Wake-up method and device of intelligent door lock, computer equipment and storage medium

Abstract

The invention relates to the technical field of intelligent locks, and discloses an intelligent door lock awakening method and device, computer equipment and a storage medium, and the method comprises the following steps: obtaining position information between an intelligent door lock and a target user at adjacent moments; determining whether the target user has a return intention or not according to the position information, and if yes, triggering a sensing positioning mechanism of the intelligent door lock; obtaining a thoracic cavity fluctuation signal of the target user based on a perception positioning mechanism, and determining a position relation of the target user relative to the intelligent door lock according to the thoracic cavity fluctuation signal; and when the position relation is the opposite relation, the intelligent door lock is controlled to execute awakening operation. The problem that the awakening and safety requirements of a user on the intelligent lock cannot be met due to the situation that an existing intelligent lock is awakened mistakenly and is opened mistakenly opposite to a door lock is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of smart locks, and in particular to a method, device, computer equipment and storage medium for waking up a smart door lock. Background Art

[0002] With the development of science and technology, smart locks are widely used in life. Smart locks with contactless biometric technology (such as face recognition and palm vein recognition) use human proximity sensing technology to wake up the smart lock and start the recognition module when someone approaches, bringing convenience. However, in actual use, the problems of false awakening and mistaken door opening are prominent. In areas with high personnel flow, such as the first floor, non-target customers passing by can easily cause the door lock to be frequently and invalidly awakened, consuming power quickly and increasing the cost of use; when the user locks and goes out and stays for a while, the door lock may mistakenly wake up and open the door, which goes against the user's wishes and affects the user experience.

[0003] At present, the existing technologies for the problem of mistaken door opening of smart locks have, to a certain extent, avoided the situation of mistaken door opening when users observe the door lock from the side through specific methods. However, the phenomenon of mistaken door opening when users are facing the door lock, such as changing shoes outside the door after locking it, cannot be effectively avoided. At the same time, in terms of dealing with the phenomenon of false awakening, the existing technologies have not provided effective solutions. When non-target users pass by the door lock, the door lock will still be awakened and the face recognition function will be activated, which makes it difficult to meet the user's demand for accurate awakening and safe use of smart locks. Summary of the invention

[0004] In view of this, the embodiments of the present invention provide a smart door lock wake-up method, device, computer equipment and storage medium to solve the problem that existing smart locks have the problems of false wake-up and mistaken door opening when facing the door lock, and cannot meet the user's wake-up and safety requirements for the smart lock.

[0005] In a first aspect, an embodiment of the present invention provides a method for waking up a smart door lock, the method comprising:

[0006] Obtain the location information between the smart door lock and the target user at adjacent times;

[0007] Determine whether the target user has a return intention according to the location information, and if the target user has the return intention, trigger the perception positioning mechanism of the smart door lock;

[0008] Acquire a chest rise and fall signal of the target user based on the perception positioning mechanism, and determine a position relationship of the target user relative to the smart door lock according to the chest rise and fall signal;

[0009] When the position relationship is a facing relationship, the smart door lock is controlled to perform a wake-up operation.

[0010] Further, determining whether the target user has a return intention according to the location information includes:

[0011] Determine a first distance value and a second distance value between the target user and the smart door lock according to the location information, wherein the first distance value is the distance between the target user and the smart door lock at a first moment, and the second distance value is the distance between the target user and the smart door lock at a second moment, and the first moment is smaller than the second moment;

[0012] Comparing the first distance value with the second distance value to obtain a comparison result;

[0013] Based on the comparison result, it is determined whether the target user has a return intention.

[0014] Further, determining whether the target user has a return intention based on the comparison result includes:

[0015] If the comparison result is that the first distance value is less than the second distance value, then calculating the distance difference between the first distance value and the second distance value, and comparing the distance difference with a preset threshold, and when the distance difference is greater than the preset threshold, determining that the target user has a return intention;

[0016] Alternatively, if the comparison result is that the first distance value is greater than or equal to the second distance value, and / or the distance difference is less than or equal to a preset threshold, it is determined that the target user has no return intention.

[0017] Furthermore, the step of acquiring the chest rise and fall signal of the target user based on the perception positioning mechanism includes:

[0018] Identifying a chest area of ​​the target user;

[0019] Calling the radar module of the smart door lock to send a transmission signal to the chest area;

[0020] An echo signal from the chest area is received, and the echo signal is screened according to a chest rise and fall rule to obtain a chest rise and fall signal of the target user.

[0021] Further, determining the position relationship of the target user relative to the smart door lock according to the chest rise and fall signal includes:

[0022] Extracting key features from the chest rise and fall signal;

[0023] Determining the attenuation direction and angle deviation of the chest cavity rise and fall signal according to the key features;

[0024] The position relationship of the target user relative to the smart door lock is determined based on the attenuation direction and the angle deviation.

[0025] Further, determining the position relationship of the target user relative to the smart door lock based on the attenuation direction and the angle deviation includes:

[0026] If the attenuation direction is uniform and unbiased and the angle deviation is within a first preset range centered on the central axis of the smart door lock, the position relationship of the target user relative to the smart door lock is a facing relationship;

[0027] Or, if the attenuation direction is from left to right and the angle deviation is within a second preset range to the right of the central axis of the smart door lock, the position relationship of the target user relative to the smart door lock is a left-side relationship;

[0028] Alternatively, if the attenuation direction is from right to left and the angle deviation is within a third preset range to the right of the central axis of the smart door lock, the position relationship of the target user relative to the smart door lock is a right-side relationship.

[0029] Furthermore, the method further comprises:

[0030] Obtain the current time period of the smart door lock;

[0031] Querying a threshold database of the smart door lock for a preset threshold corresponding to the current time period;

[0032] The preset threshold is used to determine whether the target user within the preset range of the smart door lock has the intention to return.

[0033] In a second aspect, an embodiment of the present invention provides a smart door lock wake-up device, the device comprising:

[0034] The first acquisition module is used to obtain the location information between the smart door lock and the target user at adjacent moments;

[0035] A determination module, used to determine whether the target user has a return intention according to the location information, and if so, trigger the perception and positioning mechanism of the smart door lock;

[0036] A second acquisition module, configured to acquire a chest rise and fall signal of the target user based on the perception positioning mechanism, and determine a position relationship of the target user relative to the smart door lock according to the chest rise and fall signal;

[0037] The control module is used to control the smart door lock to perform a wake-up operation when the position relationship is a positive relationship.

[0038] In a third aspect, an embodiment of the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the method of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0039] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method of the first aspect or any corresponding embodiment thereof.

[0040] The method provided in the embodiment of the present application has the following beneficial effects:

[0041] The method provided in the embodiment of the present application can track the dynamic changes of the position of the user and the smart door lock in real time by obtaining the position information at different times, and provides the necessary basis for accurately analyzing the user behavior pattern. By analyzing the position information to determine whether the user has the intention to return, the invalid awakening of the door lock when the non-target user passes by or the user approaches unintentionally is avoided, the power consumption of the door lock is reduced, the use time of the door lock is extended, and the user experience is also improved, making the awakening of the door lock more intelligent and accurate. The position relationship is determined by the chest rise and fall signal, which is more accurate than the traditional method that only relies on human proximity sensing. The chest rise and fall signal has uniqueness and stability, and can effectively eliminate external interference, so as to determine the position relationship between the user and the door lock, provide a basis for whether to wake up the door lock, and further reduce the risk of false awakening and false opening of the door. Only when the user is facing the door lock, it is considered that there is an intention to open the door, which avoids the false awakening and false opening of the door lock when the user does not intend to open the door (such as passing by the side, staying for a short time to organize items, etc.), ensuring the safety and convenience of the user, and greatly improving the safety and user experience of the smart lock. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 is a flowchart of a method for waking up a smart door lock according to an embodiment of the present invention;

[0044] Figure 2 is a flowchart of another smart door lock wake-up method according to an embodiment of the present invention;

[0045] Figure 3is a schematic diagram of the positional relationship between the smart door lock and the user side according to an embodiment of the present invention;

[0046] Figure 4 is a schematic diagram of the position relationship between the smart door lock and the user according to an embodiment of the present invention;

[0047] Figure 5 is a structural block diagram of a wake-up device for a smart door lock according to an embodiment of the present invention;

[0048] Figure 6 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0050] According to an embodiment of the present invention, a wake-up method, apparatus, computer device and storage medium for a smart door lock are provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in an order different from that shown here.

[0051] In this embodiment, a method for waking up a smart door lock is provided. Figure 1 is a flow chart of a method for waking up a smart door lock according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0052] Step S11, obtaining the location information between the smart door lock and the target user at adjacent moments.

[0053] In the embodiment of the present application, the position information between the smart door lock and the target user at adjacent moments can be realized by the proximity sensing module equipped with the smart lock. The proximity sensing module has the function of detecting the distance. When the user is detected, the distance between the user and the door lock when the user is first detected is recorded as the first distance value. After a short time interval, the distance between the user and the door lock is detected again to obtain the second distance value.

[0054] The method provided in the embodiment of the present application is based on the way that the proximity sensing module obtains the distance information of adjacent moments in real time, which provides a direct and critical data basis for the subsequent judgment of whether the user has the intention to return. It can not only capture the dynamic changes in the distance between the user and the door lock, but also provide timeliness and consistency data support for subsequent analysis by comparing the distance at adjacent moments, making the judgment of the user's behavioral intention more accurate and reliable.

[0055] Step S12, determining whether the target user has the intention to return based on the location information, and if so, triggering the perception and positioning mechanism of the smart door lock.

[0056] In the embodiment of the present application, determining whether the target user has a return intention according to the location information includes the following steps A1-A3:

[0057] Step A1, determine the first distance value and the second distance value between the target user and the smart door lock based on the location information, wherein the first distance value is the distance between the target user and the smart door lock at the first moment, and the second distance value is the distance between the target user and the smart door lock at the second moment, and the first moment is smaller than the second moment.

[0058] Specifically, when the proximity sensing module detects that the target user enters its sensing range, it records the distance between the user and the smart door lock at this time. This distance is the first distance value, which represents the distance between the target user and the smart door lock at the first moment. Subsequently, the proximity sensing module continues to monitor, and after a set time interval (which can be determined based on the actual scenario and algorithm optimization to ensure that the user's relatively stable movement state changes can be captured), the distance between the user and the smart door lock is measured again to obtain a second distance value, which is the distance between the target user and the smart door lock at the second moment.

[0059] Step A2: compare the first distance value with the second distance value to obtain a comparison result.

[0060] Specifically, the microprocessor inside the smart lock is responsible for performing this comparison operation. The microprocessor quickly and accurately compares the first distance value with the second distance value. It uses an efficient digital comparison algorithm that can not only quickly determine the size relationship between the two distance values, but also intelligently correct possible numerical errors during the comparison process (for example, taking into account the slight measurement error of the sensing module, it is adjusted through a preset error correction table).

[0061] Step A3: determine whether the target user has a return intention based on the comparison result.

[0062] In an embodiment of the present application, step A3 includes: if the comparison result is that the first distance value is less than the second distance value, then calculating the distance difference between the first distance value and the second distance value, and comparing the distance difference with a preset threshold value, and when the distance difference is greater than the preset threshold value, determining that the target user has the intention to return; or, if the comparison result is that the first distance value is greater than or equal to the second distance value, and / or the distance difference is less than or equal to the preset threshold value, determining that the target user does not have the intention to return.

[0063] Specifically, Figure 2 As shown in the figure, the process of preventing false awakening of the smart lock is that the proximity sensing module first detects whether there is a person approaching. If no person is detected, the process ends; if a person is detected, the distance a from the first detected person to the door lock is recorded. Then the distance b from the person to the door lock is recorded again, and then the size of b and a is compared. If b is not less than a, it returns to re-record the distance b; if b is less than a, the difference between a and b is further calculated and compared with the preset threshold. If the difference is not greater than the preset threshold, it also returns to re-record the distance b; if the difference is greater than the preset threshold, the door lock is awakened and the contactless biometric recognition function is turned on, and finally the process ends. This flowchart avoids false awakening of the smart lock by detecting the change in the distance from the person to the door lock.

[0064] As an example, assume that a smart door lock is installed at the door of a resident's home for the user to enter and exit daily.

[0065] Scenario 1: When the proximity sensing module of the smart door lock detects a user, the distance between the user and the door lock is recorded as 2 meters at the first moment. At the second moment, after a set time interval of 2 seconds, the distance is detected to be 1.5 meters. Since the first distance value is less than the second distance value, it indicates that the user is approaching the door lock. The calculated distance difference is 2-1.5=0.5 meters. Assuming that the preset threshold of this scenario is 0.3 meters, since 0.5 meters is greater than 0.3 meters, it can be determined that the target user has the intention to return, and is likely to go home to open the door.

[0066] Scenario 2: On the one hand, if the distance between the user and the door lock is detected to be 1.8 meters at the first moment and becomes 2 meters at the second moment, that is, the first distance value is greater than the second distance value, indicating that the user is moving away from the door lock, it can be directly determined that the target user has no intention to return and may continue to move forward after going out. On the other hand, if the distance is 2 meters at the first moment and becomes 1.9 meters at the second moment, although the first distance value is less than the second distance value, the user seems to be approaching the door lock, but the calculated distance difference is 2-1.9=0.1 meters, which is less than the preset threshold of 0.3 meters, indicating that the user's approach is small, and may just be approaching by chance when passing by, and not explicitly returning to open the door, so it is determined that the target user has no intention to return.

[0067] The method provided in the embodiment of the present application obtains the distance between the target user and the smart door lock at different times, that is, the first distance value and the second distance value, and compares them, and then determines whether there is an intention to return based on the comparison result. Such a design can use the key information of the change in the distance between the user and the smart door lock to preliminarily judge the user's action intention in a relatively simple and intuitive way, avoid the smart door lock from performing unnecessary subsequent operations on users who have no intention to return, effectively reduce the probability of false awakening, and improve the use efficiency and energy efficiency of the smart door lock. At the same time, by setting a preset threshold for further precise judgment, it is possible to more accurately identify the user's true intention and reduce misjudgment, thereby better meeting the user's demand for the accuracy of smart lock wake-up.

[0068] Step S13, obtaining the chest rise and fall signal of the target user based on the perception positioning mechanism, and determining the position relationship of the target user relative to the smart door lock according to the chest rise and fall signal.

[0069] In the embodiment of the present application, obtaining the chest rise and fall signal of the target user based on the perception positioning mechanism includes the following steps B1-B3:

[0070] Step B1, identifying the chest area of ​​the target user.

[0071] Specifically, the smart lock first uses the built-in millimeter-wave radar to perform a preliminary scan of the human body contour. The millimeter-wave radar outlines the approximate shape and position information of the human body. At the same time, the thermal distribution image of the human body is obtained based on the thermal imaging sensor. Since the metabolism of the chest area is relatively active, the thermal characteristics different from the surrounding environment and other parts of the body will be presented in the thermal image. Then, the generated contour image and thermal imaging image are fused and analyzed through a deep learning algorithm. The algorithm has been trained with a large number of human data samples and can identify the position of the chest area in the fused image. For example, the characteristic patterns of the chest area in two modal images are learned, such as the specific shape and reflection characteristics of the chest in the radar image, and the thermal radiation distribution characteristics in the thermal imaging image, so as to distinguish the chest area.

[0072] Step B2, calling the radar module of the smart door lock to send a transmission signal to the chest area.

[0073] Specifically, after identifying the chest area of ​​the target user, the smart door lock adjusts the transmitting antenna array of the radar module according to its spatial position information. By changing the phase and amplitude of the transmitted signals of each antenna, the radar transmit signal forms a beam focused on the chest area in space. This adaptive beamforming technology can not only increase the energy density of the signal reaching the chest area, enhance the strength and quality of subsequent echo signals, but also reduce interference to other areas and prevent misjudgment due to reflected signals from the surrounding environment. In addition, to adapt to users of different heights and distances, the radar module will refer to the previously obtained distance information between the user and the door lock, and dynamically adjust the frequency and power of the transmitted signal. For example, for users who are farther away, appropriately increase the power and adjust the frequency to ensure that the signal effectively reaches the chest area and obtains a clear echo.

[0074] Step B3, receiving the echo signal from the chest area, and filtering the echo signal according to the chest rise and fall rule to obtain the chest rise and fall signal of the target user.

[0075] Specifically, after the radar module signal is reflected back from the chest area, the smart door lock uses a high-speed signal collector to capture the echo signal. The signal is complex, with both effective chest fluctuation signals and environmental noise interference signals. In order to filter out the chest fluctuation signal, a signal recognition model based on a deep learning algorithm can be used. This model is pre-trained on a large number of echo signal data sets containing different chest fluctuation characteristics of human bodies and various types of environmental noise, and can accurately identify the typical patterns of chest fluctuation signals. It distinguishes signal fragments that meet the chest fluctuation characteristics by analyzing the multi-dimensional characteristics of the echo signal, such as amplitude, frequency, and phase. At the same time, considering that environmental differences will affect noise intensity and signal characteristics, a dynamic threshold mechanism is introduced. The smart door lock monitors the overall characteristics of the echo signal in real time, and dynamically adjusts the threshold for filtering signals based on factors such as signal average strength and noise distribution. For example, when the environmental noise is large, the threshold is increased to filter out more noise; when the environment is quiet, the threshold is lowered to prevent missing weak effective signals. The deep learning model works in conjunction with the dynamic threshold, enabling the smart door lock to filter out chest fluctuation signals from complex echo signals.

[0076] The method provided in the embodiment of the present application identifies the chest area of ​​the target user, calls the radar module to send a transmission signal to the area, receives the echo signal and screens it according to the chest rise and fall law to obtain the chest rise and fall signal. This series of steps uses radar technology to obtain signals based on the unique physiological characteristics of the human chest rise and fall, which can accurately locate and obtain specific signals related to the user, providing a reliable data basis for the subsequent determination of the position relationship between the user and the smart door lock, effectively improving the accuracy and reliability of the judgment, and helping to solve the problem of misjudgment that may occur in the existing smart lock in locating the user's position relationship, and enhancing the safety and intelligence of the smart door lock.

[0077] In the embodiment of the present application, determining the position relationship of the target user relative to the smart door lock according to the chest rise and fall signal includes the following steps C1-C3:

[0078] Step C1, extracting key features from the chest rise and fall signal.

[0079] Specifically, first, the chest rise and fall signal is processed using time-frequency analysis techniques, such as short-time Fourier transform or wavelet transform, and converted from a single time domain representation to a time-frequency two-dimensional image, presenting the frequency characteristics of the signal changing over time in the two dimensions of time and frequency. Then, from the time-frequency analysis results, conventional features such as amplitude and frequency, as well as features such as phase change, energy distribution and signal self-similarity are extracted. These features reflect the subtle dynamics of chest rise and fall movement, the energy concentration of the signal in different frequency bands, and the inherent pattern. Then, through the intelligent feature screening algorithm based on machine learning, it is allowed to learn a large amount of chest rise and fall signal data marked with different positional relationships, and automatically identify the most critical feature combination for determining the user's positional relationship. For example, through classification algorithms such as random forests or support vector machines, the optimal feature subset is found in the feature space to maximize the distinction between the user's positional relationship facing, left side or right side, thereby extracting the key features for determining the user's positional relationship.

[0080] Step C2, determining the attenuation direction and angle deviation of the chest rise and fall signal according to the key features.

[0081] Specifically, the smart door lock can use a multi-dimensional joint analysis method to determine the attenuation direction and angle deviation based on key features. When determining the attenuation direction, the echo signal received by the radar module is divided into multiple small areas in the horizontal direction. By comparing the changes in signal strength in each area, if the changes are uniform and unbiased, it is initially judged as uniform and unbiased attenuation; if one side is strong and gradually weakens to the other side, such as from left to right, it is judged to be attenuated from left to right, and vice versa. When determining the angle deviation, the phase difference positioning technology and machine learning assisted calibration are combined, and the phase difference principle of radar signal transmission and reception is used to calculate the signal propagation angle through a mathematical model algorithm. At the same time, a machine learning model is introduced. The model recognizes the complex relationship between signal characteristics and actual angle deviations, and calibrates and optimizes the angle calculated by the phase difference, so as to determine the angle deviation, laying the foundation for accurately judging the user's position relative to the smart door lock.

[0082] Step C3, determining the position relationship of the target user relative to the smart door lock based on the attenuation direction and the angle deviation.

[0083] In an embodiment of the present application, step C3 includes the following steps: if the attenuation direction is uniform and unbiased and the angle deviation is in a first preset range centered on the central axis of the smart door lock, the position relationship of the target user relative to the smart door lock is a head-on relationship; or, if the attenuation direction is from left to right and the angle deviation is in a second preset range to the right of the central axis of the smart door lock, the position relationship of the target user relative to the smart door lock is a left-side relationship; or, if the attenuation direction is from right to left and the angle deviation is in a third preset range to the right of the central axis of the smart door lock, the position relationship of the target user relative to the smart door lock is a right-side relationship.

[0084] It should be noted that if Figure 3 As shown in the figure, the position relationship of the two human models relative to the smart door lock is shown. The smart door lock is located in the upper middle position of the figure. The two human models are located on the left and right sides of the smart door lock respectively. The position of the human model on the left is the left-side relationship, and the position of the human model on the right is the right-side relationship. Figure 4 The figure shows the positional relationship between a human model and a smart door lock. The human model is located in front of the smart door lock, which is marked as facing, indicating that the human model is facing the smart door lock. This figure is used to intuitively illustrate the scenario where the user is in a facing relationship with the smart door lock, and the smart door lock needs to be awakened in this scenario.

[0085] Specifically, the smart door lock can receive the attenuation direction and angle deviation data in real time through the built-in position relationship determination engine. If the attenuation direction is uniform and unbiased and the angle deviation is within the first preset range centered on the central axis of the door lock (set after a large number of experiments and data analysis, it can reflect that the user is facing the door lock), it is determined to be a facing relationship; if the attenuation direction is from left to right and the angle deviation is within the second preset range to the right of the central axis (after calibration, combined with the attenuation direction, it can characterize that the user is facing the door lock on the left side), it is determined to be a left-side facing relationship; conversely, when the attenuation direction is from right to left and the angle deviation is within the third preset range to the right of the central axis, it is determined to be a right-side facing relationship.

[0086] The method provided in the embodiment of the present application extracts the key features in the chest rise and fall signal, determines the attenuation direction and angle deviation of the signal based on the key features, and determines the position relationship based on the attenuation direction and angle deviation. This method of determining the position relationship based on signal feature analysis can deeply explore the position information contained in the chest rise and fall signal, and accurately judge the relative position of the user and the smart door lock through a detailed analysis of the attenuation direction and angle deviation. Compared with the traditional simple position judgment method, it is more scientific and accurate, effectively solves the problem of mistakenly opening the door when facing the door lock, greatly improves the accuracy of the smart door lock's judgment in different positions, and further guarantees the user's safety needs.

[0087] Step S14, when the position relationship is a facing relationship, control the smart door lock to perform a wake-up operation.

[0088] In an embodiment of the present application, when a signal indicating that the position relationship is a positive relationship is received, the pre-wake-up check mechanism is triggered. The mechanism may include detecting the power status of the door lock itself, the system operation status, and the connection status with peripheral devices (such as a smart home system), etc., to ensure that the door lock is in a ready state to wake up normally and perform subsequent operations. After confirming that the door lock is in good condition in all aspects, a wake-up algorithm is used to activate the smart door lock. The algorithm can not only quickly start the various functional modules of the door lock, but also intelligently adjust the mode and degree of wake-up according to the current environmental factors (such as time period, ambient light intensity, etc.). For example, at night, in order to avoid disturbing the user, the wake-up operation will be relatively gentle and reduce unnecessary prompt sounds; during the day, wake-up feedback can be performed more quickly and clearly.

[0089] In addition, in order to improve security and accuracy, the system can also perform multiple verifications on this wake-up operation. On the one hand, it will reconfirm whether the currently detected positive relationship signal is continuously stable to prevent false wake-ups due to short-term signal fluctuations; on the other hand, it will combine the previously acquired user behavior pattern data (such as the user's usual entry and exit time, usage habits, etc.) to determine whether this wake-up is in line with the user's normal behavior logic. Only after all verifications are passed, the smart door lock will officially perform the wake-up operation to provide users with a safe and convenient user experience.

[0090] In the embodiment of the present application, the method further includes the following steps D1-D3:

[0091] Step D1, obtaining the current time period of the smart door lock.

[0092] Specifically, the smart door lock has a built-in real-time clock module, which is synchronized regularly with the network time protocol server to ensure the accuracy of the time. In order to more intelligently adapt to the time zone differences in different regions, when the door lock is first installed, the user can set the time zone through the mobile phone APP or the door lock operation panel. The system will automatically obtain the current local time according to the set time zone and real-time clock, and divide the day into different time periods, such as the pre-defined 7:00-20:00 as the daytime time period and 20:00-7:00 as the nighttime time period. At the same time, in order to cope with special time adjustments such as daylight saving time, the system can also have an automatic identification and adjustment mechanism, which can automatically adjust the time according to the daylight saving time rules in the area and accurately determine the current time period.

[0093] Step D2, query the threshold database of the smart door lock for the preset threshold corresponding to the current time period.

[0094] Specifically, the smart door lock is equipped with a dedicated storage chip for building a threshold database, which uses time periods as indexes and stores distance threshold data corresponding to different time periods. After obtaining the current time period, the threshold database is searched based on the time period information. For example, if the current time period is daytime, the record corresponding to the time period is located, and the set higher distance threshold, such as 1.5 meters, is extracted; if it is nighttime, the lower distance threshold, such as 0.8 meters, is extracted.

[0095] Step D3, using a preset threshold to determine whether the target user within the preset range of the smart door lock has the intention to return.

[0096] Specifically, after obtaining the preset threshold corresponding to the current time period from the threshold database, the smart door lock will compare this preset threshold with the distance difference calculated previously. If the distance difference is greater than the preset threshold, combined with the judgment that the target user is close to the door lock (the first distance value is less than the second distance value), it is further determined that the target user has the intention to return. This method of dynamically adjusting the preset threshold based on the time period and judging the user's intention to return accordingly fully considers the characteristics of human activities in different time periods. For example, there are relatively fewer human activities at night, and a small distance change may mean that the user has the intention to return, thereby improving the accuracy of the judgment and the safety and convenience of using smart door locks.

[0097] The method provided in the embodiment of the present application obtains the current time period of the smart door lock, queries the preset threshold corresponding to the time period in the threshold database, and uses the preset threshold to determine whether the target user within the preset range of the smart door lock has the intention to return. This step takes into account that the behavior patterns of users in different time periods may be different. By setting the preset thresholds corresponding to different time periods, the standard for judging the user's intention to return can be flexibly adjusted according to the actual situation, so that the wake-up judgment of the smart door lock is more in line with the actual needs of users in different time periods, further improving the accuracy and rationality of the wake-up judgment, and better meeting the user's personalized use needs for the smart lock in different time scenarios.

[0098] In this embodiment, a wake-up device for a smart door lock is also provided, which is used to implement the above embodiments and preferred implementations, and will not be repeated here. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0099] This embodiment provides a smart door lock wake-up device, such as Figure 5 As shown, including:

[0100] An acquisition module 51 is used to acquire the location information between the smart door lock and the target user at adjacent moments;

[0101] The determination module 52 is used to determine whether the target user has the intention to return according to the location information, and if so, trigger the perception and positioning mechanism of the smart door lock;

[0102] A sensing module 53 is used to obtain a chest rise and fall signal of a target user based on a sensing positioning mechanism, and determine a position relationship of the target user relative to the smart door lock according to the chest rise and fall signal;

[0103] The control module 54 is used to control the smart door lock to perform a wake-up operation when the position relationship is a facing relationship.

[0104] In an optional embodiment of the present application, a determination module 52 is used to determine a first distance value and a second distance value between the target user and the smart door lock based on the location information, wherein the first distance value is the distance between the target user and the smart door lock at a first moment, and the second distance value is the distance between the target user and the smart door lock at a second moment, and the first moment is smaller than the second moment; the first distance value is compared with the second distance value to obtain a comparison result; and based on the comparison result, it is determined whether the target user has the intention to return.

[0105] In an optional embodiment of the present application, the determination module 52 is used to calculate the distance difference between the first distance value and the second distance value if the comparison result is that the first distance value is less than the second distance value, and compare the distance difference with a preset threshold value, and when the distance difference is greater than the preset threshold value, determine that the target user has the intention to return; or, if the comparison result is that the first distance value is greater than or equal to the second distance value, and / or the distance difference is less than or equal to the preset threshold value, determine that the target user does not have the intention to return.

[0106] In an optional embodiment of the present application, the perception module 53 includes an acquisition submodule and a determination submodule;

[0107] The acquisition submodule is used to identify the chest area of ​​the target user; call the radar module of the smart door lock to send a transmission signal to the chest area; receive the echo signal from the chest area, and filter the echo signal according to the chest rise and fall law to obtain the chest rise and fall signal of the target user.

[0108] A submodule is determined to extract key features from the chest rise and fall signal; determine the attenuation direction and angle deviation of the chest rise and fall signal based on the key features; and determine the position relationship of the target user relative to the smart door lock based on the attenuation direction and angle deviation.

[0109] A determination submodule is used to determine that if the attenuation direction is uniform and unbiased and the angular deviation is within a first preset range centered on the central axis of the smart door lock, then the position relationship of the target user relative to the smart door lock is a head-on relationship; or, if the attenuation direction is from left to right and the angular deviation is within a second preset range to the right of the central axis of the smart door lock, then the position relationship of the target user relative to the smart door lock is a left-side relationship; or, if the attenuation direction is from right to left and the angular deviation is within a third preset range to the right of the central axis of the smart door lock, then the position relationship of the target user relative to the smart door lock is a right-side relationship.

[0110] In an optional embodiment of the present application, the device also includes: a query module for obtaining the current time period of the smart door lock; querying the preset threshold corresponding to the current time period in the threshold database of the smart door lock; and using the preset threshold to determine whether the target user within the preset range of the smart door lock has the intention to return.

[0111] See also Figure 6 , Figure 6 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 6 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system).

[0112] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0113] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0114] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created by the use of a computer device based on the presentation of a small program landing page, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0115] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0116] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0117] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0118] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for waking up a smart door lock, characterized in that: The method comprises: Obtain the location information between the smart door lock and the target user at adjacent times; Determine whether the target user has a return intention according to the location information, and if the target user has the return intention, trigger the perception positioning mechanism of the smart door lock; Acquire a chest rise and fall signal of the target user based on the perception positioning mechanism, and determine a position relationship of the target user relative to the smart door lock according to the chest rise and fall signal; When the position relationship is a facing relationship, the smart door lock is controlled to perform a wake-up operation.

2. The method according to claim 1, characterized in that: The determining, according to the location information, whether the target user has a return intention includes: Determine a first distance value and a second distance value between the target user and the smart door lock according to the location information, wherein the first distance value is the distance between the target user and the smart door lock at a first moment, and the second distance value is the distance between the target user and the smart door lock at a second moment, and the first moment is smaller than the second moment; Comparing the first distance value with the second distance value to obtain a comparison result; Based on the comparison result, it is determined whether the target user has a return intention.

3. The method according to claim 2, characterized in that The determining whether the target user has a return intention based on the comparison result includes: If the comparison result is that the first distance value is less than the second distance value, then calculating the distance difference between the first distance value and the second distance value, and comparing the distance difference with a preset threshold, and when the distance difference is greater than the preset threshold, determining that the target user has a return intention; Alternatively, if the comparison result is that the first distance value is greater than or equal to the second distance value, and / or the distance difference is less than or equal to a preset threshold, it is determined that the target user has no return intention.

4. The method according to claim 1, characterized in that The acquiring the chest rise and fall signal of the target user based on the perception positioning mechanism includes: Identifying a chest area of ​​the target user; Calling the radar module of the smart door lock to send a transmission signal to the chest area; An echo signal from the chest area is received, and the echo signal is screened according to a chest rise and fall rule to obtain a chest rise and fall signal of the target user.

5. The method according to claim 1, characterized in that: The determining the position relationship of the target user relative to the smart door lock according to the chest rise and fall signal includes: Extracting key features from the chest rise and fall signal; Determining the attenuation direction and angle deviation of the chest cavity rise and fall signal according to the key features; The position relationship of the target user relative to the smart door lock is determined based on the attenuation direction and the angle deviation.

6. The method according to claim 5, characterized in that The determining the position relationship of the target user relative to the smart door lock based on the attenuation direction and the angle deviation includes: If the attenuation direction is uniform and unbiased and the angle deviation is within a first preset range centered on the central axis of the smart door lock, the position relationship of the target user relative to the smart door lock is a positive relationship; Or, if the attenuation direction is from left to right and the angle deviation is within a second preset range to the right of the central axis of the smart door lock, the position relationship of the target user relative to the smart door lock is a left-side relationship; Alternatively, if the attenuation direction is from right to left and the angle deviation is within a third preset range to the right of the central axis of the smart door lock, the position relationship of the target user relative to the smart door lock is a right-side relationship.

7. The method according to claim 2, characterized in that: The method further comprises: Obtain the current time period of the smart door lock; Querying a threshold database of the smart door lock for a preset threshold corresponding to the current time period; The preset threshold is used to determine whether the target user within the preset range of the smart door lock has the intention to return.

8. A smart door lock wake-up device, characterized in that: The device comprises: The first acquisition module is used to obtain the location information between the smart door lock and the target user at adjacent moments; A determination module, used to determine whether the target user has a return intention according to the location information, and if so, trigger the perception and positioning mechanism of the smart door lock; A second acquisition module, configured to acquire a chest rise and fall signal of the target user based on the perception positioning mechanism, and determine a position relationship of the target user relative to the smart door lock according to the chest rise and fall signal; The control module is used to control the smart door lock to perform a wake-up operation when the position relationship is a positive relationship.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 7.

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