Doorbell remote sensing method and device based on dynamic scene and medium

Abstract

The invention discloses a doorbell remote sensing method and device based on a dynamic scene and a medium, and the method comprises the steps: obtaining multi-modal environment sensing data, and carrying out the multi-modal fusion analysis of the multi-modal environment sensing data, so as to obtain abnormal behavior grade data; performing abnormal grade threshold analysis on the abnormal behavior grade data to determine doorbell state parameters; based on the doorbell state parameter, a first door lock control instruction is obtained through following state judgment; performing DES encryption on the user remote control instruction to obtain cloud doorbell service data; according to the cloud doorbell service data, a second door lock control instruction is obtained through door lock remote control analysis; and performing multi-level arbitration analysis on the first door lock control instruction and the second door lock control instruction to determine a real door lock control instruction. Through the method, the technical problem that the absolute instruction cannot be judged when the door lock control instruction corresponding to the doorbell is repeated in the prior art is solved.

Description

Technical Field

[0001] This application relates to the field of remote sensing technology, and in particular, to a doorbell remote sensing method, device, and medium based on a dynamic scenario. Background Art

[0002] In recent years, with the deep integration of Internet of Things and artificial intelligence technologies, smart door locks have gradually become the core entry point for smart home security. The intelligent upgrade of traditional door locks has developed from single biometric identification to multi-modal perception, remote control, and scenario-based linkage. According to statistics, the global smart door lock market size exceeded $10 billion in 2023, and products with remote control functions accounted for more than 75%. With the increase in functional complexity, security issues in multi-instruction concurrent scenarios have become increasingly prominent.

[0003] When a user approaches the door lock and triggers local automatic unlocking, if they encounter malicious remote attacks or interference from misoperation instructions, traditional solutions often adopt simple priority strategies and are difficult to cope with new attack methods such as forged positioning and biometric impersonation. In the prior art, since the permissions of doorbell users and door lock control are not interconnected, the analysis of the same doorbell instruction relies on a single biometric or location information, and it is impossible to determine an absolute instruction when the door lock control instructions corresponding to the doorbell are repeated. Summary of the Invention

[0004] Embodiments of this application provide a doorbell remote sensing method, device, and medium based on a dynamic scenario, which solve the technical problem that the prior art cannot determine an absolute instruction when the door lock control instructions corresponding to the doorbell are repeated.

[0005] In a first aspect, embodiments of this application provide a doorbell remote sensing method based on a dynamic scenario, which is characterized in that the method includes: obtaining multi-modal environmental perception data, and performing multi-modal fusion analysis on the multi-modal environmental perception data to obtain abnormal behavior level data; performing abnormal level threshold analysis on the abnormal behavior level data to determine doorbell state parameters; based on the doorbell state parameters, obtaining a first door lock control instruction through trailing state judgment; obtaining a user remote control instruction, and performing DES encryption on the user remote control instruction to obtain cloud doorbell service data; according to the cloud doorbell service data, obtaining a second door lock control instruction through door lock remote control parsing; and performing multi-level arbitration analysis on the first door lock control instruction and the second door lock control instruction to determine the true door lock control instruction.

[0006] In an implementation manner of the present application, multi-modal fusion analysis is performed on multi-modal environment perception data to obtain abnormal behavior level data, which specifically includes: performing multi-modal data alignment on the multi-modal environment perception data to obtain spatio-temporal consistent environment data; wherein, the spatio-temporal consistent environment data includes: visible light video stream, three-dimensional depth data, thermal imaging data, and voiceprint feature vector; performing cross-modal abnormal detection on the spatio-temporal consistent environment data to determine environment abnormal detection parameters; wherein, the cross-modal abnormal detection includes: human key point detection, thermal radiation feature detection, three-dimensional movement speed detection, and voiceprint cosine similarity analysis; based on environment monitoring, abnormal behavior level data is obtained through environment abnormal behavior level recognition.

[0007] In an implementation manner of the present application, abnormal level threshold analysis is performed on the abnormal behavior level data to determine the doorbell state parameter, which specifically includes: performing abnormal state threshold determination on the abnormal behavior level data to determine the positioning activation instruction; based on the positioning activation instruction, the user device movement trajectory data is obtained through monitoring the relative position of the user device; when the distance between the door lock and the user device movement trajectory data is less than the preset radius, the verification state parameter is determined through biometric verification; the doorbell instruction matching is performed on the verification state parameter to determine the doorbell state parameter.

[0008] In an implementation manner of the present application, based on the doorbell state parameter, the first door lock control instruction is obtained through trailing state judgment, which specifically includes: generating a pre-unlock instruction based on the doorbell state parameter, and obtaining the user's trailing state through trailing state detection according to the pre-unlock instruction; when the user's trailing state is not being trailed, the pre-unlock instruction is converted into an unlock instruction; when the user's trailing state is being trailed, the pre-unlock instruction is converted into a pause unlock instruction, and the trailing state of being trailed is sent to the user device end; according to the unlock instruction or the pause unlock instruction, the first door lock control instruction is obtained.

[0009] In an implementation manner of the present application, DES encryption is performed on the user remote control instruction to obtain cloud doorbell service data, which specifically includes: performing plaintext IP replacement on the user remote control instruction, and performing key control iteration on the replacement result obtained by the plaintext IP replacement to obtain key iteration data; performing 32-bit swapping on the key iteration data to obtain a data block to be replaced; based on the data block to be replaced, through IP -1 replacement, cloud doorbell service data is obtained.

[0010] In an implementation manner of the present application, according to the cloud doorbell service data, the second door lock control instruction is obtained through door lock remote control parsing, which specifically includes: decrypting the cloud doorbell service data through the SM4 algorithm to obtain the user unique identifier; based on the user unique identifier, the second door lock control instruction is obtained through user instruction analysis.

[0011] In an implementation manner of the present application, multi-level arbitration analysis is performed on the first door lock control instruction and the second door lock control instruction to determine the true door lock control instruction, which specifically includes: based on the first door lock control instruction and the second door lock control instruction, an instruction conflict signal is obtained through spatio-temporal consistency verification; according to the instruction conflict signal, the behavior credibility is determined through dynamic priority decision analysis; wherein, the dynamic priority decision analysis includes: biometric cross-verification, behavior pattern analysis, and priority decision; based on the behavior credibility, the true door lock control instruction is determined through an instruction source verification request.

[0012] In an implementation manner of the present application, after performing multi-level arbitration analysis on the first door lock control instruction and the second door lock control instruction to determine the true door lock control instruction, the method further includes: based on the true door lock control instruction, multi-level arbitration optimization weights are obtained through dynamic weight optimization; according to the multi-level arbitration optimization weights, a multi-level arbitration strategy is obtained through arbitration iterative verification.

[0013] In a second aspect, an embodiment of the present application further provides a doorbell remote sensing device based on a dynamic scenario, characterized in that the device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor is enabled to: obtain multi-modal environment perception data, and perform multi-modal fusion analysis on the multi-modal environment perception data to obtain abnormal behavior level data; perform abnormal level threshold analysis on the abnormal behavior level data to determine doorbell state parameters; based on the doorbell state parameters, obtain the first door lock control instruction through trailing state judgment; obtain a user remote control instruction, and perform DES encryption on the user remote control instruction to obtain cloud doorbell service data; according to the cloud doorbell service data, obtain the second door lock control instruction through door lock remote control parsing; perform multi-level arbitration analysis on the first door lock control instruction and the second door lock control instruction to determine the true door lock control instruction.

[0014] In a third aspect, an embodiment of the present application further provides a non-volatile computer storage medium for remote sensing of a doorbell based on a dynamic scenario, storing computer-executable instructions, characterized in that the computer-executable instructions are set to: obtain multi-modal environment perception data, and perform multi-modal fusion analysis on the multi-modal environment perception data to obtain abnormal behavior level data; perform abnormal level threshold analysis on the abnormal behavior level data to determine doorbell state parameters; based on the doorbell state parameters, obtain a first door lock control instruction through trailing state judgment; obtain a user remote control instruction, and perform DES encryption on the user remote control instruction to obtain cloud doorbell service data; according to the cloud doorbell service data, obtain a second door lock control instruction through door lock remote control parsing; perform multi-level arbitration analysis on the first door lock control instruction and the second door lock control instruction to determine the true door lock control instruction.

[0015] An embodiment of the present application provides a method, device and medium for remote sensing of a doorbell based on a dynamic scenario. Through multi-modal environment anomaly perception and multi-level arbitration analysis of door lock control instructions, it solves the technical problem that the prior art cannot determine an absolute instruction when the door lock control instructions corresponding to the doorbell are repeated, realizes the determination of an absolute instruction when the door lock control instructions are repeated, and improves the security of remote sensing of the intelligent doorbell and the execution of door lock instructions. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present application, and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application, and do not constitute an improper limitation to the present application. In the drawings:

[0017] Figure 1 It is a flowchart of a method for remote sensing of a doorbell based on a dynamic scenario provided by an embodiment of the present application;

[0018] Figure 2 It is a schematic internal structure diagram of a device for remote sensing of a doorbell based on a dynamic scenario provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] To make the objectives, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be clearly and completely described below in conjunction with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0020] The embodiments of the present application provide a doorbell remote sensing method, device, and medium based on a dynamic scenario. By means of multi-modal environmental anomaly perception and multi-level arbitration analysis of door lock control instructions, the technical problem in the prior art that it is impossible to determine an absolute instruction when door lock control instructions corresponding to the doorbell are repeated is solved. The determination of an absolute instruction when door lock control instructions are repeated is realized, and the security of intelligent doorbell remote sensing and door lock instruction execution is improved.

[0021] The technical solutions proposed in the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0022] Figure 1 It is a flowchart of a doorbell remote sensing method based on a dynamic scenario provided by the embodiments of the present application. As Figure 1 shown, a doorbell remote sensing method based on a dynamic scenario provided by the embodiments of the present application specifically includes the following steps:

[0023] Step 101: Obtain multi-modal environmental perception data, and perform multi-modal fusion analysis on the multi-modal environmental perception data to obtain abnormal behavior level data.

[0024] Exemplarily, multi-modal environmental perception data is obtained through a visible light camera, a thermal imaging sensor, a depth sensor, and a voiceprint recognition array, and multi-modal fusion analysis is performed on the multi-modal environmental perception data to realize multi-modal abnormal behavior perception and determination of the risk level of abnormal behavior in the environment where the doorbell and the door lock are located.

[0025] Specifically, performing multi-modal fusion analysis on the multi-modal environmental perception data to obtain abnormal behavior level data includes: performing multi-modal data alignment on the multi-modal environmental perception data to obtain spatio-temporal consistent environmental data; wherein, the spatio-temporal consistent environmental data includes: visible light video stream, three-dimensional depth data, thermal imaging data, voiceprint feature vector; performing cross-modal anomaly detection on the spatio-temporal consistent environmental data to determine environmental anomaly detection parameters; wherein, the cross-modal anomaly detection includes: human key point detection, thermal radiation feature detection, three-dimensional movement speed detection, voiceprint cosine similarity analysis; based on environmental monitoring, obtaining abnormal behavior level data through environmental abnormal behavior level recognition.

[0026] In one embodiment, first, the door lock and the doorbell main body are integrated with a four-dimensional perception module. The visible light camera collects a 1080P resolution video stream at a frame rate of 30fps, and switches to the infrared night vision mode when the ambient light intensity is lower than 10 lux. At the same time, a temperature distribution matrix is generated through the thermal imaging sensor to detect the human target temperature range to exclude interference from animals or objects.

[0027] The depth sensor and the voiceprint recognition array respectively obtain the three-dimensional movement speed detection and the voiceprint feature vector, and output spatio-temporal consistent environmental data after timestamp alignment.

[0028] Then, environmental anomaly detection is carried out through a cross-modal feature fusion algorithm. Based on the live detection branch of the improved YOLOv5, forged face attacks are identified and a binary decision signal is output. Through the voiceprint-face joint verification branch, the similarity with the pre-stored feature template is calculated.

[0029] Finally, through the behavior analysis branch, an anomaly level signal is generated based on the acceleration of the point cloud trajectory and the change frequency of the thermal imaging area.

[0030] Step 102: Analyze the anomaly level threshold of the anomaly behavior level data to determine the doorbell status parameter.

[0031] Exemplarily, analyze the anomaly level threshold of the anomaly behavior level data to determine the anomaly level, and monitor the user's location and movement trajectory according to the anomaly level. For users or operators, the usage status of a manual doorbell is usually in front of the door. To meet the monitoring of abnormal states and ensure user dynamic security, further status verification is required within the safe area in front of the door.

[0032] Specifically, analyze the anomaly level threshold of the anomaly behavior level data to determine the doorbell status parameter, including: determining the positioning activation instruction by judging the anomaly status threshold of the anomaly behavior level data; obtaining the user device movement trajectory data through the relative position monitoring of the user device based on the positioning activation instruction; when the distance between the door lock in the user device movement trajectory data is less than the preset radius, determine the verification status parameter through biometric verification; match the doorbell instruction with the verification status parameter to determine the doorbell status parameter.

[0033] In one embodiment, when the anomaly level ≥ 2, the time difference of arrival data of the user's mobile phone is received through the positioning array of three-dimensional positioning, and its three-dimensional space coordinates are solved. The moving trajectory is predicted by combining the Kalman filter algorithm. When it is detected that the user's approaching speed > 1.5 m / s, it is marked as a suspicious behavior, and the user device movement trajectory data is obtained.

[0034] Then, when the user device movement trajectory data indicates that the user enters the spherical safety area with a radius of 1 meter centered on the door lock, biometric verification is triggered, and the user's face depth information is collected.

[0035] The collected status parameter is phase-compared with the template data encrypted and stored locally. When the matching degree ≥ 97%, a verification success signal is output. Otherwise, an audible and visual alarm is triggered and a failure record is uploaded to the cloud.

[0036] Finally, when the matching degree verification is successful, the doorbell status is activated, and it is determined that the current doorbell user is a user with the doorbell usage permission.

[0037] Step 103: Based on the doorbell status parameters, obtain the first door lock control instruction through trailing status judgment.

[0038] Exemplarily, after the determination result that the doorbell can be used is determined, through trailing status judgment, it is judged whether there is an abnormal trailing situation behind the current user, which improves the security of the doorbell's remote sensing. And since the trailing status judgment is only executed after the determination result that the doorbell can be used is determined, it can further reduce the overall system energy consumption of the remote sensing.

[0039] Specifically, based on the doorbell status parameters, obtaining the first door lock control instruction through trailing status judgment includes: generating a pre-unlock instruction based on the doorbell status parameters, and through trailing status detection according to the pre-unlock instruction, obtaining the user's trailed status; when the user's trailed status is not trailed, converting the pre-unlock instruction into an unlock instruction; when the user's trailed status is trailed, converting the pre-unlock instruction into a pause unlock instruction, and sending the trailed status to the user device side; obtaining the first door lock control instruction according to the unlock instruction or the pause unlock instruction.

[0040] In one embodiment, if a speed-matching target (the difference from the user's moving speed ≤ 0.5 m / s and the direction is the same) is detected within 2 meters behind the user, it is marked as a potential trailing object; synchronously activate the thermal imaging sensor to collect the temperature distribution matrix of the target area, and exclude non-human target interference through threshold filtering.

[0041] Further, if there are ≥ 2 objects that meet the human body temperature zone and motion characteristics continuously in the target area for more than 5 seconds, it is determined as the trailed status, otherwise it is marked as the safe status.

[0042] After the pre-unlock instruction is generated, the system makes a dynamic decision according to the trailing detection result: in the non-trailed state (confidence level ≥ 90%), convert the pre-unlock instruction into a motor drive signal, control the lock tongue to retract to complete the unlocking action, and generate an operation log including the timestamp, user ID, and environmental snapshot.

[0043] Further, if it is determined as the trailed status, freeze the pre-unlock instruction, trigger the buzzer alarm at the door lock end and push a warning notice to the user's mobile phone APP. Finally, obtain the first door lock control instruction according to the unlock instruction or the pause unlock instruction.

[0044] Step 104: Obtain the user's remote control instruction and perform DES encryption on the user's remote control instruction to obtain the cloud doorbell service data.

[0045] Exemplarily,

[0046] Specifically, the user's remote control instruction is encrypted by DES to obtain cloud doorbell service data, including: performing a plaintext IP permutation on the user's remote control instruction, and performing a key-controlled iteration on the permutation result obtained by the plaintext IP permutation to obtain key iteration data; performing a 32-bit swap on the key iteration data to obtain a data block to be permuted; based on the data block to be permuted, through IP -1 permutation to obtain cloud doorbell service data.

[0047] In one embodiment, in the Feistel network of DES, each round of iterative processing divides the data block into a left 32-bit part and a right 32-bit part. In each round (a total of 16 rounds), the right half is processed by the F function and then XORed with the left half to generate a new right half, and the left half is directly copied to the right half of the next round.

[0048] In the last step of DES encryption, after 16 rounds of Feistel network processing, a 64-bit intermediate data block is obtained. To restore the original permutation order of the data block, IP -1 permutation needs to be performed, which is the inverse operation of the initial permutation (plaintext IP permutation).

[0049] Step 105: According to the cloud doorbell service data, through door lock remote control parsing, obtain a second door lock control instruction.

[0050] Specifically, according to the cloud doorbell service data, through door lock remote control parsing, obtaining a second door lock control instruction includes: decrypting the cloud doorbell service data by the SM4 algorithm to obtain a user unique identifier; based on the user unique identifier, through user instruction analysis, obtaining a second door lock control instruction.

[0051] Step 106: Perform multi-level arbitration analysis on the first door lock control instruction and the second door lock control instruction to determine the true door lock control instruction.

[0052] Exemplarily, by performing multi-level arbitration analysis on the first door lock control instruction and the second door lock control instruction to determine the true door lock control instruction, the technical problem in the prior art that it is impossible to determine an absolute instruction when the door lock control instructions corresponding to the doorbell are repeated is solved, the determination of an absolute instruction when the door lock control instructions are repeated is realized, and the security of intelligent doorbell remote sensing and door lock instruction execution is improved.

[0053] Specifically, perform multi-level arbitration analysis on the first door lock control instruction and the second door lock control instruction to determine the true door lock control instruction, including: based on the first door lock control instruction and the second door lock control instruction, obtain an instruction conflict signal through spatio-temporal consistency verification; according to the instruction conflict signal, determine the behavior credibility through dynamic priority decision analysis; wherein, the dynamic priority decision analysis includes: biometric cross-verification, behavior pattern analysis, and priority decision; based on the behavior credibility, determine the true door lock control instruction through an instruction source verification request.

[0054] Further, after performing multi-level arbitration analysis on the first door lock control instruction and the second door lock control instruction to determine the true door lock control instruction, the method further includes: based on the true door lock control instruction, obtain multi-level arbitration optimization weights through dynamic weight optimization; according to the multi-level arbitration optimization weights, obtain a multi-level arbitration strategy through arbitration iterative verification.

[0055] In one embodiment, for the conflict scenario between the remote control instruction and the local trigger instruction when the user approaches the door lock, a secure arbitration is achieved through a multi-dimensional spatio-temporal logic verification and dynamic priority decision mechanism, and data collection is mainly achieved through three-dimensional positioning and biometric collection.

[0056] When an instruction conflict unlocking request is detected, start the multi-level arbitration process. First, through spatio-temporal consistency verification, compare the instruction trigger time with the user's real-time position data, obtain the spatial coordinates of the user's mobile phone. If the distance between the user device's GPS position and the door lock is > 100 meters and the signal delay is > 500 ms when the remote instruction is sent, it is marked as a suspicious remote instruction.

[0057] Then, activate dual detection through biometric cross-verification. Collect the face depth information through the optical camera at the door lock end and compare it with the locally pre-stored feature template. At the same time, wake up the under-screen fingerprint sensor on the mobile phone for liveness verification. When the matching degree of both biometric features is ≥ 98%, it is determined that the real user is present. Through comprehensive calculation by the dynamic priority decision maker based on the above data, when the behavior credibility of the local approach instruction is ≥ 85 points, the automatic unlocking is preferentially executed, and the remote instruction is changed to the pending review state.

[0058] Finally, through blockchain evidence storage, write the key parameters of the conflict event into the consortium chain node for subsequent audit and traceability. If the arbitration result is to execute the local approach instruction, the system will control the door lock motor to perform the unlocking action and generate a dynamic encryption token to synchronize to the cloud, so that the remote unlocking instruction arriving during this period needs to be verified with the token to take effect.

[0059] If the arbitration result favors the remote instruction, a secondary confirmation process is forcibly started, and a verification request for the area within a radius of 3 meters centered on the door lock and the biometric comparison result is pushed through the APP. The user needs to complete the gesture password or iris recognition confirmation within the specified time.

[0060] The above are the method embodiments proposed in this application. Based on the same inventive concept, the embodiments of this application also provide a doorbell remote sensing device based on a dynamic scenario, and its structure is as Figure 2 shown.

[0061] Figure 2 This is a schematic diagram of the internal structure of a doorbell remote sensing device based on a dynamic scenario provided by the embodiments of this application. As Figure 2 shown, the device includes:

[0062] At least one processor 201;

[0063] And a memory 202 communicatively connected to the at least one processor;

[0064] Wherein, the memory 202 stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor 201 so that the at least one processor 201 can:

[0065] Obtain multi-modal environment perception data, perform multi-modal fusion analysis on the multi-modal environment perception data to obtain abnormal behavior level data; perform abnormal level threshold analysis on the abnormal behavior level data to determine the doorbell status parameter; based on the doorbell status parameter, obtain the first door lock control instruction through trailing status judgment; obtain the user remote control instruction, and perform DES encryption on the user remote control instruction to obtain cloud doorbell service data; according to the cloud doorbell service data, obtain the second door lock control instruction through door lock remote control parsing; perform multi-level arbitration analysis on the first door lock control instruction and the second door lock control instruction to determine the real door lock control instruction.

[0066] Some embodiments of this application provide a non-volatile computer storage medium corresponding to Figure 1 for doorbell remote sensing based on a dynamic scenario, storing computer-executable instructions, and the computer-executable instructions are set to:

[0067] Obtain multi-modal environment perception data, perform multi-modal fusion analysis on the multi-modal environment perception data to obtain abnormal behavior level data; perform abnormal level threshold analysis on the abnormal behavior level data to determine the doorbell status parameter; based on the doorbell status parameter, obtain the first door lock control instruction through trailing status judgment; obtain the user remote control instruction, and perform DES encryption on the user remote control instruction to obtain cloud doorbell service data; according to the cloud doorbell service data, obtain the second door lock control instruction through door lock remote control parsing; perform multi-level arbitration analysis on the first door lock control instruction and the second door lock control instruction to determine the real door lock control instruction.

[0068] Each embodiment in this application is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the embodiments of the Internet of Things devices and media, since they are basically similar to the method embodiments, the description is relatively simple. For the relevant parts, reference can be made to the corresponding descriptions in the method embodiments.

[0069] The systems and media provided by the embodiments of this application correspond one-to-one with the methods. Therefore, the systems and media also have beneficial technical effects similar to those of their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the systems and media will not be elaborated here.

[0070] Those skilled in the art should understand that the embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program code.

[0071] This application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of this application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more flows and / or Figure 1 blocks or multiple blocks.

[0072] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one or more flows and / or Figure 1 blocks or multiple blocks.

[0073] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 steps of the functions specified in one block or multiple blocks.

[0074] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and a memory.

[0075] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of computer-readable media.

[0076] Computer-readable media includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transitory media, such as modulated data signals and carrier waves.

[0077] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, commodity or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising one..." does not exclude the existence of additional identical elements in the process, method, commodity or device comprising the element.

[0078] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A doorbell remote sensing method based on a dynamic scenario, characterized in that, The method includes: Obtaining multi-modal environment perception data, and performing multi-modal fusion analysis on the multi-modal environment perception data to obtain abnormal behavior level data; Performing abnormal level threshold analysis on the abnormal behavior level data to determine the doorbell status parameter; Based on the doorbell status parameter, obtaining the first door lock control instruction through trailing status judgment; Obtaining a user remote control instruction, and performing DES encryption on the user remote control instruction to obtain cloud doorbell service data; According to the cloud doorbell service data, obtaining the second door lock control instruction through door lock remote control parsing; Performing multi-level arbitration analysis on the first door lock control instruction and the second door lock control instruction to determine the real door lock control instruction.

2. The doorbell remote sensing method based on a dynamic scenario according to claim 1, wherein, Performing multi-modal fusion analysis on the multi-modal environment perception data to obtain abnormal behavior level data, specifically including: Performing multi-modal data alignment on the multi-modal environment perception data to obtain spatio-temporal consistent environment data; wherein, the spatio-temporal consistent environment data includes: visible light video stream, three-dimensional depth data, thermal imaging data, voiceprint feature vector; Performing cross-modal anomaly detection on the spatio-temporal consistent environment data to determine environment anomaly detection parameters; wherein, the cross-modal anomaly detection includes: human key point detection, thermal radiation feature detection, three-dimensional movement speed detection, voiceprint cosine similarity analysis; Based on the environmental monitoring, obtaining the abnormal behavior level data through environmental abnormal behavior level recognition.

3. A doorbell remote sensing method based on a dynamic scenario according to claim 1, characterized in that, Performing abnormal level threshold analysis on the abnormal behavior level data to determine the doorbell status parameter, specifically including: Performing abnormal state threshold determination on the abnormal behavior level data to determine the positioning activation instruction; Based on the positioning activation instruction, obtaining user device movement trajectory data through relative position monitoring of the user device; When the distance between the door lock in the user device movement trajectory data is less than the preset radius, determining the verification status parameter through biometric verification; Performing doorbell instruction matching on the verification status parameter to determine the doorbell status parameter.

4. A doorbell remote sensing method based on a dynamic scenario according to claim 1, characterized in that, Based on the doorbell status parameter, obtaining the first door lock control instruction through trailing status judgment, specifically including: Based on the doorbell status parameter, generating a pre-unlock instruction, and according to the pre-unlock instruction, obtaining the user being trailed status through trailing status detection; When the user being trailed status is not trailed, converting the pre-unlock instruction into an unlock instruction; When the user being trailed status is trailed, converting the pre-unlock instruction into a pause unlock instruction, and sending the trailed status to the user device side; According to the unlock instruction or the pause unlock instruction, obtaining the first door lock control instruction.

5. A doorbell remote sensing method based on a dynamic scenario according to claim 1, characterized in that Performing DES encryption on the user remote control instruction to obtain cloud doorbell service data, specifically including: Performing plaintext IP replacement on the user remote control instruction, and performing key control iteration on the replacement result obtained by the plaintext IP replacement to obtain key iteration data; Performing 32-bit swapping on the key iteration data to obtain the data block to be replaced; Based on the data block to be replaced, through IP -1 replacement, the cloud doorbell service data is obtained.

6. A doorbell remote sensing method based on a dynamic scenario according to claim 1, characterized in that Based on the cloud doorbell service data, through remote control parsing of the door lock, a second door lock control instruction is obtained, specifically including: Decrypt the cloud doorbell service data using the SM4 algorithm to obtain the user unique identifier; Based on the user unique identifier, through user instruction analysis, obtain the second door lock control instruction.

7. A doorbell remote sensing method based on a dynamic scenario according to claim 1, characterized in that, Perform multi-level arbitration analysis on the first door lock control instruction and the second door lock control instruction to determine the true door lock control instruction, specifically including: Based on the first door lock control instruction and the second door lock control instruction, through spatio-temporal consistency verification, obtain an instruction conflict signal; According to the instruction conflict signal, through dynamic priority decision analysis, determine the behavior credibility; wherein, the dynamic priority decision analysis includes: biometric cross-verification, behavior pattern analysis, priority decision; Based on the behavior credibility, through an instruction source verification request, determine the true door lock control instruction.

8. A doorbell remote sensing method based on a dynamic scenario according to claim 1, characterized in that, After performing multi-level arbitration analysis on the first door lock control instruction and the second door lock control instruction to determine the true door lock control instruction, the method further includes: Based on the true door lock control instruction, through dynamic weight optimization, obtain a multi-level arbitration optimization weight; According to the multi-level arbitration optimization weight, through arbitration iterative verification, obtain a multi-level arbitration strategy.

9. A doorbell remote sensing device based on a dynamic scenario, characterized in that, The device includes: At least one processor; And a memory communicatively connected to the at least one processor; Wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can: Obtain multi-modal environment perception data, and perform multi-modal fusion analysis on the multi-modal environment perception data to obtain abnormal behavior level data; Perform abnormal level threshold analysis on the abnormal behavior level data to determine the doorbell status parameter; Based on the doorbell status parameter, through trailing state judgment, obtain a first door lock control instruction; Obtain a user remote control instruction, and perform DES encryption on the user remote control instruction to obtain cloud doorbell service data; According to the cloud doorbell service data, through remote control parsing of the door lock, obtain a second door lock control instruction; Perform multi-level arbitration analysis on the first door lock control instruction and the second door lock control instruction to determine the true door lock control instruction.

10. A non-volatile computer storage medium for remote sensing of doorbells based on dynamic scenarios, storing computer-executable instructions, characterized in that, The computer-executable instructions are set to: Obtain multi-modal environment perception data, and perform multi-modal fusion analysis on the multi-modal environment perception data to obtain abnormal behavior level data; Perform abnormal level threshold analysis on the abnormal behavior level data to determine the doorbell status parameter; Based on the doorbell status parameter, through trailing state judgment, obtain a first door lock control instruction; Obtain a user remote control instruction, and perform DES encryption on the user remote control instruction to obtain cloud doorbell service data; According to the cloud doorbell service data, through remote control parsing of the door lock, obtain a second door lock control instruction; Perform multi-level arbitration analysis on the first door lock control instruction and the second door lock control instruction to determine the true door lock control instruction.

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