Automatic counter locking method and system based on abnormal unlocking behavior and intelligent door lock

Abstract

The invention discloses an automatic counter locking method and system based on an abnormal unlocking behavior and an intelligent door lock, and the method comprises the steps: obtaining sensor data which is obtained through real-time monitoring of a plurality of sensors installed on the intelligent door lock; analyzing the sensor data based on a preset recognition algorithm, and judging whether an abnormal unlocking behavior exists or not; and when it is confirmed that the abnormal unlocking behavior exists, an automatic counter locking mechanism is started for counter locking, and a preset alarm behavior is triggered. According to the intelligent door lock, various sensor data are monitored, and whether the abnormal unlocking behavior is generated or not is analyzed according to the various sensor data, so that the counter locking operation is executed and the alarm information is sent in time after the abnormal unlocking behavior is confirmed, the safety performance of the intelligent door lock is improved, and illegal invasion is effectively prevented.

Description

Technical Field

[0001] The present invention relates to the technical field of smart door locks, and in particular to an automatic anti-locking method and system based on abnormal unlocking behavior, a smart door lock and a computer-readable storage medium. Background Art

[0002] Existing smart door lock technologies usually include electronic passwords, biometrics, remote unlocking and other functions to improve the security and convenience of door locks. These smart door locks usually sound an alarm or notify users through mobile applications when they detect prying or illegal unlocking attempts. However, these measures cannot prevent illegal intruders from continuing to try to unlock the door, posing a great security risk.

[0003] That is to say, existing smart door locks cannot immediately prevent intrusion when illegal unlocking is detected, the alarm system may be ignored due to environmental noise or other reasons, and in an emergency, the user may not be able to respond to the alarm in time.

[0004] Therefore, the prior art still needs to be improved and developed. Summary of the invention

[0005] The main purpose of the present invention is to provide an automatic anti-locking method, system, smart door lock and computer-readable storage medium based on abnormal unlocking behavior, aiming to solve the problem in the prior art that the smart door lock cannot take effective countermeasures in time when abnormal unlocking behavior is detected, thereby failing to prevent illegal intruders from continuing to try to unlock the door.

[0006] To achieve the above object, the present invention provides an automatic anti-locking method based on abnormal unlocking behavior, and the automatic anti-locking method based on abnormal unlocking behavior comprises the following steps:

[0007] Acquire sensor data, where the sensor data is obtained by real-time monitoring of multiple sensors installed on the smart door lock;

[0008] Analyze the sensor data based on a preset recognition algorithm to determine whether there is abnormal unlocking behavior;

[0009] When abnormal unlocking behavior is confirmed, the automatic anti-locking mechanism is activated to anti-lock and trigger the preset alarm behavior.

[0010] Optionally, in the automatic anti-locking method based on abnormal unlocking behavior, the sensor includes a vibration sensor, a pressure sensor and a sound sensor;

[0011] The vibration sensor is used to detect abnormal vibrations to which the smart door lock is subjected;

[0012] The pressure sensor is used to detect abnormal pressure changes on the smart door lock panel;

[0013] The sound sensor is used to detect abnormal sounds in the smart door lock area.

[0014] Optionally, in the automatic anti-locking method based on abnormal unlocking behavior, the preset recognition algorithm includes a recognition algorithm based on vibration patterns, a recognition algorithm based on pressure changes, a recognition algorithm based on sound features, and a recognition algorithm based on behavior sequences.

[0015] Optionally, the automatic anti-locking method based on abnormal unlocking behavior, wherein the abnormal unlocking behavior includes prying behavior, hammering behavior, master key unlocking behavior, password or fingerprint brute force cracking behavior, electronic interference behavior and lock core injection behavior.

[0016] Optionally, the automatic anti-locking method based on abnormal unlocking behavior, wherein the analyzing the sensor data based on a preset recognition algorithm to determine whether there is abnormal unlocking behavior specifically includes:

[0017] When the preset recognition algorithm is a recognition algorithm based on vibration patterns, the vibration data of the smart door lock is collected through a vibration sensor, and vibration features in the vibration data are extracted, wherein the vibration features include frequency, amplitude and duration, and the vibration features extracted in real time are matched with the pre-stored normal unlocking vibration patterns. If the difference exceeds a preset threshold, it is determined that there is abnormal unlocking behavior;

[0018] When the preset recognition algorithm is a recognition algorithm based on pressure changes, the pressure changes of the smart door lock panel are monitored in real time through the pressure sensor, and the pressure range for normal unlocking is set. When the monitored pressure exceeds the pressure range, the dynamic pattern of the pressure change is analyzed and compared with the pressure change pattern of normal unlocking. If there is an abnormality in the pressure change, it is determined that there is an abnormal unlocking behavior;

[0019] When the preset recognition algorithm is a recognition algorithm based on sound features, the sound signal in the smart door lock area is detected by a sound sensor, the sound signal is subjected to spectrum analysis, the frequency domain features of the sound are extracted, and the frequency domain features are analyzed using sound recognition technology. If the sound is abnormal, it is determined that there is abnormal unlocking behavior.

[0020] When the preset recognition algorithm is a recognition algorithm based on behavior sequence, the behavior sequence of the user performing the unlocking operation under normal circumstances is recorded in advance, and a standard behavior sequence model is constructed. The user's unlocking behavior is tracked and recorded in real time, and the real-time behavior sequence collected in real time is compared with the pre-constructed standard behavior sequence. It is analyzed whether the duration of each behavior in the real-time behavior sequence falls within the normal range defined by the standard sequence. If the duration of a behavior exceeds the expected normal range, it is marked as a duration abnormality. It is verified whether the order of the real-time behavior sequence is consistent with the standard sequence. If the execution order of the behavior does not match the expectation, it is marked as a sequence abnormality. Based on the results of the duration analysis and sequence verification, if there is any duration abnormality or sequence abnormality, it means that the real-time behavior sequence is abnormal, and it is determined that there is abnormal unlocking behavior.

[0021] Optionally, the automatic anti-locking method based on abnormal unlocking behavior, wherein when the abnormal unlocking behavior is confirmed, the automatic anti-locking mechanism is started to perform anti-locking and a preset alarm behavior is triggered, specifically including:

[0022] When it is confirmed that there is any one or more of the following behaviors: lock picking, hammering, master key unlocking, password or fingerprint brute force cracking, electronic interference and lock core injection, the automatic anti-locking mechanism is activated, and an anti-locking instruction is sent to the electromagnetic lock, and the electromagnetic lock is controlled to be activated to achieve anti-locking. When the electromagnetic lock fails, the backup mechanical locking mechanism is controlled to start and achieve anti-locking;

[0023] At the same time as the door is automatically locked, the alarm information is sent to the bound user's mobile phone or other designated devices via the wireless network, and an audible and visual alarm is issued.

[0024] Optionally, the automatic anti-locking method based on abnormal unlocking behavior, wherein the alarm information is sent to a bound user's mobile phone or other designated device via a wireless network, and then further includes:

[0025] If the user receives an alarm notification via mobile phone, the user is granted the authority to remotely control the door lock status.

[0026] In addition, to achieve the above-mentioned purpose, the present invention further provides an automatic anti-locking system based on abnormal unlocking behavior, wherein the automatic anti-locking system based on abnormal unlocking behavior comprises:

[0027] A data acquisition module is used to acquire sensor data, wherein the sensor data is obtained by real-time monitoring of multiple sensors installed on the smart door lock;

[0028] A data analysis module, used to analyze the sensor data based on a preset recognition algorithm to determine whether there is abnormal unlocking behavior;

[0029] The exception handling module is used to start the automatic anti-locking mechanism to perform anti-locking and trigger the preset alarm behavior when abnormal unlocking behavior is confirmed.

[0030] In addition, to achieve the above-mentioned purpose, the present invention also provides a smart door lock, wherein the smart door lock includes: a memory, a processor, and an automatic anti-locking program based on abnormal unlocking behavior stored in the memory and runnable on the processor, and when the automatic anti-locking program based on abnormal unlocking behavior is executed by the processor, the steps of the automatic anti-locking method based on abnormal unlocking behavior as described above are implemented.

[0031] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores an automatic anti-locking program based on abnormal unlocking behavior, and when the automatic anti-locking program based on abnormal unlocking behavior is executed by the processor, the steps of the automatic anti-locking method based on abnormal unlocking behavior as described above are implemented.

[0032] In the present invention, sensor data is obtained, and the sensor data is obtained by real-time monitoring of multiple sensors installed on the smart door lock; the sensor data is analyzed based on a preset recognition algorithm to determine whether there is abnormal unlocking behavior; when it is confirmed that there is abnormal unlocking behavior, the automatic anti-locking mechanism is started to reverse the lock and trigger the preset alarm behavior. The present invention monitors multiple sensor data, analyzes whether abnormal unlocking behavior occurs based on multiple sensor data, and thus promptly performs anti-locking operations and sends alarm information after confirming that abnormal unlocking behavior occurs, thereby improving the safety performance of the smart door lock and effectively preventing illegal intrusion. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a flow chart of a preferred embodiment of the automatic anti-locking method based on abnormal unlocking behavior of the present invention;

[0034] Figure 2 It is a structural diagram of a preferred embodiment of the automatic anti-locking system based on abnormal unlocking behavior of the present invention;

[0035] Figure 3 This is a structural diagram of a preferred embodiment of the smart door lock of the present invention. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0037] The automatic anti-locking method based on abnormal unlocking behavior described in the preferred embodiment of the present invention is as follows: Figure 1As shown, the automatic anti-locking method based on abnormal unlocking behavior includes the following steps:

[0038] Step S10: Acquire sensor data, where the sensor data is obtained by real-time monitoring of multiple sensors installed on the smart door lock.

[0039] Specifically, the sensors include vibration sensors, pressure sensors and sound sensors, which are built-in or externally connected to the smart door lock and are used to monitor the status of the door lock in real time; the vibration sensor is used to detect abnormal vibrations to the smart door lock, such as knocking, prying, etc.; the pressure sensor is used to detect abnormal pressure changes on the smart door lock panel to determine whether someone is trying to pry the lock; the sound sensor is used to detect abnormal sounds in the smart door lock area, such as the sound of prying tools.

[0040] The smart door lock obtains sensor data collected by sensors such as vibration sensors, pressure sensors and sound sensors, preliminarily processes the sensor data, and makes preliminary abnormality judgments.

[0041] Step S20: Analyze the sensor data based on a preset recognition algorithm to determine whether there is any abnormal unlocking behavior.

[0042] Specifically, the preset recognition algorithm (intelligent algorithm: a calculation method for analyzing sensor data and determining whether there is abnormal behavior) includes a recognition algorithm based on vibration patterns, a recognition algorithm based on pressure changes, a recognition algorithm based on sound features, and a recognition algorithm based on behavior sequences. The abnormal unlocking behavior (referring to the behavior of trying to open the smart door lock by using keys, passwords or other authorized methods abnormally) includes lock picking behavior (using tools such as crowbars and screwdrivers to try to pry open the smart door lock, including lock body destruction: using tools such as electric drills to try to destroy the lock body structure), hammering behavior (using hard objects such as hammers to hit the door lock in an attempt to destroy the lock body), master key unlocking behavior (using master keys or other unauthorized keys to try to open the lock), password or fingerprint brute force cracking behavior (consecutively and quickly entering different passwords or fingerprints in an attempt to crack the smart door lock), electronic interference behavior (using electronic jammers to interfere with the electronic signals of smart door locks in an attempt to make them ineffective) and lock core injection behavior (injecting sticky substances or ice cubes into the lock core of the smart door lock in an attempt to freeze or block the lock core).

[0043] (1) Recognition algorithm based on vibration pattern:

[0044] When the preset recognition algorithm is a recognition algorithm based on vibration patterns, the vibration data of the smart door lock is collected through a vibration sensor, and vibration features in the vibration data are extracted, wherein the vibration features include frequency, amplitude and duration (feature extraction). The vibration features extracted in real time are matched with the pre-stored normal unlocking vibration patterns. If the difference exceeds a preset threshold, it is determined that abnormal unlocking behavior exists (pattern matching). In addition, machine learning algorithms (such as SVM, random forest, neural network, etc.) can be used to train normal and abnormal vibration data to establish a classification model.

[0045] (2) Recognition algorithm based on pressure change:

[0046] When the preset recognition algorithm is a recognition algorithm based on pressure changes, the pressure changes of the smart door lock panel are monitored in real time through the pressure sensor (real-time monitoring), and the pressure range for normal unlocking is set. When the monitored pressure exceeds the pressure range, an abnormal judgment (threshold judgment) is triggered, and the dynamic pattern of pressure changes, such as rapid rise or fall, is analyzed and compared with the pressure change pattern of normal unlocking (dynamic analysis). If there is an abnormality in the pressure change, it is determined that abnormal unlocking behavior exists.

[0047] (3) Recognition algorithm based on sound features:

[0048] When the preset recognition algorithm is a recognition algorithm based on sound features, the sound signal in the smart door lock area is detected by a sound sensor (sound collection), the sound signal is spectrally analyzed, the frequency domain features of the sound are extracted (spectral analysis), and the frequency domain features are analyzed using sound recognition technology, such as MFCC (Mel Frequency Cepstral Coefficient) and sound classification algorithm. If the sound is abnormal, it is determined that there is abnormal unlocking behavior (sound recognition), and the normal unlocking sound is distinguished from the sound of the lock picking tool.

[0049] (4) Recognition algorithm based on behavior sequence:

[0050] When the preset recognition algorithm is a recognition algorithm based on a behavior sequence, the behavior sequence of the user performing the unlocking operation under normal circumstances is recorded in advance, including the execution order of each behavior and its duration (sequence construction), and a standard behavior sequence model (sequence definition) is constructed. The model not only includes the order of the behavior, but also the expected duration of each behavior. For example, a standard behavior sequence may be described as: "User approaches the door lock (3-5 seconds) → enters the password (1-3 seconds) → waits (0.5-1 seconds) → presses the door handle (0.5-2 seconds) → unlocks successfully", and the user's unlocking behavior is tracked and recorded in real time to ensure that each behavior and its corresponding duration are accurately recorded (real-time monitoring). The real-time behavior sequence collected in real time is compared with the pre-built standard behavior sequence. The comparison content includes the order of behaviors and the duration of each behavior (sequence comparison). It is analyzed whether the duration of each behavior in the real-time behavior sequence falls within the normal range defined by the standard sequence. If the duration of a behavior exceeds the expected normal range, it is marked as a duration abnormality (timing analysis). It is verified whether the order of the real-time behavior sequence is consistent with the standard sequence. If the execution order of the behavior does not match the expectation, it is marked as a sequence abnormality (sequence verification). Based on the results of duration analysis and sequence verification, if there is any duration abnormality or sequence abnormality, it means that the real-time behavior sequence is abnormal, and it is determined that there is abnormal unlocking behavior (abnormal determination).

[0051] By integrating the order of the behavior sequence and the duration of each behavior, it is possible to more accurately identify the user's behavior patterns and effectively distinguish between normal and abnormal unlocking behaviors, thereby significantly improving the security protection capabilities of the smart door lock system.

[0052] Step S30: When it is confirmed that there is abnormal unlocking behavior, the automatic anti-locking mechanism is activated to perform anti-locking and trigger a preset alarm behavior.

[0053] Specifically, when it is confirmed that there is any one or more of the following behaviors: prying, hammering, master key unlocking, password or fingerprint brute force cracking, electronic interference and lock core injection, the automatic anti-locking mechanism is started, and an anti-locking instruction is sent to the electromagnetic lock. The electromagnetic lock is controlled to achieve anti-locking after activation (physical locking, a mechanical structure that automatically performs anti-locking operations). When the electromagnetic lock fails, the backup mechanical locking mechanism is controlled to start and achieve anti-locking to ensure that the door lock is in a locked state to prevent illegal opening. If the door lock is automatically anti-locked, assuming that the abnormal unlocking fails, the user can open the door lock with an APP or use a password with management authority, fingerprint or face to unlock the door after returning home. At the same time of automatic anti-locking, an alarm message is sent to the bound user's mobile phone or other designated device via the wireless network, an audible and visual alarm is issued, and an alarm message is sent via the wireless communication unit (the smart door lock communicates with the user's device or monitoring center via Wi-Fi, Bluetooth or other wireless communication technologies).

[0054] Furthermore, if the user receives an alarm notification via a mobile phone, the user is granted permission to remotely control the door lock status, and the user interface allows the user to configure door lock parameters, receive alarm notifications, and remotely control the door lock status.

[0055] Beneficial effects of the present invention:

[0056] (1) Improve the security performance of smart door locks and effectively prevent illegal intrusion.

[0057] (2) Enhanced users’ trust in the security of smart door locks.

[0058] (3) The automatic anti-lock mechanism buys users valuable time to respond to illegal intrusions.

[0059] Furthermore, the present invention can also be combined with a video surveillance system to record the image of the intruder while automatically locking the door, so as to facilitate subsequent investigations; the door lock status can be synchronized through a cloud service to achieve remote monitoring and control.

[0060] Furthermore, if Figure 2 As shown, based on the above-mentioned automatic anti-locking method based on abnormal unlocking behavior, the present invention also provides an automatic anti-locking system based on abnormal unlocking behavior, wherein the automatic anti-locking system based on abnormal unlocking behavior includes:

[0061] A data acquisition module 51 is used to acquire sensor data, wherein the sensor data is obtained by real-time monitoring of multiple sensors installed on the smart door lock;

[0062] A data analysis module 52, used to analyze the sensor data based on a preset recognition algorithm to determine whether there is abnormal unlocking behavior;

[0063] The exception handling module 53 is used to start the automatic anti-locking mechanism to perform anti-locking and trigger a preset alarm behavior when it is confirmed that there is an abnormal unlocking behavior.

[0064] Furthermore, if Figure 3 As shown, based on the above-mentioned automatic anti-locking method and system based on abnormal unlocking behavior, the present invention also provides a smart door lock accordingly, and the smart door lock includes a processor 10, a memory 20 and a display 30. Figure 3 Only some components of the smart door lock are shown, but it should be understood that it is not required to implement all the components shown, and more or fewer components may be implemented instead.

[0065] In some embodiments, the memory 20 may be an internal storage unit of the smart door lock, such as a hard disk or memory of the smart door lock. In other embodiments, the memory 20 may also be an external storage device of the smart door lock, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the smart door lock. Further, the memory 20 may also include both an internal storage unit of the smart door lock and an external storage device. The memory 20 is used to store application software and various types of data installed in the smart door lock, such as the program code of the smart door lock installed. The memory 20 may also be used to temporarily store data that has been output or is to be output. In one embodiment, an automatic anti-locking program 40 based on abnormal unlocking behavior is stored on the memory 20, and the automatic anti-locking program 40 based on abnormal unlocking behavior can be executed by the processor 10, thereby realizing the automatic anti-locking method based on abnormal unlocking behavior in the present application.

[0066] In some embodiments, the processor 10 may be a central processing unit (CPU), a microprocessor or other data processing chip, used to run the program code or process data stored in the memory 20, such as executing the automatic anti-locking method based on abnormal unlocking behavior.

[0067] In some embodiments, the display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 30 is used to display information on the smart door lock and to display a visual user interface. The components 10-30 of the smart door lock communicate with each other via a system bus.

[0068] In one embodiment, when the processor 10 executes the automatic anti-locking program 40 based on abnormal unlocking behavior in the memory 20, the following steps are implemented:

[0069] Acquire sensor data, where the sensor data is obtained by real-time monitoring of multiple sensors installed on the smart door lock;

[0070] Analyze the sensor data based on a preset recognition algorithm to determine whether there is abnormal unlocking behavior;

[0071] When abnormal unlocking behavior is confirmed, the automatic anti-locking mechanism is activated to anti-lock and trigger the preset alarm behavior.

[0072] Wherein, the sensors include vibration sensors, pressure sensors and sound sensors;

[0073] The vibration sensor is used to detect abnormal vibrations to which the smart door lock is subjected;

[0074] The pressure sensor is used to detect abnormal pressure changes on the smart door lock panel;

[0075] The sound sensor is used to detect abnormal sounds in the smart door lock area.

[0076] Among them, the preset recognition algorithms include a recognition algorithm based on vibration patterns, a recognition algorithm based on pressure changes, a recognition algorithm based on sound features, and a recognition algorithm based on behavior sequences.

[0077] Among them, the abnormal unlocking behavior includes prying, hammering, master key unlocking, password or fingerprint brute force cracking, electronic interference and lock core injection.

[0078] The analyzing the sensor data based on a preset recognition algorithm to determine whether there is abnormal unlocking behavior specifically includes:

[0079] When the preset recognition algorithm is a recognition algorithm based on vibration patterns, the vibration data of the smart door lock is collected through a vibration sensor, and vibration features in the vibration data are extracted, wherein the vibration features include frequency, amplitude and duration, and the vibration features extracted in real time are matched with the pre-stored normal unlocking vibration patterns. If the difference exceeds a preset threshold, it is determined that there is abnormal unlocking behavior;

[0080] When the preset recognition algorithm is a recognition algorithm based on pressure changes, the pressure changes of the smart door lock panel are monitored in real time through the pressure sensor, and the pressure range for normal unlocking is set. When the monitored pressure exceeds the pressure range, the dynamic pattern of the pressure change is analyzed and compared with the pressure change pattern of normal unlocking. If there is an abnormality in the pressure change, it is determined that there is an abnormal unlocking behavior;

[0081] When the preset recognition algorithm is a recognition algorithm based on sound features, the sound signal in the smart door lock area is detected by a sound sensor, the sound signal is subjected to spectrum analysis, the frequency domain features of the sound are extracted, and the frequency domain features are analyzed using sound recognition technology. If the sound is abnormal, it is determined that there is abnormal unlocking behavior.

[0082] When the preset recognition algorithm is a recognition algorithm based on behavior sequence, the behavior sequence of the user performing the unlocking operation under normal circumstances is recorded in advance, and a standard behavior sequence model is constructed. The user's unlocking behavior is tracked and recorded in real time, and the real-time behavior sequence collected in real time is compared with the pre-constructed standard behavior sequence. It is analyzed whether the duration of each behavior in the real-time behavior sequence falls within the normal range defined by the standard sequence. If the duration of a behavior exceeds the expected normal range, it is marked as a duration abnormality. It is verified whether the order of the real-time behavior sequence is consistent with the standard sequence. If the execution order of the behavior does not match the expectation, it is marked as a sequence abnormality. Based on the results of the duration analysis and sequence verification, if there is any duration abnormality or sequence abnormality, it means that the real-time behavior sequence is abnormal, and it is determined that there is abnormal unlocking behavior.

[0083] When it is confirmed that there is abnormal unlocking behavior, the automatic anti-locking mechanism is activated to perform anti-locking and trigger the preset alarm behavior, which specifically includes:

[0084] When it is confirmed that there is any one or more of the following behaviors: lock picking, hammering, master key unlocking, password or fingerprint brute force cracking, electronic interference and lock core injection, the automatic anti-locking mechanism is activated, and an anti-locking instruction is sent to the electromagnetic lock, and the electromagnetic lock is controlled to be activated to achieve anti-locking. When the electromagnetic lock fails, the backup mechanical locking mechanism is controlled to start and achieve anti-locking;

[0085] At the same time as the door is automatically locked, the alarm information is sent to the bound user's mobile phone or other designated devices via the wireless network, and an audible and visual alarm is issued.

[0086] The method further includes sending the alarm information to the bound user's mobile phone or other designated device via the wireless network, and then:

[0087] If the user receives an alarm notification via mobile phone, the user is granted the authority to remotely control the door lock status.

[0088] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores an automatic anti-locking program based on abnormal unlocking behavior, and when the automatic anti-locking program based on abnormal unlocking behavior is executed by a processor, the steps of the automatic anti-locking method based on abnormal unlocking behavior as described above are implemented.

[0089] In summary, the present invention provides an automatic anti-locking method, system, smart door lock and storage medium based on abnormal unlocking behavior, the method comprising: obtaining sensor data, the sensor data is obtained by real-time monitoring of multiple sensors installed on the smart door lock; analyzing the sensor data based on a preset recognition algorithm to determine whether there is abnormal unlocking behavior; when it is confirmed that there is abnormal unlocking behavior, starting the automatic anti-locking mechanism to perform anti-locking and triggering a preset alarm behavior. The present invention monitors a variety of sensor data, analyzes whether abnormal unlocking behavior occurs based on the multiple sensor data, and thus promptly performs anti-locking operations and sends alarm information after confirming that abnormal unlocking behavior occurs, thereby improving the security performance of the smart door lock and effectively preventing illegal intrusion.

[0090] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or smart door lock including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or smart door lock. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or smart door lock including the element.

[0091] Of course, those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware (such as a processor, a controller, etc.) through a computer program, and the program can be stored in a computer-readable storage medium that can be read by a computer, and the program can include the processes of the above-mentioned method embodiments when executed. The computer-readable storage medium can be a memory, a disk, an optical disk, etc.

[0092] It should be understood that the application of the present invention is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. An automatic anti-locking method based on abnormal unlocking behavior, It is characterized in that The automatic anti-locking method based on abnormal unlocking behavior includes: Acquire sensor data, where the sensor data is obtained by real-time monitoring of multiple sensors installed on the smart door lock; Analyze the sensor data based on a preset recognition algorithm to determine whether there is abnormal unlocking behavior; When abnormal unlocking behavior is confirmed, the automatic anti-locking mechanism is activated to anti-lock and trigger the preset alarm behavior.

2. The automatic anti-locking method based on abnormal unlocking behavior according to claim 1, It is characterized in that The sensors include vibration sensors, pressure sensors and sound sensors; The vibration sensor is used to detect abnormal vibrations to which the smart door lock is subjected; The pressure sensor is used to detect abnormal pressure changes on the smart door lock panel; The sound sensor is used to detect abnormal sounds in the smart door lock area.

3. The automatic anti-locking method based on abnormal unlocking behavior according to claim 2, It is characterized in that The preset recognition algorithms include a recognition algorithm based on vibration patterns, a recognition algorithm based on pressure changes, a recognition algorithm based on sound features, and a recognition algorithm based on behavior sequences.

4. The automatic anti-locking method based on abnormal unlocking behavior according to claim 1, It is characterized in that The abnormal unlocking behaviors include prying, hammering, master key unlocking, password or fingerprint brute force cracking, electronic interference and lock core injection.

5. The automatic anti-locking method based on abnormal unlocking behavior according to claim 3, It is characterized in that The analyzing the sensor data based on a preset recognition algorithm to determine whether there is abnormal unlocking behavior specifically includes: When the preset recognition algorithm is a recognition algorithm based on vibration patterns, the vibration data of the smart door lock is collected through a vibration sensor, and vibration features in the vibration data are extracted, wherein the vibration features include frequency, amplitude and duration, and the vibration features extracted in real time are matched with the pre-stored normal unlocking vibration patterns. If the difference exceeds a preset threshold, it is determined that there is abnormal unlocking behavior; When the preset recognition algorithm is a recognition algorithm based on pressure changes, the pressure changes of the smart door lock panel are monitored in real time through the pressure sensor, and the pressure range for normal unlocking is set. When the monitored pressure exceeds the pressure range, the dynamic pattern of the pressure change is analyzed and compared with the pressure change pattern of normal unlocking. If there is an abnormality in the pressure change, it is determined that there is an abnormal unlocking behavior; When the preset recognition algorithm is a recognition algorithm based on sound features, the sound signal in the smart door lock area is detected by a sound sensor, the sound signal is subjected to spectrum analysis, the frequency domain features of the sound are extracted, and the frequency domain features are analyzed using sound recognition technology. If the sound is abnormal, it is determined that there is abnormal unlocking behavior. When the preset recognition algorithm is a recognition algorithm based on behavior sequence, the behavior sequence of the user performing the unlocking operation under normal circumstances is recorded in advance, and a standard behavior sequence model is constructed. The user's unlocking behavior is tracked and recorded in real time, and the real-time behavior sequence collected in real time is compared with the pre-constructed standard behavior sequence. It is analyzed whether the duration of each behavior in the real-time behavior sequence falls within the normal range defined by the standard sequence. If the duration of a behavior exceeds the expected normal range, it is marked as a duration abnormality. It is verified whether the order of the real-time behavior sequence is consistent with the standard sequence. If the execution order of the behavior does not match the expectation, it is marked as a sequence abnormality. Based on the results of the duration analysis and sequence verification, if there is any duration abnormality or sequence abnormality, it means that the real-time behavior sequence is abnormal, and it is determined that there is abnormal unlocking behavior.

6. The automatic anti-locking method based on abnormal unlocking behavior according to claim 4, It is characterized in that When it is confirmed that there is abnormal unlocking behavior, the automatic anti-locking mechanism is activated to perform anti-locking and trigger the preset alarm behavior, which specifically includes: When it is confirmed that there is any one or more of the following behaviors: lock picking, hammering, master key unlocking, password or fingerprint brute force cracking, electronic interference and lock core injection, the automatic anti-locking mechanism is activated, and an anti-locking instruction is sent to the electromagnetic lock, and the electromagnetic lock is controlled to be activated to achieve anti-locking. When the electromagnetic lock fails, the backup mechanical locking mechanism is controlled to start and achieve anti-locking; At the same time as the door is automatically locked, the alarm information is sent to the bound user's mobile phone or other designated devices via the wireless network, and an audible and visual alarm is issued.

7. The automatic anti-locking method based on abnormal unlocking behavior according to claim 6, It is characterized in that The alarm information is sent to the bound user's mobile phone or other designated device via the wireless network, and then includes: If the user receives an alarm notification via mobile phone, the user is granted the authority to remotely control the door lock status.

8. An automatic anti-locking system based on abnormal unlocking behavior, It is characterized in that The automatic anti-locking system based on abnormal unlocking behavior includes: A data acquisition module is used to acquire sensor data, wherein the sensor data is obtained by real-time monitoring of multiple sensors installed on the smart door lock; A data analysis module, used to analyze the sensor data based on a preset recognition algorithm to determine whether there is abnormal unlocking behavior; The exception handling module is used to start the automatic anti-locking mechanism to perform anti-locking and trigger the preset alarm behavior when abnormal unlocking behavior is confirmed.

9. A smart door lock, It is characterized in that The smart door lock includes: a memory, a processor, and an automatic anti-locking program based on abnormal unlocking behavior stored in the memory and runable on the processor. When the automatic anti-locking program based on abnormal unlocking behavior is executed by the processor, the steps of the automatic anti-locking method based on abnormal unlocking behavior as described in any one of claims 1-7 are implemented.

10. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores an automatic anti-locking program based on abnormal unlocking behavior, and when the automatic anti-locking program based on abnormal unlocking behavior is executed by the processor, the steps of the automatic anti-locking method based on abnormal unlocking behavior according to any one of claims 1-7 are implemented.

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