UWB-based information identification module control method and device, equipment and storage medium

Abstract

The invention relates to the technical field of passage detection, and discloses a UWB-based information identification module control method, device and equipment and a storage medium, which are applied to intelligent door lock equipment, and the intelligent door lock equipment comprises a UWB module and an information identification module. The method comprises the following steps: acquiring position information, a moving direction and a moving speed of a target user detected by a UWB module in a preset detection range; obtaining a prediction result based on the position information, the moving direction and the moving speed; and determining whether to wake up the information identification module to perform user identity identification according to the prediction result. The number of times of waking up the information identification module of the intelligent door lock equipment when a person who does not want to pass by the intelligent door lock equipment can be reduced, so that the power consumption of the intelligent door lock equipment can be reduced, an information identification target can be waken up in advance for a user who wants to pass by, and the user experience is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of passage detection, and in particular to a UWB-based information recognition module control method, device, equipment and storage medium. Background Art

[0002] Smart door lock devices are usually installed in specific scenarios. For example, smart door locks can be installed at locations such as entrance doors in residential areas. Smart door locks can also be installed in public places such as office buildings, stations, and airports. Smart access control devices are generally equipped with a location detection function. When a person appears within the detection distance of the smart door lock, the information recognition module is immediately awakened, and the identification of the person is determined to determine whether to perform the unlocking action. When there are many people within the detection distance of the smart door lock, the information recognition module is always activated, but these people are not all people who want to pass. They may be cleaning staff, passers-by, neighbors of residents, etc. Such frequent awakening of the information recognition module will cause the smart door lock device to consume a lot of power, and it is impossible to wake up the information recognition module in advance for users who want to pass, which reduces the user experience.

[0003] Therefore, there is an urgent need for an intelligent information recognition module control method that can predict the user's moving direction and speed to determine whether to wake up the information recognition module of the smart door lock. Summary of the invention

[0004] In view of this, the present application provides a UWB-based information recognition module control method, device, equipment and storage medium to reduce the power consumption of smart door lock equipment and improve user experience. The technical solution is as follows.

[0005] In a first aspect, the present invention provides a UWB-based information identification module control method, which is applied to a smart door lock device, wherein the smart door lock device includes a UWB module and an information identification module, and the method includes:

[0006] The motion state of the target user detected by the UWB module within a preset detection range is obtained; the motion state includes the location information, moving direction and moving speed of the target user.

[0007] Based on the location information, the moving direction and the moving speed, a prediction result is obtained; the prediction result is used to indicate the target user's interaction behavior with the smart door lock device in a future time period.

[0008] Determine whether to wake up the information recognition module according to the prediction result; the information recognition module is used to identify the identity information of the target user.

[0009] The UWB-based information identification module control method provided by the present invention has the following advantages.

[0010] The UWB-based information identification module control method of the present invention is applied to a smart door lock device. The smart door lock device includes a UWB module and an information identification module. The smart door lock device detects the motion state of the target user through the UWB module to obtain the moving direction and moving speed of the target user. The UWB module adopts UWB wireless communication technology. UWB technology belongs to the communication technology within the medium and short distance range. It can achieve centimeter-level positioning accuracy, which is very suitable for the indoor environment where the smart door lock device is located. It has low transmission power and strong anti-interference ability, and can still maintain stable working performance in a complex electromagnetic environment. Subsequently, a prediction is made based on the moving direction and moving speed to obtain a prediction result, which is used to determine whether it is necessary to wake up the information identification module of the smart door lock device. The prediction can directly obtain the prediction result according to the moving direction and moving speed through a pre-trained neural network model, or it can predict the movement trajectory of the target user based on the moving direction and moving speed, and then match it with the pre-stored movement trajectory. Since the predicted motion trajectory is the motion trajectory of a person with access rights within the preset detection range, when the predicted motion trajectory matches the pre-stored motion trajectory successfully, it indicates that the person is likely to be a person who wants to pass through, and the information recognition module needs to be awakened. The information recognition module can be awakened in advance for the person who wants to pass through, thereby improving the user experience. When the match is unsuccessful, it indicates that the person is likely to be a cleaning staff, a passerby, or other person who does not want to pass through. At this time, there is no need to wake up the information recognition module, which can reduce the number of times the information recognition module is awakened, thereby reducing the power consumption of the smart door lock device.

[0011] In an optional implementation, obtaining a prediction result based on the moving direction and the moving speed includes: inputting the moving direction and the moving speed into a pre-built prediction model to obtain the prediction result.

[0012] In an optional embodiment, a prediction result is obtained based on the moving direction and the moving speed, including: inputting the moving direction and the moving speed into a pre-built prediction model to obtain a predicted motion trajectory of the target user; matching the predicted motion trajectory with a pre-stored motion trajectory to obtain a matching result; the pre-stored motion trajectory is a pre-stored motion trajectory of a person with access authority within the preset detection range; and obtaining the prediction result based on the matching result.

[0013] In an optional implementation, the prediction model is obtained by training a preset neural network model.

[0014] In an optional embodiment, the motion state of the target user detected by the UWB module within a preset detection range is obtained, including: when the UWB module detects that the target user enters the preset detection range, collecting the location information of the target user at preset time intervals to obtain a curve of the change of the location information over time; based on the curve of the change of the location information over time, obtaining the moving direction and speed of the target user.

[0015] In an optional embodiment, the UWB module includes a first antenna and a second antenna, the first antenna and the second antenna are symmetrically distributed on the UWB module, and the target user carries a UWB tag; the method also includes: simultaneously receiving the UWB signal emitted by the UWB tag through the first antenna and the second antenna, and obtaining the phase difference and time difference of the UWB signal reaching the first antenna and the second antenna; based on the phase difference and the time difference, obtaining the location information of the target user.

[0016] In an optional implementation, the method further includes: when the UWB module fails to detect the target user within the preset detection range, or detects that the target user leaves the preset detection range, stopping detecting the motion state of the target user within the preset detection range.

[0017] In a second aspect, the present invention provides a UWB-based information identification module control device, which is applied to a smart door lock device. The smart door lock device includes a UWB module and an information identification module. The device includes:

[0018] The acquisition module is used to acquire the motion state of the target user detected by the UWB module within a preset detection range; the motion state includes the location information, moving direction and moving speed of the target user.

[0019] The prediction module is used to obtain a prediction result based on the location information, the moving direction and the moving speed; the prediction result is used to indicate the interaction behavior of the target user with the smart door lock device in a future time period.

[0020] The wake-up module is used to determine whether to wake up the information recognition module according to the prediction result; the information recognition module is used to identify the identity information of the target user.

[0021] In an optional implementation, the prediction module is specifically used to: input the moving direction and the moving speed into a pre-built prediction model to obtain the prediction result.

[0022] In an optional embodiment, the prediction module is specifically used to: input the moving direction and the moving speed into a pre-built prediction model to obtain the predicted motion trajectory of the target user; match the predicted motion trajectory with the pre-stored motion trajectory to obtain a matching result; the pre-stored motion trajectory is a pre-stored motion trajectory of a person with access authority within the preset detection range; and obtain the prediction result based on the matching result.

[0023] In an optional embodiment, the acquisition module is specifically used to: when the UWB module detects that the target user enters the preset detection range, collect the location information of the target user at a preset time interval to obtain a curve of the change of the location information over time; based on the curve of the change of the location information over time, obtain the moving direction and speed of the target user.

[0024] In an optional implementation, the acquisition module is further used to: when the UWB module fails to detect the target user within the preset detection range, or detects that the target user leaves the preset detection range, stop detecting the motion state of the target user within the preset detection range.

[0025] In a third aspect, 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 UWB-based information identification module control method of the above-mentioned first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0026] In a fourth aspect, 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 UWB-based information identification module control method of the first aspect or any corresponding embodiment thereof.

[0027] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions for causing a computer to execute the UWB-based information identification module control method of the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] 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.

[0029] Figure 1It is a flow chart of a UWB-based information identification module control method provided by an embodiment of the present invention.

[0030] Figure 2 The diagram is a logical diagram showing how a UWB module acquires location information according to an exemplary embodiment.

[0031] Figure 3 The figure is a schematic diagram of an application scenario of a UWB-based information recognition module control method according to an exemplary embodiment.

[0032] Figure 4 It is a structural schematic diagram of a UWB-based information identification module control device provided in an embodiment of the present application.

[0033] Figure 5 It is a structural schematic diagram of a computer device provided by an optional embodiment of the present invention. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of this application.

[0035] It should be understood that the "indication" mentioned in the embodiments of the present application can be a direct indication, an indirect indication, or an indication of an association relationship. For example, A indicates B, which can mean that A directly indicates B, for example, B can be obtained through A; it can also mean that A indirectly indicates B, for example, A indicates C, and B can be obtained through C; it can also mean that there is an association relationship between A and B.

[0036] In the description of the embodiments of the present application, the term "corresponding" may indicate a direct or indirect correspondence between two items, or an association relationship between the two items, or a relationship between indication and being indicated, configuration and being configured, and the like.

[0037] In an embodiment of the present application, "predefinition" can be achieved by pre-saving corresponding codes, tables or other methods that can be used to indicate relevant information in a device (for example, including a terminal device and a network device). The present application does not limit its specific implementation method.

[0038] The location detection module of the smart door lock device will detect people coming and going, and the information recognition module will always be in an activated state, which consumes more power. However, these people are not all people who want to pass through. They may be cleaning staff, passers-by, neighbors of residents, etc. Such frequent awakening of the information recognition module will cause the smart door lock device to consume a lot of power, and it is impossible to wake up the information recognition module in advance for users who want to pass through, which reduces the user experience.

[0039] Therefore, an embodiment of the present invention provides a UWB-based information recognition module control method, which detects the user's moving direction and moving speed through UWB technology, and obtains a prediction result based on the moving direction and moving speed, and determines whether it is necessary to wake up the information recognition module of the smart door lock to identify the user through the prediction result, thereby reducing the power consumption of the smart door lock device and improving the user experience. The UWB-based information recognition module control method provided in this embodiment is applied to a smart door lock device, which includes a UWB module and an information recognition module. The process of the method is as follows: Figure 1 As shown, the following steps are included.

[0040] S101. Acquire a motion state of a target user detected by the UWB module within a preset detection range; the motion state includes location information, moving direction, and moving speed of the target user.

[0041] Specifically, in this step, the preset detection range is the area near the door lock, specifically the area that the user needs to pass through when passing through the smart door lock, including the area in front of or behind the door of the access control device equipped with the smart door lock device, generally the area in front of the door. The UWB module uses UWB (Ultra Wideband) wireless communication technology to detect the user's motion state within the preset detection range, that is, the user's moving direction and moving speed. The preset detection range may include multiple gears, each gear is an empirical value determined by debugging, not a relatively wide distance interval, and the accuracy requirement is high. Since the person who wants to pass needs to move from a distance to the front of the smart door lock device, when the person is a certain distance away from the smart door lock device, the information recognition module will be awakened to identify the identity information of the person, therefore, the preset detection range is a range at a certain distance from the smart access control device. The smart door lock device includes a UWB module, and the person is moving to the front of the smart door lock device, that is, close to the UWB module, therefore, the preset detection range is also a range at a certain distance from the UWB module.

[0042] Optionally, the above-mentioned preset detection range may take the range between the first distance from the UWB module and the second distance from the UWB module as the preset detection range, so that the smart door lock device can obtain the movement status of the person detected by the UWB module within the range between the first distance from the UWB module and the second distance from the UWB module.

[0043] Optionally, when the UWB module detects that the target user has entered the preset detection range, the location information of the target user is collected at a preset time interval to obtain a curve of the change of the location information over time; based on the curve of the change of the location information over time, the moving direction and moving speed of the target user are obtained. The preset time interval can be set according to the actual situation, and should not be too long or too short. The principle is that the multiple location coordinates obtained by the smart door lock device can constitute a change curve. It can be 5ms, 10ms, etc., and is not specifically limited here.

[0044] Optionally, in order to obtain the above-mentioned position information change curve over time, the smart door lock device can first determine the positions of multiple points within the preset detection range, and then determine the change curve based on the principle of multiple points determining a curve. Then, when a person enters the preset detection range, the UWB card can sample the position of the person multiple times, so that the smart door lock device can obtain the position coordinates of the person detected by multiple UWB modules, thereby obtaining the position information change curve over time.

[0045] Optionally, the UWB module includes a first antenna and a second antenna, such as Figure 2 As shown, the first antenna and the second antenna are symmetrically distributed on the UWB module, and the target user carries a UWB tag. The UWB signal emitted by the UWB tag is received simultaneously by the first antenna and the second antenna, and the phase difference and time difference of the UWB signal reaching the first antenna and the second antenna are obtained; based on the phase difference and the time difference, the location information of the target user is obtained. The dual-antenna UWB module can obtain a phase difference of 5 degrees, and the plane position of the target user's UWB tag can be determined with the aid of the flight time parameter.

[0046] Optionally, when the UWB module fails to detect the target user within the preset detection range, or detects that the target user leaves the preset detection range, the UWB module stops detecting the motion state of the target user within the preset detection range.

[0047] It should be noted that this is merely an example of how to obtain the user's motion status, and it does not limit the scope of protection of the present application. In other embodiments of the present application, the user's motion status can also be obtained by other means. For example, positioning technologies such as radar positioning, Bluetooth positioning, and WiFi positioning can all be used to obtain the above-mentioned motion status, which will not be repeated here.

[0048] S102. Obtain a prediction result based on the location information, moving direction and moving speed; the prediction result is used to indicate the target user's interaction behavior with the smart door lock device in a future time period.

[0049] Optionally, in step S102, the prediction result can be predicted by a pre-trained neural network model, and the corresponding prediction result can be directly generated based on the moving direction and the moving speed. Alternatively, the predicted motion trajectory can be generated first, and then matched with the pre-stored motion trajectory. Since the predicted motion trajectory is the motion trajectory of a person with access authority within a preset detection range, when the predicted motion trajectory matches the pre-stored motion trajectory successfully, it indicates that the person is largely a person who wants to pass. When the match is unsuccessful, it indicates that the person is largely a cleaning staff, a passerby, etc. who do not want to pass. The pre-stored motion trajectory is the pre-stored motion trajectory of a person with access authority. The motion trajectory of a person with access authority corresponds to the intention of entering the house through the opening seam of the door leaf, and the information recognition module needs to be awakened for personnel identity recognition. The motion trajectory of a person without access authority does not correspond to the intention of entering the house through the opening seam of the door leaf, but may be to press the doorbell, pass by, or have other intentions. At this time, there is no need to wake up the information recognition module for personnel identity recognition.

[0050] Optionally, the neural network model can directly determine whether the user is a target user who needs to pass based on the user's motion state. Specifically, the motion state of a large number of users who need to pass and the motion state of users who do not need to pass in a variety of situations can be obtained as a training data set, and the motion state of users who need to pass is marked as a motion state that needs to pass, and the trajectory information of users who do not need to pass is marked as a motion state that does not need to pass, and the neural network can be supervised by using the marked training data set.

[0051] Optionally, the above neural network model can predict the user's motion trajectory based on the user's motion state, and match it with the pre-stored trajectory to determine whether the user is a user who needs to pass. Specifically, a large number of user motion states and corresponding motion trajectories can be obtained as training sets and verification sets. After the training is completed, the user's predicted motion trajectory can be obtained according to the user's current motion state. Then the predicted motion trajectory is matched with the pre-stored motion trajectory. Since the predicted motion trajectory is the motion trajectory of a person with access authority within a preset detection range, when the predicted motion trajectory matches the pre-stored motion trajectory successfully, it indicates that the person is largely a person who wants to pass. When the match is unsuccessful, it indicates that the person is largely a cleaning staff, passerby, and other people who do not want to pass.

[0052] Optionally, in step S102, the predicted motion trajectory is matched with the pre-stored motion trajectory. Specifically, the similarity between the predicted motion trajectory and the pre-stored motion trajectory is calculated, and it is determined whether the similarity reaches a preset threshold. If the preset threshold is reached, the pre-stored motion trajectory with the highest similarity to the predicted motion trajectory is obtained, thereby obtaining the pre-stored result corresponding to the predicted motion trajectory with the highest similarity as the prediction result.

[0053] S103, determining whether to wake up the information identification module according to the prediction result; the information identification module is used to identify the identity information of the target user.

[0054] Specifically, in this step, when the prediction result shows that the user is a person who wants to pass, the information recognition module is awakened to perform user identity recognition; when the prediction result shows that the person is not a person who wants to pass, the information recognition module is not awakened. The information recognition module is used to identify the user's identity information, which can be fingerprint recognition, infrared recognition, face recognition, etc. Wake-up is the action of the smart door lock device switching from a low-power sleep state to the operation of the information recognition module (or main processor). Generally, smart door lock devices are in a sleep state most of the time to maintain low-power operation. When an event is triggered, the MCU (Micro Controller Unit) in the smart door lock device can wake up the information recognition module (or main processor), which will increase the power consumption of the smart access control device.

[0055] Based on the UWB-based information identification module control method described in the above embodiment, a specific example is used to illustrate it below.

[0056] The scenario of the UWB-based information recognition module control method in this example is as follows Figure 3 As shown in the figure, after a person comes out of the elevator, there may be several situations when passing by Household A: directly out of the unit door, going to the doorbell of Household A, and going to the door gap of Household A, which correspond to different intentions: passing by the door intention, ringing the doorbell intention, and entering the house intention. After the smart door lock on the main door of Household A senses the elevator door opening, it will obtain the user's moving direction and moving speed when exiting the elevator, and predict the user's intention. When the user's intention is to pass by the door, the moving direction is toward the unit door, and the change in moving speed should be uniform or accelerated; when the user's intention is to ring the doorbell or enter the house, the user's moving direction is to go to the doorbell of Household A or the door gap of Household A, the moving direction is roughly the same but there are some deviations, and the change in moving speed when going to the doorbell of Household A should gradually slow down, and the moving speed when going to the door gap of Household A should be uniform or accelerated, so as to distinguish whether the user wants to ring the doorbell or enter the house. The neural network model in the smart door lock device is trained based on a large number of moving directions, moving speeds and corresponding intentions. After the training is completed, the user's specific intentions can be judged through the user's different moving directions and speeds, and it can be determined whether the information recognition module needs to be awakened to identify the user's identity information.

[0057] In summary, the UWB-based information identification module control method of the embodiment of the present invention is applied to a smart door lock device, and the smart door lock device includes a UWB module and an information identification module. The smart door lock device detects the motion state of the target user through the UWB module to obtain the moving direction and moving speed of the target user. The UWB module adopts UWB wireless communication technology. UWB technology belongs to the communication technology within the medium and short distance range, which can achieve centimeter-level positioning accuracy, which is very suitable for the indoor environment where the smart door lock device is located, and has low transmission power and strong anti-interference ability. It can still maintain stable working performance in a complex electromagnetic environment. Subsequently, a prediction is made based on the moving direction and moving speed to obtain a prediction result, which is used to determine whether it is necessary to wake up the information identification module of the smart door lock device. The prediction can be directly obtained according to the moving direction and moving speed through a pre-trained neural network model. The target user's motion trajectory can also be predicted based on the moving direction and moving speed, and then matched with the pre-stored motion trajectory. Since the predicted motion trajectory is the motion trajectory of a person with access rights within the preset detection range, when the predicted motion trajectory matches the pre-stored motion trajectory successfully, it indicates that the person is likely to be a person who wants to pass through, and the information recognition module needs to be awakened. The information recognition module can be awakened in advance for the person who wants to pass through, thereby improving the user experience. When the match is unsuccessful, it indicates that the person is likely to be a cleaning staff, a passerby, or other person who does not want to pass through. At this time, there is no need to wake up the information recognition module, which can reduce the number of times the information recognition module is awakened, thereby reducing the power consumption of the smart door lock device.

[0058] On the basis of the above-mentioned embodiments, a UWB-based information identification module control device is also provided in the embodiments of the present application, and the device is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. 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 conceived.

[0059] The present application embodiment provides a UWB-based information recognition module control device, Figure 4 : is a structural schematic diagram of a UWB-based information identification module control device provided in an embodiment of the present application. The device is applied to a smart door lock device. The smart door lock device includes a UWB module and an information identification module. The device includes:

[0060] The acquisition module 401 is used to acquire the motion state of the target user detected by the UWB module within a preset detection range; the motion state includes the location information, moving direction and moving speed of the target user.

[0061] The prediction module 402 is used to obtain a prediction result based on the location information, the moving direction and the moving speed; the prediction result is used to indicate the interaction behavior of the target user with the smart door lock device in a future time period.

[0062] The awakening module 403 is used to determine whether to awaken the information identification module according to the prediction result; the information identification module is used to identify the identity information of the target user.

[0063] In an optional implementation, the prediction module 402 is specifically used to: input the moving direction and the moving speed into a pre-built prediction model to obtain the prediction result.

[0064] In an optional embodiment, the prediction module 402 is specifically used to: input the moving direction and the moving speed into a pre-built prediction model to obtain the predicted motion trajectory of the target user; match the predicted motion trajectory with the pre-stored motion trajectory to obtain a matching result; the pre-stored motion trajectory is a pre-stored motion trajectory of a person with access authority within the preset detection range; and obtain the prediction result based on the matching result.

[0065] In an optional embodiment, the acquisition module 401 is specifically used for: when the UWB module detects that the target user enters the preset detection range, collecting the location information of the target user at a preset time interval to obtain a curve of the change of the location information over time; based on the curve of the change of the location information over time, obtaining the moving direction and moving speed of the target user.

[0066] In an optional implementation, the acquisition module 401 is further used to: when the UWB module fails to detect the target user within the preset detection range, or detects that the target user leaves the preset detection range, stop detecting the motion state of the target user within the preset detection range.

[0067] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0068] The UWB-based information identification module control device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0069] The embodiment of the present invention also provides a computer device having the above Figure 4The UWB-based information identification module control device is shown.

[0070] See also Figure 5 , Figure 5 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 5 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 instructions executed in the computer device, including instructions stored in or on the memory to display graphic information in a graphical user interface on an external input / output device (such as a display device coupled to an 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). Figure 5 A processor 10 is taken as an example.

[0071] 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.

[0072] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0073] 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 according to the use of the computer device, 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.

[0074] 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.

[0075] The computer device also includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Figure 5 The example of connecting through bus is taken in the following.

[0076] 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.

[0077] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0078] 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 UWB-based information recognition module control method, characterized in that: Applied to a smart door lock device, the smart door lock device includes a UWB module and an information recognition module, and the method includes: Acquire the motion state of the target user detected by the UWB module within a preset detection range; the motion state includes the location information, moving direction and moving speed of the target user; Based on the location information, the moving direction and the moving speed, a prediction result is obtained; the prediction result is used to indicate the interaction behavior of the target user with the smart door lock device in a future time period; Determine whether to wake up the information identification module according to the prediction result; the information identification module is used to identify the identity information of the target user.

2. The method according to claim 1, characterized in that The obtaining a prediction result based on the position information, the moving direction and the moving speed includes: The position information, the moving direction and the moving speed are input into a pre-built prediction model to obtain the prediction result.

3. The method according to claim 1, characterized in that The obtaining a prediction result based on the position information, the moving direction and the moving speed includes: Inputting the location information, the moving direction and the moving speed into a pre-built prediction model to obtain a predicted movement trajectory of the target user; The predicted motion trajectory is matched with the pre-stored motion trajectory to obtain a matching result; the pre-stored motion trajectory is a pre-stored motion trajectory of a person with access authority within the preset detection range; The prediction result is obtained according to the matching result.

4. The method according to any one of claims 2 to 3, characterized in that: The prediction model is obtained by training a preset neural network model.

5. The method according to claim 1, characterized in that The obtaining of the motion state of the target user detected by the UWB module within a preset detection range includes: When the UWB module detects that the target user enters the preset detection range, the location information of the target user is collected at preset time intervals to obtain a curve of the change of the location information over time; The moving direction and the moving speed of the target user are obtained based on a curve of the position information changing over time.

6. The method according to claim 5, characterized in that The UWB module includes a first antenna and a second antenna, the first antenna and the second antenna are symmetrically distributed on the UWB module, and the target user carries a UWB tag; the method further includes: Receiving the UWB signal sent by the UWB tag simultaneously through the first antenna and the second antenna, and obtaining a phase difference and a time difference between the UWB signal reaching the first antenna and the second antenna; Based on the phase difference and the time difference, the location information of the target user is obtained.

7. The method according to claim 1, characterized in that The method further comprises: When the UWB module fails to detect the target user within the preset detection range, or detects that the target user leaves the preset detection range, it stops detecting the motion state of the target user within the preset detection range.

8. A UWB-based information recognition module control device, characterized in that: Applied to a smart door lock device, the smart door lock device includes a UWB module and an information recognition module, and the device includes: An acquisition module, used to acquire the motion state of the target user detected by the UWB module within a preset detection range; the motion state includes the location information, moving direction and moving speed of the target user; A prediction module, used to obtain a prediction result based on the location information, the moving direction and the moving speed; the prediction result is used to indicate the interaction behavior of the target user with the smart door lock device in a future time period; A wake-up module is used to determine whether to wake up the information identification module according to the prediction result; the information identification module is used to identify the identity information of the target user.

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 UWB-based information identification module control 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 UWB-based information identification module control method according to any one of claims 1 to 7.

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