transmission protocol; and S6, performing security verification and content reconstruction. The method has the beneficial effects that through gesture interaction, the user operation cost is reduced, the applicability is improved, the optimal protocol can be selected and dynamically switched, the transmission stability in a complex network environment is ensured, and the applicability is improved.

Description

Technical Field

[0001] This invention relates to the field of smart terminal interaction and information transmission technology, specifically to a gesture-based cross-screen content transmission control system and method. Background Technology

[0002] With the widespread use of mobile phones, tablets, computers, smart TVs and other multi-terminal devices, users often need to transfer content between different devices. Content transfer often relies on manual operation of the devices, which increases the user's operating costs and requires a high level of proficiency in using the devices, resulting in poor applicability.

[0003] In existing technologies, content transmission largely relies on manual operation, which is cumbersome, requires a high level of proficiency in using the equipment, and has poor applicability. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this application proposes a gesture-based cross-screen content transmission control system and method. This system reduces user operation costs and improves applicability through gesture interaction. Furthermore, it can select the optimal protocol and dynamically switch between them to ensure transmission stability in complex network environments, thus enhancing applicability.

[0005] The following is the technical solution of the present invention: a gesture-based cross-screen content transmission control method, comprising the following steps: S1. Collect gestures and perform data preprocessing; S2. Recognize gesture intent and generate commands; S3. Locate, extract, and encapsulate the content; S4. Dynamically match target devices; S5. Execute the adaptive transmission protocol; S6. Perform security verification and content reconstruction.

[0006] As a preferred embodiment of the present invention, S1 includes the following steps: S101, The user performs a preset cross-device transfer gesture on the screen; S102. Activate the infrared camera, touch screen sensor and gyroscope to simultaneously collect the air trajectory, pinch position and direction of movement of the gesture; S103. Remove ambient light interference from the collected data and unify the coordinate system.

[0007] As a preferred embodiment of the present invention, S2 includes the following steps: S201. Call the deep learning model to compare trajectory, force, direction features and threshold; S202. If the match is successful, a transmission command is generated and the direction parameters are extracted; if it fails, an invalid message is returned. S203. Distribute instructions and parameters.

[0008] As a preferred embodiment of the present invention, S3 includes the following steps: S301, Locate a rectangular area of ​​the screen by pinching the position; S302: Text is converted into editable text using OCR, and pixel data is extracted from images; S303. Compress the content and add sensitive tags; S304. Sensitive information is identified through keyword matching, and sensitive information is set to high privacy.

[0009] As a preferred embodiment of the present invention, S4 includes the following steps: S401. Receive direction parameters, combine with the Bluetooth / WiFi device list and the same account login information to generate a candidate device set; S402. Determine the consistency between the device and the gesture direction by the signal strength; S403. Verify the account of the candidate device and output a unique target device identifier or a multi-device transmission queue.

[0010] As a preferred embodiment of the present invention, S5 includes the following steps: S501, Query the protocols supported by the target device; S502, a dynamic selection protocol based on rate and latency assessment; S503 uses AES-128 to encrypt data and transmits it to a single device or multiple devices according to the protocol.

[0011] As a preferred embodiment of the present invention, in S502, the dynamic selection of the protocol includes the following steps: S5021, Real-time monitoring of link quality; S5022, Switch protocol when the threshold is below; S5023, Enable resume download; As a preferred embodiment of the present invention, in S503, multi-device transmission according to the protocol includes the following steps: S5031. Sort the queues according to the priority of the target devices and network load; S5032, Time-division multiplexing transmission is adopted; S5033, Real-time progress feedback.

[0012] As a preferred embodiment of the present invention, S6 includes the following steps: S601. After receiving the data, perform hierarchical verification according to the sensitivity level; S602. Perform integrity verification; S603, Convert the content format to fit the target device screen.

[0013] A gesture-based cross-screen content transfer control system, comprising: The gesture acquisition module is used to collect the spatiotemporal characteristics of user gestures; The gesture recognition module is used to recognize gesture intentions and connects to the gesture acquisition module; The content extraction module is used to extract the content to be transmitted from the source device screen and convert it into a standardized data format, which is then connected to the gesture recognition module. The target device matching module matches target devices based on gesture direction, network environment, and account information, and connects to the gesture recognition module. The transmission protocol adaptation module selects the optimal transmission protocol and encrypts data based on the device connection status; the connection content extraction module and the target device matching module; The content reconstruction module is used to receive data and reconstruct content; The device status module is used to monitor the connection status of the device in real time and connect to the target device matching module; The security verification module verifies the sensitivity level of the transmitted content, requests user permissions from the target device based on the sensitivity level, and connects the transmission protocol adaptation module and the content reconstruction module. The beneficial effects of this invention are: 1. In this invention, gesture interaction eliminates the need for manual device and protocol selection, reducing user operating costs and improving applicability; 2. In this invention, the optimal protocol is adaptively selected and dynamic switching is supported, ensuring transmission stability in complex network environments and improving applicability; 3. In this invention, dynamic permission management based on content sensitivity levels protects private information and improves transmission security; 4. This invention supports multi-device queue transmission, improves the efficiency of multi-terminal collaboration, and enhances applicability. Attached Figure Description

[0014] Figure 1 This is a schematic diagram of the system connection of the present invention; Figure 2 This is a diagram illustrating the steps of the method of the present invention; Figure 3 This is a flowchart of the method of the present invention; In the diagram: 1. Gesture acquisition module; 2. Gesture recognition module; 3. Content extraction module; 4. Target device matching module; 5. Transmission protocol adaptation module; 6. Content reconstruction module; 7. Device status module; 8. Security verification module. Detailed Implementation

[0015] To make the technical problems solved by the present invention, the technical solutions adopted, and the technical effects achieved clearer, the technical solutions of the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Example 1

[0016] like Figure 1 As shown, a gesture-based cross-screen content transmission control system includes: The source device and the target device are connected via a network, Bluetooth, or account association channel; each device includes: Gesture acquisition module 1 is used to acquire the spatiotemporal characteristics of user gestures; Gesture recognition module 2 is used to recognize gesture intentions and is connected to gesture acquisition module 1; Content extraction module 3 is used to extract the content to be transmitted from the screen of the source device and convert it into a standardized data format, and connects to gesture recognition module 2; The target device matching module 4 matches the target device based on gesture direction, network environment, and account information, and is connected to the gesture recognition module 2. Transmission protocol adaptation module 5 selects the optimal transmission protocol and encrypts data according to the device connection status, connection content extraction module 3 and target device matching module 4; Content reconstruction module 6 is used to receive data and reconstruct content; Device status module 7 is used to monitor the connection status of the device in real time and connect to target device matching module 4; The security verification module 8 is used to verify the sensitivity level of the transmitted content, request user permissions from the target device according to the sensitivity level, and connects the transmission protocol adaptation module 5 and the content reconstruction module 6.

[0017] In this embodiment, the gesture acquisition module 1 is used to acquire the spatiotemporal features of user gestures, including gesture trajectory, force, direction of movement, and touch position. The gesture acquisition module 1 includes an infrared camera, a gyroscope, and a touchscreen sensor. The gesture acquisition module 1 is connected to the gesture recognition module 2 via a PCIe bus to transmit raw acquired data in real time.

[0018] The gesture acquisition module 1 detects user gesture triggers, such as screen touch and air movement; it simultaneously acquires image and motion data; and after denoising and normalization preprocessing, it outputs the data to the gesture recognition module.

[0019] In this embodiment, the gesture recognition module 2 is used to recognize gesture intentions and distinguish between cross-device and single-device operations. Gesture intentions include copying and transmitting, canceling transmission, etc. The gesture recognition module 2 includes a deep learning model and a gesture feature library. The deep learning model uses CNN and LSTM. The input end of the gesture recognition module 2 is connected to the gesture acquisition module 1, and the output end is connected to the content extraction module 3 and the target device matching module 4 via an internal bus.

[0020] The gesture recognition module 2 receives the preprocessed gesture features; compares them with the gesture feature library and infers through the model; and outputs the gesture intent and target device orientation information.

[0021] In this embodiment, the content extraction module 3 is used to extract the content to be transmitted from the source device screen and convert it into a standardized data format. The content to be transmitted includes text, images, etc. The content extraction module 3 includes a screen rendering analysis unit, an OCR recognition unit, an image cropping unit, and a sensitive content recognition unit. The input end of the content extraction module 3 is connected to the gesture recognition module 2 to receive extraction instructions, and the output end is connected to the transmission protocol adaptation module 5.

[0022] Content extraction module 3 locates the area to be transmitted based on the gesture trajectory, such as the gesture selection area; extracts text through OCR recognition or extracts images by pixels; and compresses and encapsulates it into a transmission data packet.

[0023] In this embodiment, the target device matching module 4 matches target devices based on gesture direction, network environment, and account information. The target device matching module 4 includes a device scanning unit, an account verification unit, and a distance sensing unit. The input end of the target device matching module 4 is connected to the gesture recognition module 2 and the device status module 7, and the output end is connected to the transmission protocol adaptation module 5.

[0024] The target device matching module 4 scans for surrounding devices via Bluetooth / WiFi signals and a list of devices under the same account; it filters candidate devices by combining gesture directions; it verifies device availability, such as online status and permissions; and it outputs the target device identifier.

[0025] In this embodiment, the transmission protocol adaptation module 5 selects the optimal transmission protocol based on the device connection status and encrypts the data. The transmission protocol adaptation module 5 includes a protocol detection unit, a dynamic switching unit, and an encryption unit. The input end of the transmission protocol adaptation module 5 is connected to the content extraction module 3 and the target device matching module 4, receiving data packets from the content extraction module 3 and the target identifier from the target device matching module 4.

[0026] The transmission protocol adaptation module 5 detects the transmission protocols supported by the target device, including Bluetooth BLE, WiFi Direct, and HTTP LAN protocol; evaluates protocol performance such as rate and latency; selects the optimal protocol and encrypts the data; establishes a transmission channel and sends the data.

[0027] In this embodiment, the content reconstruction module 6 receives data from the target device and reconstructs the content to adapt to the target device's screen size and format. The content reconstruction module 6 includes a format conversion unit, a display adaptation unit, and an integrity verification unit. The input end of the content reconstruction module 6 is connected to the source device security verification module 8 via an external interface, and the output end is connected to the target device display module.

[0028] Content reconstruction module 6 receives encrypted data and decrypts it; verifies data integrity via CRC; converts the format to suit image resolution and text layout; and outputs and displays the data.

[0029] In this embodiment, the device status module 7 monitors the device's connection status in real time, including network strength, Bluetooth pairing, and account login information. The device status module 7 includes a network status monitoring unit, a Bluetooth / WiFi status unit, and an account login status unit. The network status monitoring unit monitors network strength, the Bluetooth / WiFi status unit monitors Bluetooth pairing, and the account login status unit monitors account login information. The device status module 7 is bidirectionally connected to the target device matching module 4, pushing status data in real time.

[0030] In this embodiment, the security verification module 8 is used to verify the sensitivity level of the transmitted content and request user permissions from the target device according to the level; for example, private content requires confirmation. The security verification module 8 includes a permission management unit and an identity authentication unit. The security verification module 8 is connected in series between the transmission protocol adaptation module 5 and the content reconstruction module 6 to perform permission verification on the transmitted data.

[0031] The security verification module 8 receives the sensitivity level identifier from the content extraction module 3. The sensitivity level identifier includes public and private. For private content, it sends an authorization request to the target device. After successful verification, it allows transmission and reconstruction. Example 2

[0032] like Figure 2 and Figure 3 As shown, a gesture-based cross-screen content transfer control method includes the following steps: S1. Collect gestures and perform data preprocessing; S2. Recognize gesture intent and generate commands; S3. Locate, extract, and encapsulate the content; S4. Dynamically match target devices; S5. Execute the adaptive transmission protocol; S6. Perform security verification and content reconstruction.

[0033] In step S1, the gesture is collected and the data is preprocessed, including the following steps: S101, The user performs a preset cross-device transmission gesture on the source device screen; The default cross-device transfer gesture is to pinch the screen content with two fingers and slide it toward the target device.

[0034] S102. Activate the infrared camera, touch screen sensor and gyroscope to simultaneously collect the air trajectory, pinch position and direction of movement of the gesture; The source device gesture acquisition module 1 activates the infrared camera to capture the air sliding trajectory, activates the touch screen sensor to capture the pinch position, activates the gyroscope to capture the direction of movement, and simultaneously collects the spatiotemporal feature data of the gesture.

[0035] S103. Remove ambient light interference from the collected data and unify the coordinate system.

[0036] The collected data is preprocessed, including removing ambient light interference and unifying the coordinate system, and then output to the gesture recognition module 2.

[0037] In step S2, the gesture intent is recognized and a command is generated, including the following steps: S201. Call the deep learning model to compare trajectory, force, direction features and threshold; The gesture recognition module 2 calls a deep learning model to compare the collected gesture features with a preset gesture feature library, including trajectory, force, and direction thresholds.

[0038] S202. If the match is successful, a transmission command is generated and the direction parameters are extracted; if it fails, an invalid message is returned. If the match is successful, a command for cross-device content transfer is generated, and gesture direction parameters, such as the azimuth angle pointing to the target device, are extracted; if the match fails, an invalid operation message is returned.

[0039] S203. Distribute instructions and parameters; The instructions and direction parameters are sent to the content extraction module 3 and the target device matching module 4, respectively.

[0040] Step S3 involves locating, extracting, and encapsulating the content, including the following steps: S301, Locate a rectangular area of ​​the screen by pinching the position; The content extraction module 3 locates the area to be transmitted based on the gesture pinch position, which is a rectangular range from screen coordinates (x1, y1) to (x2, y2).

[0041] S302: Text is converted into editable text using OCR, and pixel data is extracted from images; If the area contains text, the OCR recognition unit is activated to convert it into editable text; if it contains an image, the image cropping unit is activated to extract pixel data.

[0042] S303. Compress the content and add sensitive tags; The extracted content is compressed, images are in WebP format, text is encapsulated in JSON, and a sensitivity level label is added. The content is automatically marked as highly private, private, or public through content recognition, and then output to the transmission protocol adaptation module 5.

[0043] S304. Sensitive information is identified through keyword matching, and sensitive information labels are set to high privacy. The sensitive content identification unit identifies sensitive content such as ID card numbers and passwords through keyword matching and automatically upgrades the sensitivity level to high privacy.

[0044] In step S4, dynamically matching the target device includes the following steps: S401. Receive direction parameters, combine with the Bluetooth / WiFi device list and the same account login information to generate a candidate device set; The target device matching module 4 receives the gesture direction parameters and combines them with real-time data such as the list of devices within the Bluetooth / WiFi range and devices logged in with the same account from the device status module 7 to filter candidate devices.

[0045] S402. Determine the consistency between the device and the gesture direction by the signal strength; The consistency between the candidate device and the gesture direction is determined by the RSSI value of the distance sensing unit, with a direction error ≤30°.

[0046] S403. Verify the account of the candidate device and output a unique target device identifier or a multi-device transmission queue. For the selected devices, the account verification unit confirms whether they belong to the same account and outputs a unique target device identifier, which can be a MAC address or a device name. If it is a single device, output a unique target device identifier; if it is multiple devices, generate a transmission queue and output multiple unique target device identifiers in sequence.

[0047] In step S5, the adaptive transport protocol is executed, including the following steps: S501, Query the protocols supported by the target device; The transmission protocol adaptation module 5 receives the target device identifier, and the device status query module 7 obtains the transmission protocols supported by the target device, including Bluetooth BLE, WiFi Direct, and LAN HTTP.

[0048] S502, a dynamic selection protocol based on rate and latency assessment; Evaluate the performance of each protocol, perform dynamic protocol selection, and prioritize high-speed, low-latency protocols; For example, WiFi Direct has a speed of 10Mbps and a latency of 50ms, Bluetooth has a speed of 2Mbps and a latency of 200ms, so choose WiFi Direct.

[0049] In step S502, dynamic protocol selection is performed, link quality is monitored in real time, the protocol is switched when it falls below a threshold, and breakpoint resumption is enabled, including the following steps: S5021, Real-time monitoring of link quality; During transmission, the protocol detection unit monitors the quality of the current transmission link in real time, including packet loss rate and latency.

[0050] S5022, Switch protocol when the threshold is below; If the link quality is below the threshold, the dynamic switching unit will activate the alternative protocol.

[0051] S5023, Enable resume download; During the handover process, the number of bytes transmitted is recorded through a breakpoint resume mechanism to avoid data retransmission and ensure transmission continuity.

[0052] S503 uses AES-128 to encrypt data and transmits it to a single or multiple devices according to the protocol. The encryption unit uses the AES-128 algorithm to encrypt content data packets, establishes a transmission channel based on a selected protocol, and sends data to one or more target devices.

[0053] In step S503, data is sent to multiple target devices. When there are multiple targets, the transmission is time-division multiplexed according to priority, and the progress is fed back in real time. This includes the following steps: S5031. Sort the queues according to the priority of the target devices and network load; The transmission protocol adaptation module 5 sorts the queues according to the priority of several target devices and network load; S5032, Time-division multiplexing transmission is adopted; Time-division multiplexing transmission is used to avoid a single device occupying all the bandwidth; For example, 50% of the data can be transmitted to device A first, then 50% to device B, and so on, alternating between the two. S5033, Real-time progress feedback; The queue progress is fed back to the source device in real time; for example, device A has completed the transmission, while device B is at 30% progress.

[0054] In step S6, security verification and content reconstruction are performed, including the following steps: S601. After receiving the data, perform hierarchical verification according to the sensitivity level; The target device transmission protocol adaptation module 5 receives encrypted data, decrypts it, and sends it to the security verification module 8. Security verification module 8 implements tiered permissions based on sensitivity level: public content is transmitted directly; private content requires confirmation from the target device user; highly private content requires the target device to enter a verification code. If the authorization verification times out, the transmission will be automatically terminated and a transmission failure report will be sent to the source device.

[0055] S602. Perform integrity verification; The content reconstruction module 6 confirms that no data is lost through the integrity verification unit.

[0056] S603. Convert the content format to suit the target device screen; the format conversion unit adapts to the target device screen parameters and performs text layout; the reconstructed content is output to the target device display module to complete the transmission. Example 3

[0057] This embodiment applies to a scenario involving mobile phones, tablets, and smart TVs in a conference room, and adopts the system of Embodiment 1 and the method of Embodiment 2.

[0058] A user with a mobile phone, logged into account A, views a meeting document on the phone and needs to simultaneously transfer the document to a tablet and a smart TV on the same local network. The tablet is logged into account A, while the smart TV is not logged into an account, and Bluetooth pairing is complete. The user performs a gesture: pinching the document area with two fingers and simultaneously swiping towards both the tablet and the TV.

[0059] The phone's camera captures the swipe trajectory, the touchscreen locates the pinch area, and the gyroscope records the direction. Confirming the intent is to transfer a document to the tablet and TV, the system outputs the target direction and device name. It extracts the document's text and images, marks them as public content, and compresses them into a data packet. Upon scanning for the tablet (with a WiFi signal strength of -50dBm and a TV signal strength of -60dBm), a transmission queue is created prioritizing the tablet's transmission. The system also detects that the tablet supports WiFi Direct and the TV supports Bluetooth BLE, selecting the corresponding protocol and encrypting the data.

[0060] First, 50% of the data is transmitted to the tablet, then the remaining 50% is transmitted to the TV, alternating between time-division multiplexing. During transmission, if the tablet's WiFi link briefly deteriorates and the packet loss rate exceeds the threshold, it automatically switches to the local area network TCP protocol and resumes the remaining transmission. After the tablet receives the data, security verification module 8 passes directly due to its open-access status; it adapts to the target device's screen parameters, performs text formatting, and displays a pop-up indicating successful reception. After the smart TV receives the data, security verification module 8 passes directly due to its open-access status; the video is paused and the content is displayed. A pop-up message from the source device indicates that both the tablet and TV transmissions are complete.

[0061] In this invention, gesture interaction eliminates the need for manual device and protocol selection, reducing user operating costs and improving applicability; adaptive selection of the optimal protocol and support for dynamic switching ensure transmission stability in complex network environments, further enhancing applicability; dynamic permission management based on content sensitivity levels protects private information, improving transmission security; and support for multi-device queue transmission improves multi-terminal collaboration efficiency, further enhancing applicability.

[0062] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Clearly, those skilled in the art can make various alterations and variations to the invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of equivalents of the invention, the invention is also intended to include these modifications and variations.

Claims

1. A gesture-based cross-screen content transmission control method, characterized in that, Includes the following steps: S1. Collect gestures and perform data preprocessing; S2. Recognize gesture intent and generate commands; S3. Locate, extract, and encapsulate the content; S4. Dynamically match target devices; S5. Execute the adaptive transmission protocol; S6. Perform security verification and content reconstruction.

2. The gesture-based cross-screen content transmission control method according to claim 1, characterized in that, S1 includes the following steps: S101, The user performs a preset cross-device transfer gesture on the screen; S102. Activate the infrared camera, touch screen sensor and gyroscope to simultaneously collect the air trajectory, pinch position and direction of movement of the gesture; S103. Remove ambient light interference from the collected data and unify the coordinate system.

3. The gesture-based cross-screen content transmission control method according to claim 1, characterized in that, S2 includes the following steps: S201. Call the deep learning model to compare trajectory, force, direction features and threshold; S202. If the match is successful, a transmission command is generated and the direction parameters are extracted; if it fails, an invalid message is returned. S203. Distribute instructions and parameters.

4. The gesture-based cross-screen content transmission control method according to claim 3, characterized in that, S3 includes the following steps: S301, Locate a rectangular area of ​​the screen by pinching the position; S302: Text is converted into editable text using OCR, and pixel data is extracted from images; S303. Compress the content and add sensitive tags; S304. Sensitive information is identified through keyword matching, and sensitive information is set to high privacy.

5. The gesture-based cross-screen content transmission control method according to claim 4, characterized in that, S4 includes the following steps: S401. Receive direction parameters, combine with the Bluetooth / WiFi device list and the same account login information to generate a candidate device set; S402. Determine the consistency between the device and the gesture direction by the signal strength; S403. Verify the account of the candidate device and output a unique target device identifier or a multi-device transmission queue.

6. The gesture-based cross-screen content transmission control method according to claim 5, characterized in that, S5 includes the following steps: S501, Query the protocols supported by the target device; S502, a dynamic selection protocol based on rate and latency assessment; S503 uses AES-128 to encrypt data and transmits it to a single device or multiple devices according to the protocol.

7. The gesture-based cross-screen content transmission control method according to claim 6, characterized in that, In S502, the dynamic selection of the protocol includes the following steps: S5021, Real-time monitoring of link quality; S5022, Switch protocol when the threshold is below; S5023, Enable resume download.

8. The gesture-based cross-screen content transmission control method according to claim 6, characterized in that, In S503, multi-device transmission according to the protocol includes the following steps: S5031. Sort the queues according to the priority of the target devices and network load; S5032, Time-division multiplexing transmission is adopted; S5033, Real-time progress feedback.

9. A gesture-based cross-screen content transmission control method according to claim 6, characterized in that, S6 includes the following steps: S601. After receiving the data, perform hierarchical verification according to the sensitivity level; S602. Perform integrity verification; S603, Convert the content format to fit the target device screen.

10. A gesture-based cross-screen content transmission control system, applicable to the gesture-based cross-screen content transmission control method according to any one of claims 1-9, characterized in that, include: The gesture acquisition module is used to collect the spatiotemporal characteristics of user gestures; The gesture recognition module is used to recognize gesture intentions and connects to the gesture acquisition module; The content extraction module is used to extract the content to be transmitted from the source device screen and convert it into a standardized data format, which is then connected to the gesture recognition module. The target device matching module matches target devices based on gesture direction, network environment, and account information, and connects to the gesture recognition module. The transmission protocol adaptation module selects the optimal transmission protocol and encrypts data based on the device connection status; the connection content extraction module and the target device matching module; The content reconstruction module is used to receive data and reconstruct content; The device status module is used to monitor the connection status of the device in real time and connect to the target device matching module; The security verification module is used to verify the sensitivity level of the transmitted content, request user permissions from the target device according to the sensitivity level, and connect the transmission protocol adaptation module and the content reconstruction module.

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