Intelligent lock theft prevention identification method, intelligent lock, and readable medium

Abstract

The present application relates to the field of intelligent lock control, especially to an intelligent lock anti-theft identification method, an intelligent lock and a readable medium.A kind of intelligent lock anti-theft identification method, comprising: obtaining a plurality of first image data arranged in time sequence;Obtain the first coordinate position of the first mark in a plurality of the first image data by first identification model;The first mark position is marked on the first image data in the first image data, and then the moving track of the first mark is obtained;Determine whether there is abnormal behavior based on the moving track.The intelligent lock abnormal behavior identification method provided by the present application can identify the first mark, determine the first coordinate position of the first mark, generate the moving track of the first mark, and quickly determine whether there is abnormal behavior according to the moving track, which is convenient and fast.

Description

Technical Field

[0001] This invention relates to the field of smart lock control, and more particularly to a smart lock anti-theft identification method, a smart lock, and a readable medium. Background Technology

[0002] With social development and technological advancements, smart locks have become commonplace in households. However, currently, smart locks can only perform simple actions such as facial recognition to determine if the user's face data has been registered, and then execute the door unlocking operation. When someone attempts to pick the lock or engages in other unusual behavior, the detection of such behavior may be delayed, leading to property loss. Therefore, detecting unusual behavior before a theft occurs is particularly important. Summary of the Invention

[0003] In view of the shortcomings of the prior art, the purpose of this invention is to provide a smart lock anti-theft identification method, a smart lock, and a readable medium, which can quickly detect abnormal behavior before a theft.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] On one hand, the present invention provides a smart lock anti-theft identification method, comprising:

[0006] Acquire multiple first image data arranged in chronological order;

[0007] The first coordinate position of the first identifier in multiple first image data is obtained through the first recognition model;

[0008] Multiple first marker locations are marked on the first first image data to obtain the movement trajectory of the first marker;

[0009] The presence of abnormal behavior is determined based on the movement trajectory.

[0010] Furthermore, the first image data acquisition process includes:

[0011] Obtain the first video data;

[0012] Based on the first video data, a video image is acquired at predetermined time intervals as the first image data.

[0013] Furthermore, before acquiring the first image data, the process also includes:

[0014] Acquire the second image data;

[0015] The second recognition model is used to perform face recognition on the second image data to obtain face feature data;

[0016] The system uses a family facial database to determine if the person is a family member. If so, the door is unlocked; otherwise, the second image data is transmitted to the user terminal.

[0017] Furthermore, the generation steps of the first recognition model are as follows:

[0018] Obtain a first training set; the first training set includes multiple first images labeled with first identifiers;

[0019] The first recognition model is obtained by training the initialized neural network model using the first training set;

[0020] The steps for generating the second recognition model are as follows:

[0021] Obtain a second training set; the second training set includes multiple second images labeled with facial feature data.

[0022] The second recognition model is obtained by training the initialized neural network model using the second training set.

[0023] Furthermore, the first identifier includes the iris;

[0024] The abnormal behavior determination process includes:

[0025] Obtain the number of zigzags in the movement trajectory per unit time;

[0026] If the number of bends exceeds the threshold, then abnormal behavior is determined to exist.

[0027] Furthermore, the aforementioned smart lock anti-theft identification method is characterized in that, upon determining the existence of the abnormal behavior, alarm information is simultaneously sent to both the user terminal and the property management terminal.

[0028] Furthermore, the aforementioned smart lock anti-theft identification method is characterized by further comprising:

[0029] Receive a stop alarm command from the user terminal and stop sending alarm information to the outside world.

[0030] On the other hand, the present invention provides a smart lock, characterized in that it includes:

[0031] The acquisition module is used to acquire multiple first image data arranged in chronological order;

[0032] The processing module is used to obtain the first coordinate position of the first marker in multiple first image data through a first recognition model; mark the multiple first marker positions on the first first image data to obtain the movement trajectory of the first marker; and determine whether there is abnormal behavior based on the movement trajectory.

[0033] On the other hand, the present invention provides a smart lock, comprising:

[0034] Memory, which stores computer programs;

[0035] When the processor executes the computer program, it implements any of the smart lock anti-theft identification methods described above.

[0036] On the other hand, the present invention provides a computer-readable medium storing a computer program that, when executed by a processor, implements any of the smart lock anti-theft identification methods described above.

[0037] Compared with existing technologies, the smart lock anti-theft identification method, smart lock, and readable medium provided by this invention have the following beneficial effects:

[0038] The intelligent lock abnormal behavior recognition method provided by the present invention can identify a first marker, obtain and determine the first coordinate position of the first marker, and then generate the movement trajectory of the first marker. Based on the movement trajectory, it can quickly determine whether there is abnormal behavior, which is convenient and fast. Attached Figure Description

[0039] Figure 1 This is a flowchart of the smart lock anti-theft identification method provided by the present invention.

[0040] Figure 2 This is a structural block diagram of the smart lock provided by the present invention. Detailed Implementation

[0041] To make the objectives, technical solutions, and effects of this invention clearer and more explicit, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0042] Those skilled in the art will understand that the foregoing general description and the following detailed description are exemplary and illustrative embodiments of the present invention and are not intended to limit the invention.

[0043] The terms “comprising,” “including,” or any other variations thereof throughout this document are intended to cover non-exclusive inclusion, such that a process or method that includes a list of steps includes not only those steps but may also include other steps not expressly listed or inherent to such a process or method. Similarly, without further limitation, one or more devices or subsystems, elements, structures, or components beginning with “comprising…a” will not exclude the presence of other devices or other subsystems or other elements or other structures or components. Throughout the specification, the phrases “in one embodiment,” “in another embodiment,” and similar language may, but not necessarily, refer to the same embodiment.

[0044] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0045] Please see Figure 1 This invention provides a smart lock anti-theft identification method, which is applied to smart locks. When a user operates the smart lock, the method will determine whether there is any abnormal behavior based on the user's characteristic location. In particular, it can quickly detect certain lock-picking behaviors.

[0046] The smart lock anti-theft identification method includes:

[0047] Acquire multiple first image data arranged in chronological order;

[0048] The first coordinate position of the first identifier in the first image data is obtained by the first recognition model; specifically, the first identifier is preferably the iris image in the eye image, and the first coordinate position is the center position of the iris image.

[0049] Furthermore, as a preferred embodiment, the generation step of the first recognition model is as follows:

[0050] Obtain a first training set; the first training set includes multiple first images labeled with first identifiers; preferably, the first identifiers are facial organs such as the iris and the tip of the nose.

[0051] The first recognition model is obtained by training the initialized neural network model using the first training set.

[0052] Multiple first marker positions are marked on the first first image data to obtain the movement trajectory of the first marker; specifically, the movement trajectory formed by connecting multiple first coordinate positions of the first marker reflects data such as the movement frequency of the first marker, which can quickly determine whether the first marker is in a state of rapid vibration, and thus determine whether there is an anomaly.

[0053] The movement trajectory is used to determine whether any abnormal behavior exists. Specifically, the abnormal behavior includes acts such as peeping and lock picking.

[0054] The intelligent lock abnormal behavior recognition method provided by the present invention can identify a first marker, obtain and determine the first coordinate position of the first marker, and then generate the movement trajectory of the first marker. Based on the movement trajectory, it can quickly determine whether there is abnormal behavior, which is convenient and fast.

[0055] Furthermore, as a preferred embodiment, in this example, the first image data acquisition process includes:

[0056] Obtain the first video data;

[0057] Based on the first video data, a video frame is acquired at predetermined time intervals as the first image data. In this embodiment, continuous video content is used as the data source for the first image data, ensuring that the acquired data is continuous and not discontinuous. The camera used to acquire the first video data is preferably a high-definition camera that supports acquiring high-definition video data at 120 frames per second. The predetermined time interval is preferably 10-100 milliseconds, and more preferably 50 milliseconds. Selecting a suitable first image from the images acquired by the high-speed camera makes the subsequent determination of the movement trajectory more reliable.

[0058] Furthermore, as a preferred embodiment, before acquiring the first image data, the following steps are also included:

[0059] Acquire the second image data;

[0060] The second recognition model is used to perform face recognition on the second image data to obtain face feature data;

[0061] Furthermore, the generation steps of the second recognition model are as follows:

[0062] Obtain a second training set; the second training set includes multiple second images labeled with facial feature data.

[0063] The second recognition model is obtained by training the initialized neural network model using the second training set.

[0064] Based on the family's facial database, the system determines whether the person is a family member. If so, the door lock is opened; otherwise, the second image data is transmitted to the user terminal. Specifically, before recognizing the first identifier, facial recognition is performed. If the person is not a family member, the second image is immediately sent to the user terminal, informing the user of the potential risks in advance. This allows the system to anticipate any abnormal behavior that might occur in front of the smart lock before any further abnormal behavior is detected.

[0065] Furthermore, as a preferred embodiment, the first marker includes the iris; preferably, choosing the iris as the marker can quickly determine whether the current person's eyeballs are moving rapidly. Once rapid movement occurs, it indicates that the person is quite nervous.

[0066] The abnormal behavior determination process includes:

[0067] The number of zigzags in the movement trajectory per unit time is obtained; that is, the fluctuation frequency of the movement trajectory is determined. The fluctuation frequency of the movement trajectory will reflect whether the current actor is in a state of tension.

[0068] If the number of bends exceeds a threshold, abnormal behavior is determined. Specifically, the threshold is set based on the length of a unit of time. Preferably, the threshold is set to 1.5-2 times per second, which determines whether the person is panicking and thus whether abnormal behavior exists.

[0069] Furthermore, as a preferred embodiment, upon determining the existence of the abnormal behavior, alarm information is simultaneously sent to both the user terminal and the property management terminal. This ensures that the consequences of the abnormal behavior are not allowed to escalate further in the event of an abnormal risk, effectively improving the security of the community or home. Additionally, the smart lock also emits alarm sounds to deter the intruder.

[0070] Furthermore, as a preferred embodiment, this embodiment also includes:

[0071] The system receives a stop alarm command from the user terminal and ceases sending alarm messages to external systems. If the user believes there is no risk or the risk caused by abnormal behavior has been eliminated, they can send a stop alarm command to the smart lock through their user terminal to stop sending alarm messages to external systems. In this way, the property management can quickly receive a notification that the risk has been eliminated, or the smart lock's external alarm behavior will also be deactivated.

[0072] Accordingly, please refer to Figure 2 This invention provides a smart lock, comprising:

[0073] The acquisition module is used to acquire multiple first image data arranged in chronological order;

[0074] The processing module is used to obtain the first coordinate position of the first marker in multiple first image data through a first recognition model; mark the multiple first marker positions on the first first image data to obtain the movement trajectory of the first marker; and determine whether there is abnormal behavior based on the movement trajectory.

[0075] Accordingly, the present invention provides a smart lock, comprising:

[0076] Memory, which stores computer programs;

[0077] When the processor executes the computer program, it implements the smart lock anti-theft identification method described in any of the foregoing embodiments.

[0078] Accordingly, the present invention provides a computer-readable medium, characterized in that it stores a computer program, which, when executed by a processor, implements the smart lock anti-theft identification method described in any of the foregoing embodiments.

[0079] More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0080] In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof.

[0081] It is understood that those skilled in the art can make equivalent substitutions or modifications to the technical solution and inventive concept of the present invention, and all such substitutions or modifications should fall within the protection scope of the appended claims.

Claims

1. A smart lock anti-theft identification method, characterized in that, include: Acquire multiple first image data arranged in chronological order; The first coordinate position of a first identifier in multiple first image data is obtained through a first recognition model, wherein the first identifier includes the iris; Multiple first coordinate positions are marked on the first first image data to obtain the movement trajectory of the first marker; Based on the movement trajectory, it is determined whether there is abnormal behavior. The abnormal behavior determination process includes: obtaining the number of twists and turns of the movement trajectory per unit time. If the number of bends exceeds the threshold, then abnormal behavior is determined to exist.

2. The smart lock anti-theft identification method according to claim 1, characterized in that, The first image data acquisition process includes: Obtain the first video data; Based on the first video data, a video image is acquired at predetermined time intervals as the first image data.

3. The smart lock anti-theft identification method according to claim 1, characterized in that, Before acquiring the first image data, the method further includes: Acquire the second image data; The second recognition model is used to perform face recognition on the second image data to obtain face feature data; The system uses a family facial database to determine if the person is a family member. If so, the door is unlocked; otherwise, the second image data is transmitted to the user terminal.

4. The smart lock anti-theft identification method according to claim 3, characterized in that, The steps for generating the first recognition model are as follows: Obtain a first training set; the first training set includes multiple first images labeled with first identifiers; The first recognition model is obtained by training the initialized neural network model using the first training set; The steps for generating the second recognition model are as follows: Obtain a second training set; the second training set includes multiple second images labeled with facial feature data. The second recognition model is obtained by training the initialized neural network model using the second training set.

5. The smart lock anti-theft identification method according to claim 1, characterized in that, Once the abnormal behavior is detected, an alarm message is sent to both the user terminal and the property management terminal.

6. The smart lock anti-theft identification method according to claim 5, characterized in that, Also includes: Receive a stop alarm command from the user terminal and stop sending alarm information to the outside world.

7. A smart lock, characterized in that, include: The acquisition module is used to acquire multiple first image data arranged in chronological order; The processing module is configured to obtain the first coordinate position of a first identifier in multiple first image data through a first recognition model, wherein the first identifier includes the iris; and to mark the multiple first coordinate positions on the first first image data to obtain the movement trajectory of the first identifier. Based on the movement trajectory, it is determined whether there is abnormal behavior. The abnormal behavior determination process includes: obtaining the number of twists and turns of the movement trajectory per unit time. If the number of bends exceeds the threshold, then abnormal behavior is determined to exist.

8. A smart lock, characterized in that, include: Memory, which stores computer programs; When the processor executes the computer program, it implements the smart lock anti-theft identification method according to any one of claims 1-6.

9. A computer-readable medium, characterized in that, The device contains a computer program that, when executed by a processor, implements the smart lock anti-theft identification method according to any one of claims 1-6.

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