TOF-based non-inductive indoor door opening system and method

Abstract

The invention relates to the technical field of intelligent door locks, in particular to a TOF-based non-inductive indoor door opening system and method.The TOF-based non-inductive indoor door opening system comprises a TOF monitoring unit used for collecting distance data of all points in a detection area in real time; the signal processing unit is used for carrying out filtering processing on the distance data so as to improve the data precision and the anti-interference capability; the algorithm unit is used for constructing three-dimensional depth information based on the filtered distance data, identifying the type of the target object and analyzing the movement direction and speed of the target object to judge whether the target object has a door opening intention or not; and the door control execution unit is used for executing a door opening action when the algorithm unit judges that the door opening intention is the door opening intention. The high-precision distance data is collected in real time based on the TOF monitoring unit, filtering and noise reduction are carried out through the signal processing unit, environmental interference can be effectively resisted, and therefore the stability and reliability of detection are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of smart door lock technology, specifically to a time-of-flight (TOF)-based contactless indoor door opening system and method. Background Technology

[0002] Traditional indoor door opening methods, such as mechanical handles, buttons, or infrared sensors, provide users with basic access convenience. Among these, non-contact sensing solutions, such as infrared and microwave sensors, have achieved a door opening experience without physical contact to a certain extent, becoming a common auxiliary opening method in the smart home field.

[0003] However, the aforementioned sensing solutions in related technologies generally suffer from a core flaw: they cannot accurately distinguish between a person's true intention to open the door and other behavioral intentions, resulting in inaccurate door opening control and a high false trigger rate. Therefore, how to achieve a contactless door opening system that can accurately identify human bodies and intelligently determine door opening intentions has become an urgent problem to be solved. Summary of the Invention

[0004] In view of this, the present invention provides a TOF-based contactless indoor door opening system and method to solve the problem of how to realize a contactless door opening system that can accurately identify human body and intelligently determine the intention to open the door.

[0005] This disclosure provides a time-of-flight (TOF)-based contactless indoor door opening system, comprising: a TOF monitoring unit, a signal processing unit, an algorithm unit, and a door control execution unit, wherein: The TOF monitoring unit is used to collect distance data of each point in the detection area in real time. The signal processing unit is used to filter the distance data to improve data accuracy and anti-interference capability; The algorithm unit is used to construct three-dimensional depth information based on the filtered distance data, identify the type of the target object, and analyze the direction and speed of the target object's movement to determine whether it has the intention to open the door. The gate control execution unit is used to execute the door opening action when the algorithm unit determines that the intention to open the door is correct.

[0006] This disclosure also provides a time-of-flight (TOF)-based contactless interior door opening method, applied to the aforementioned TOF-based contactless interior door opening system. The method includes: The distance data of each point within the detection area is collected in real time by the TOF monitoring unit; The distance data is filtered by the signal processing unit to improve data accuracy and anti-interference capability. The algorithm unit constructs three-dimensional depth information based on the processed distance data, identifies the type of target object, and analyzes its direction of movement and speed to determine whether it has the intention to open the door. When the intention to open the door is determined, the door opening action is executed through the door control execution unit.

[0007] This disclosure also provides an electronic device, including: a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the above-described TOF-based contactless indoor door opening method.

[0008] This disclosure also provides a computer-readable storage medium storing computer instructions for enabling a computer to implement the above-described TOF-based contactless indoor door opening method.

[0009] This disclosure also provides a computer program product, including computer instructions for causing a computer to execute the above-described TOF-based contactless indoor door opening method.

[0010] The TOF-based contactless indoor door opening system and method disclosed in the above embodiments of this invention can effectively resist environmental interference by using a TOF monitoring unit to collect high-precision distance data in real time and filtering and reducing noise through a signal processing unit, thereby significantly improving the stability and reliability of detection.

[0011] Furthermore, by constructing three-dimensional depth information and analyzing the direction and speed of movement through the algorithm unit, intelligent recognition and judgment of the human's intention to open the door are realized, thereby significantly reducing the false trigger rate while ensuring high accuracy. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the specific embodiments or related technologies of this disclosure, the accompanying drawings used in the description of the specific embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 An exemplary schematic diagram of the architecture of a TOF-based contactless indoor door opening system according to an embodiment of the present disclosure is shown; Figure 2 A schematic diagram of the integrated installation location of a TOF-based contactless indoor door opening system according to an embodiment of the present disclosure is shown. Figure 3 A flowchart illustrating a time-of-flight (TOF)-based contactless indoor door opening method provided in an embodiment of this disclosure is shown. Figure 4 A schematic diagram of the structure of an electronic device according to an embodiment of the present disclosure is shown. Detailed Implementation

[0014] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0015] With the development of smart homes and building automation, people have placed higher demands on the convenience, security, and seamless experience of indoor entry and exit. To achieve automatic door opening without physical contact, related technologies often employ non-contact sensing devices such as infrared sensors, microwave sensors, or cameras. These devices detect the presence or movement of a human body, thereby triggering the door lock to open.

[0016] In practical applications, the accuracy and reliability of automatic door opening highly depend on the precise identification of people and their intentions. Currently, the sensing and judgment methods commonly used in related technologies are mainly based on signal threshold triggering or simple motion detection. Although these methods are relatively simple in terms of implementation cost and control logic, they often have the following problems when facing real-world, complex indoor living scenarios: 1. Most existing solutions can only detect the presence of objects or movement within a specific range, but cannot effectively distinguish whether the target is a person, a pet, or another moving object. Furthermore, they cannot analyze the target's movement trajectory, direction, and speed to determine its true intentions (such as leaving the house, passing by, or simply lingering in front of the door). This makes the system highly susceptible to false triggers due to non-leaking behaviors such as pet activity or people passing by, resulting in a poor user experience and potential security risks.

[0017] 2. Common infrared and ultrasonic sensors are easily affected by ambient temperature, light, complex reflective surfaces, or other electromagnetic signals, resulting in unstable detection signals, low accuracy, and insufficient reliability in complex home environments. While visual camera solutions can acquire richer information, they involve the risk of user privacy leaks and require high image processing power, leading to high system costs and power consumption, making them difficult to popularize in ordinary door lock products.

[0018] 3. The functional design of related technologies lacks consideration for expanding contactless interaction capabilities. The functionality of related solutions is limited to "automatic door opening," making it difficult to support more advanced and flexible contactless interaction commands such as unlocking with specific gestures. Their system architecture and sensor selection typically do not reserve conditions for implementing such functions, limiting the scalability of product functions and further improvement of the user interaction experience.

[0019] To address the aforementioned issues, various embodiments of this disclosure provide a Time-of-Flight (TOF)-based contactless indoor door opening system. The system includes a TOF monitoring unit, a signal processing unit, an algorithm unit, and a door control execution unit. Specifically: the TOF monitoring unit is used to collect distance data from various points within the detection area in real time; the signal processing unit is used to filter the distance data to improve data accuracy and anti-interference capability; the algorithm unit is used to construct three-dimensional depth information based on the filtered distance data, identify the type of the target object, and analyze the target object's movement direction and speed to determine whether it has an intention to open the door; the door control execution unit is used to execute the door opening action when the algorithm unit determines that there is an intention to open the door.

[0020] Please refer to Figure 1 , Figure 1 An exemplary schematic diagram of the architecture of a Time-of-Flight (TOF)-based contactless indoor door opening system according to an embodiment of this disclosure is shown. Figure 1 As shown, the TOF-based contactless indoor door opening system 100 includes: a TOF monitoring unit 101, a signal processing unit 102, an algorithm unit 103, and a door control execution unit 104, wherein: The TOF monitoring unit 101 is used to collect distance data of each point in the detection area in real time.

[0021] In this embodiment, the TOF monitoring unit 101 can be a depth sensor based on the Time of Flight (TOF) principle.

[0022] The core function of the TOF monitoring unit 101 is to actively transmit detection signals and receive echo signals reflected from objects within the detection area. By measuring the round-trip flight time of the signal, the distance between the sensor and each point on the object surface can be obtained, thereby outputting a set of distance data that characterizes the three-dimensional spatial information of the area.

[0023] For example, the TOF monitoring unit 101 can be a type of TOF sensor capable of outputting depth maps or point cloud data.

[0024] The signal processing unit 102 is used to filter the distance data to improve data accuracy and anti-interference capability.

[0025] In this embodiment, the signal processing unit 102 can be a computing module that preprocesses and optimizes the raw sensing data.

[0026] Specifically, the signal processing unit 102 can apply a specific digital signal processing algorithm to the raw distance dataset collected by the TOF monitoring unit 101, which may contain noise and interference, in order to suppress random errors, smooth abnormal fluctuations and enhance effective signal components, thereby outputting more stable and reliable distance data.

[0027] For example, this unit can be functionally embodied as an embedded signal processor or preprocessing firmware with real-time filtering capabilities.

[0028] Algorithm unit 103 is used to construct three-dimensional depth information based on the filtered distance data, identify the type of target object, and analyze the direction and speed of the target object's movement to determine whether it has the intention to open the door.

[0029] In this embodiment, the algorithm unit 103 can be an intelligent analysis module that parses and understands the behavior of distance data after filtering.

[0030] Specifically, the algorithm unit 103 can reconstruct discrete distance data into coherent three-dimensional depth information (such as a three-dimensional point cloud) and identify the category attributes of the target (such as a human body or an object) based on this three-dimensional depth information.

[0031] Furthermore, by correlating the changes in three-dimensional information between consecutive time frames, the motion vector field of the target is calculated, and its dynamic characteristics such as motion direction and velocity are obtained from it.

[0032] Ultimately, by matching the target's type and dynamic characteristics with the preset intent judgment logic, the intention to open the door is intelligently determined.

[0033] For example, the algorithm unit 103 can be functionally embodied as an algorithm processor that integrates 3D reconstruction, target classification and motion tracking functions.

[0034] The gate control execution unit 104 is used to execute the door opening action when the algorithm unit 103 determines that there is an intention to open the door.

[0035] In this embodiment, the door control execution unit 104 can be an execution interface and control module that drives the door lock mechanism to move according to intelligent decision signals.

[0036] Specifically, the door control execution unit 104 can receive a logical instruction representing the intention to open the door from the algorithm unit 103, and convert the electronic control instruction into a drive signal that can drive the door lock mechanical structure (such as the bolt, motor or electromagnetic device) to produce an unlocking or opening action.

[0037] For example, the gate control execution unit 104 can be functionally embodied as an electronically controlled drive circuit, motor controller, or relay module that connects the control system and the lock mechanism.

[0038] The TOF-based contactless indoor door opening system and method disclosed in the above embodiments effectively resist environmental interference by using a TOF monitoring unit to collect high-precision distance data in real time and filtering and reducing noise through a signal processing unit, thereby significantly improving the stability and reliability of detection. Furthermore, by constructing three-dimensional depth information and analyzing movement direction and speed through an algorithm unit, intelligent recognition and judgment of human intention to open the door are achieved, thus significantly reducing the false trigger rate while ensuring high accuracy.

[0039] In one possible implementation of the above embodiments, the system is integrated at the indoor handle position of the door, and the TOF monitoring unit 101 is horizontally oriented towards the detection area, including multiple detection points distributed in an array.

[0040] In this embodiment, the system can be designed as an integrated module, and its physical structure is adapted to be integrated and installed in the area near the handle on the inside of the door.

[0041] The location was chosen by taking into account ease of installation, simplicity of wiring, and seamless user experience.

[0042] Setting the TOF monitoring unit 101 to a horizontal orientation allows its optical emission and reception axes to be basically parallel to the ground, thus making its main detection area a fan-shaped three-dimensional space extending forward, which can effectively cover the typical activity areas of users standing in front of the door, walking towards the doorway, and making gestures.

[0043] For example, please refer to Figure 2 , Figure 2 A schematic diagram of the integrated installation location of a Time-of-Flight (TOF)-based contactless indoor door opening system according to an embodiment of this disclosure is shown. Figure 2 As shown, the system can be integrated into the indoor handle of the door, and the TOF monitoring unit 101 is set to a horizontal orientation to detect objects within the coverage area.

[0044] Understandably, the TOF monitoring unit 101 is positioned horizontally to optimize the sensitivity of sensing the direction of movement indicating an intention to open the door. The system is positioned on the interior door handle for easy concealment and to prevent accidental obstruction.

[0045] Furthermore, the TOF monitoring unit 101 may contain multiple detection points arranged in an array (e.g., forming an M×N pixel matrix).

[0046] Each detection point independently performs time-of-flight ranging, thereby obtaining the distance matrix corresponding to each pixel within the detection area in one go.

[0047] Understandably, this arrayed multi-point measurement method, compared to a single-point ranging sensor, can capture the contour shape information and surface depth changes of the target object in three-dimensional space, providing a data foundation for the subsequent algorithm unit 103 to perform accurate target shape recognition and motion analysis.

[0048] In addition, the system can be embedded in the door panel or handle base, with only the sensor's detection window exposed, thus maintaining the door's simple appearance while realizing intelligent functions.

[0049] Furthermore, the TOF monitoring unit 101 is based on the principle of actively transmitting modulated light and measuring TOF, and its performance is far less affected by ambient light conditions than that of traditional vision sensors.

[0050] Specifically, the TOF monitoring unit 101 can have high resistance to ambient light interference. In dark environments, its own active light source is sufficient for accurate distance measurement. In strong light environments, through optical filtering, modulation and demodulation, and noise reduction by the algorithm of the signal processing unit 102, it can effectively suppress interference from background natural light or artificial light sources.

[0051] The Time-of-Flight (TOF) based non-intrusive indoor door opening system and method disclosed above utilizes the horizontal orientation of the TOF detection units to create a forward-extending three-dimensional space within the detection area. This effectively covers the user's path towards the door, enhancing the ability to capture approach behavior and providing an optimized spatial perception basis for accurately determining the intention to open the door. The array of detection points can acquire a distance matrix simultaneously, capturing the three-dimensional contour and depth variation information of the target object, thus upgrading from presence detection to intention recognition.

[0052] In one possible implementation of the above embodiments, the signal processing unit 102 is used to process distance data using a Kalman filtering algorithm.

[0053] In this embodiment, the signal processing unit 102 uses a Kalman filter algorithm to process the raw distance data collected by the TOF monitoring unit 101 in real time.

[0054] Among them, the Kalman filter algorithm can be a highly efficient recursive digital filtering algorithm. Its core lies in the continuous iteration of the two steps of "prediction-update" to make the optimal estimate of the state of the dynamic system.

[0055] Specifically, the Kalman filter algorithm treats the distance value of each detection point as a system state that changes over time. By establishing a model that includes the system state equation and the observation equation, and combining the current observation value (i.e., the distance read in real time by the TOF sensor) with the optimal estimate value from the previous moment, a more accurate distance estimate value for the current moment is calculated.

[0056] Here, the processing performed by the signal processing unit 102 can effectively suppress random noise, smooth abnormal fluctuations in measurement data, and significantly reduce measurement errors caused by environmental factors.

[0057] The TOF-based non-sensory indoor door opening system and method disclosed above significantly reduces the impact of environmental random noise and transient interference on the data by performing optimal estimation of the measured values. The output distance data sequence is more stable and continuous, providing high-quality input for subsequent contour reconstruction and motion analysis, and improving the consistency and smoothness of the data.

[0058] In one possible implementation of the above embodiments, the algorithm unit 103 is specifically used to: construct a 3D distance-depth image based on the distance data processed by the signal processing unit 102 to identify the shape of the target object, and analyze the relationship between the distance data and time to perform motion vector analysis.

[0059] In this embodiment, the core processing flow of the algorithm unit 103 may include two key technical stages: the three-dimensional spatial reconstruction stage and the temporal motion analysis stage.

[0060] Specifically, in the three-dimensional space reconstruction stage, the algorithm unit 103 can reconstruct the set of discrete distance data points output by the signal processing unit 102, which has been filtered out of noise, into a continuous 3D distance and depth image with clear geometric meaning through methods such as spatial interpolation, surface fitting, or voxelization.

[0061] Here, a 3D distance-depth image can essentially be a spatial representation with a depth dimension, which can clearly reflect the surface undulations, contour boundaries and three-dimensional shape of the target object within the detection area.

[0062] Based on this three-dimensional representation, the algorithm unit 103 can further extract features (such as overall size, aspect ratio, volume, surface curvature, etc.) and use a pre-trained lightweight classification model or rule base to identify the type of target object, such as accurately distinguishing between human body, pet, and ordinary object.

[0063] During the temporal motion analysis phase, the algorithm unit 103 can continuously receive and cache distance data or 3D images processed from multiple frames.

[0064] Specifically, by comparing the changes in depth values ​​of the same spatial location or feature point under consecutive timestamps, the displacement in three-dimensional space is calculated, thereby generating a motion vector field describing the entire target or local area.

[0065] Among them, motion vector analysis not only includes calculating the overall motion velocity and direction of the target (such as the normal direction relative to the gate plane), but also further analyzes the smoothness of its motion trajectory, acceleration changes and other dynamic characteristics.

[0066] For example, in a specific implementation, the algorithm unit 103 can first segment the foreground moving target from the 3D image through background subtraction, and then perform inter-frame registration on the three-dimensional point cloud of the target to directly calculate its rigid body motion transformation matrix, thereby analyzing the precise translation speed and direction.

[0067] The TOF-based contactless indoor door opening system and method disclosed in the above embodiments effectively distinguishes between humans and non-human objects through shape analysis based on 3D distance and depth images, fundamentally avoiding false triggers caused by pets or moving objects, and improving the security and reliability of door opening recognition. By analyzing the precise translation speed and direction, the true intention of the target to open the door can be accurately identified, further improving the intelligence level of door opening recognition.

[0068] In one possible implementation of the above embodiments, the conditions for the algorithm unit 103 to determine an intention to open the door include: the target object continuously approaches the door and its movement speed reaches a preset threshold; and, Algorithm unit 103 is also used to eliminate interference intent through the following steps: when the angle between the direction of movement of the target object and the normal of the door exceeds a preset angle threshold, it is determined to be a passing intent; and / or, when the movement speed fluctuation of the target object exceeds a preset ratio threshold, it is determined to be a loitering intent.

[0069] In this embodiment, the algorithm unit can realize an intent judgment based on multi-condition composite logic and interference behavior feature recognition.

[0070] Here, the recognition of the intention to open the door does not rely on a single condition, but requires at least two conditions to be met simultaneously: the target's movement direction must be determined to be a continuous approach to the door, and the target's movement speed must reach a preset threshold. This preset threshold can be set according to the reasonable speed range of a typical adult walking to the door, in order to exclude approaching behaviors that are too slow to an unreasonable degree.

[0071] One method to determine the direction of the target's movement is to identify that it is continuously approaching the door is that the algorithm detects the target's centroid or main part moving in three-dimensional space in a direction pointing towards the door during multiple frames of data.

[0072] Furthermore, to reduce misjudgments, the algorithm unit also integrates logic for identifying and eliminating two typical interference intentions.

[0073] Specifically, for the intention to pass by, the algorithm unit 103 calculates the angle between the overall movement direction of the target and the normal of the door plane (i.e., the direction perpendicular to the door and outward). If the angle is greater than a preset angle threshold (e.g., a value in the range of 45° to 60°), it can be determined that the main movement trajectory of the target is to pass by the door almost parallel to the door rather than to approach it perpendicularly, thus determining it as "passing by".

[0074] Regarding the intention to loiter, the algorithm unit 103 monitors the fluctuation of the target's speed within a set time window, calculates the ratio of its speed standard deviation to the average value or a similar volatility index. If the volatility exceeds a preset ratio threshold, it indicates that the target's movement is hesitant or intermittent, and it does not have a clear intention to approach, and is therefore judged as "loitering".

[0075] It is understandable that the aforementioned preset thresholds and angle parameters can be calibrated and configured according to the actual installation environment (such as corridor width) and user group habits to make the system adaptable to different scenarios.

[0076] Furthermore, the algorithm unit 103 is also used to predict the arrival time by combining the real-time movement speed of the target with the continuous tracking of its current position, instead of immediately initiating the door opening action after determining the intention to open the door.

[0077] Specifically, the algorithm unit 103 calculates and sends an opening command to the door control execution unit 104 based on the predicted time of the user's arrival at the door.

[0078] Preferably, the advance time can be within the range of 0.8 to 1.2 seconds. This time range is a carefully designed balance point: it ensures that the motor or lock drive mechanism has enough time to complete the unlocking and opening actions, while also allowing the door to be open enough for passage when the user arrives at a natural walking pace, achieving a seamless "door opens as soon as person arrives" experience. This fundamentally frees the user's hands, eliminating the need to stop, wait, or perform any additional actions, providing a smooth and natural, imperceptible passage experience.

[0079] The Time-of-Flight (TOF) based non-intrusive indoor door opening system and method of the above embodiments of this disclosure only consider objects that simultaneously meet the objectives of "continuous approach" and "speed reaching the standard," directly filtering out unintentionally approaching or slowly moving objects, which can significantly improve the accuracy of door opening intention judgment. By quantitatively identifying the two most common interference behavior patterns, "passing by" and "lingering," the system can actively exclude them from the triggering conditions, thereby reducing the false trigger rate to an extremely low level in complex and dynamic home environments. Compared with traditional camera solutions, the embodiments of this disclosure do not have high-computing-power algorithms, resulting in relatively lower costs.

[0080] In one possible implementation of the above embodiments, the detection resolution of the TOF monitoring unit 101 is not less than 72*72, and it is used to recognize a preset specific gesture.

[0081] In this embodiment, by increasing the detection resolution of the TOF monitoring unit 101 to no less than 72*72, the system can obtain the ability to perform high spatial resolution sampling of the target surface within the detection area.

[0082] Higher resolution means that more independent ranging points are distributed within the same field of view, thus enabling the capture of finer target geometric details and contour variations.

[0083] When a target (such as a user's hand) enters the detection area and makes a gesture, the high-resolution TOF monitoring unit 101 can generate a high-precision depth point cloud or depth image containing rich details, clearly outlining the finger posture, the outline of the palm, the movement trajectory of the hand, and the unique three-dimensional spatial structure presented by complex gestures.

[0084] Algorithm unit 103 can utilize the aforementioned high-detail 3D data to run a specialized gesture recognition algorithm. This algorithm process may include: segmenting the hand region from the depth data, extracting the 3D shape features of the hand point cloud (e.g., fingertip position, palm plane normal vector, etc.), and matching these features with a predefined gesture template library. For example, preset gestures in the gesture template library may include, but are not limited to: waving, clenching a fist, or custom door-opening / closing coded gestures.

[0085] Using machine learning models or rule-based classifiers, the above algorithms can determine in real time whether the user's gesture is a valid unlocking gesture and use it as another contactless door opening trigger command, or as a personalized command to distinguish different users.

[0086] Through the Time-of-Flight (TOF) based contactless indoor door opening system and method of the above embodiments of this disclosure, users can unlock the door using specific preset gestures, increasing the flexibility and fun of opening the door, and making it particularly suitable for scenarios where it is inconvenient to approach the door directly, such as when both hands are carrying items. In addition, complex gestures can serve as an additional security verification or personalized command, improving the system's security and its ability to identify different users, providing advanced interactive functions while maintaining the system's privacy protection features.

[0087] In one embodiment, please refer to Figure 3 , Figure 3 The diagram illustrates a flow chart of a Time-of-Flight (TOF)-based contactless indoor door opening method according to an embodiment of this disclosure. This method is applied to the aforementioned TOF-based contactless indoor door opening system, and the process may include the following steps: Step S301: The distance data of each point in the detection area is collected in real time through the TOF monitoring unit; Step S302: The distance data is filtered by the signal processing unit to improve data accuracy and anti-interference capability; Step S303: The algorithm unit constructs three-dimensional depth information based on the processed distance data, identifies the type of the target object, and analyzes its movement direction and speed to determine whether it has the intention to open the door. Step S304: When the intention to open the door is determined, the door opening action is executed through the door control execution unit.

[0088] In one embodiment, the aforementioned TOF-based contactless indoor door opening system is integrated into the indoor handle position of the door, and the TOF monitoring unit is horizontally oriented towards the detection area, including multiple detection points distributed in an array.

[0089] In one embodiment, the distance data is filtered by a signal processing unit, including: The distance data is processed using a Kalman filter algorithm through a signal processing unit.

[0090] In one embodiment, an algorithm unit constructs three-dimensional depth information based on processed distance data, identifies the type of the target object, and analyzes its direction of movement and speed to determine whether it intends to open a door, including: A 3D distance-depth image is constructed based on the distance data processed by the signal processing unit to identify the shape of the target object, and the relationship between the distance data and time is analyzed to perform motion vector analysis.

[0091] In one embodiment, the conditions for determining an intention to open the door include: the target object continuously approaches the door and its movement speed reaches a preset threshold; and, The method also includes the following steps to eliminate interference intentions: by means of an algorithm unit, when the angle between the direction of motion of the target object and the normal of the door exceeds a preset angle threshold, it is determined to be a passing intention; and / or, when the fluctuation of the target object's motion speed exceeds a preset ratio threshold, it is determined to be a loitering intention.

[0092] In one embodiment, the detection resolution of the TOF monitoring unit is not less than 72*72, and the TOF monitoring unit can identify a preset specific gesture.

[0093] It should be noted that the TOF-based contactless indoor door opening system provided in the above embodiments is only illustrated by the division of the above-described program modules when implementing the corresponding TOF-based contactless indoor door opening method. In practical applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the above system can be divided into different program modules to complete all or part of the processing described above. In addition, the system provided in the above embodiments and the corresponding Figure 3 The embodiments of the methods shown belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

[0094] This disclosure also provides an electronic device having the above-described features. Figure 1 The image shows a Time-of-Flight (TOF) based, contactless indoor door opening system.

[0095] Figure 4 A schematic diagram of the structure of an electronic device according to an embodiment of the present disclosure is shown.

[0096] The following is a detailed reference. Figure 4 The diagram illustrates a structural schematic suitable for implementing an electronic device according to embodiments of the present disclosure. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 401, which can perform various appropriate actions and processes based on a program stored in read-only memory (ROM) 402 or a program loaded from memory 408 into random access memory (RAM) 403. RAM 403 also stores various programs and data required for the operation of the electronic device. The processor 401, ROM 402, and RAM 403 are interconnected via bus 404. Input / output (I / O) interface 405 is also connected to bus 404.

[0097] Typically, the following devices can be connected to I / O interface 405: input devices 406 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 407 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 408 including, for example, magnetic tapes, hard disks, etc.; and communication devices 409. Communication device 409 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 4 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0098] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 409, or installed from memory 408, or installed from ROM 402. When the computer program is executed by processor 401, it performs the functions defined in the network data stream hardware offloading method for heterogeneous descriptor unified processing of embodiments of this disclosure.

[0099] Figure 4 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0100] This disclosure also provides a computer-readable storage medium in which the methods described in this disclosure can be implemented in hardware or firmware, or implemented as recordable on a storage medium, or implemented as computer code downloaded over a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and subsequently stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that the computer, processor, microprocessor controller, or programmable hardware includes storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the network data stream hardware offloading method for unified processing of heterogeneous descriptors shown in the above embodiments is implemented.

[0101] A portion of this disclosure can be applied to computer program products, such as computer program instructions, which, when executed by a computer, can invoke or provide methods and / or technical solutions according to this disclosure through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, and installation package files. Accordingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions; the computer compiling the instructions and then executing the corresponding compiled program; the computer reading and executing the instructions; or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0102] Although embodiments of the present disclosure have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present disclosure, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A time-of-flight (TOF) based, seamless indoor door opening system, characterized in that, The system includes: a Time-of-Flight (TOF) monitoring unit, a signal processing unit, an algorithm unit, and a gating execution unit, wherein: The TOF monitoring unit is used to collect distance data of each point in the detection area in real time. The signal processing unit is used to filter the distance data to improve data accuracy and anti-interference capability; The algorithm unit is used to construct three-dimensional depth information based on the filtered distance data, identify the type of the target object, and analyze the direction and speed of the target object's movement to determine whether it has the intention to open the door. A gate control execution unit is used to execute a door opening action when the algorithm unit determines that the intention to open the door is to do so.

2. The system according to claim 1, characterized in that, The system is integrated into the indoor handle of the door, and the TOF monitoring unit is horizontally oriented towards the detection area, including multiple detection points distributed in an array.

3. The system according to claim 1, characterized in that, The signal processing unit is used to process the distance data using a Kalman filtering algorithm.

4. The system according to claim 1, characterized in that, The algorithm unit is specifically used to: construct a 3D distance-depth image based on the distance data processed by the signal processing unit to identify the shape of the target object, and analyze the relationship between the distance data and time to perform motion vector analysis.

5. The system according to claim 1 or 4, characterized in that, The algorithm unit determines the intention to open the door based on the following conditions: the target object continuously approaches the door and its movement speed reaches a preset threshold; and, The algorithm unit is further configured to eliminate interference intent through the following steps: when the angle between the direction of movement of the target object and the normal of the door exceeds a preset angle threshold, it is determined to be a passing intent; and / or, when the fluctuation of the movement speed of the target object exceeds a preset ratio threshold, it is determined to be a loitering intent.

6. The system according to claim 1, characterized in that, The TOF monitoring unit has a detection resolution of no less than 72*72 and is used to recognize preset specific gestures.

7. A time-of-flight (TOF)-based contactless indoor door opening method, applied to any one of the TOF-based contactless indoor door opening systems according to claims 1-6, characterized in that, The method includes: The distance data of each point within the detection area is collected in real time by the TOF monitoring unit; The distance data is filtered by a signal processing unit to improve data accuracy and anti-interference capability. The algorithm unit constructs three-dimensional depth information based on the processed distance data, identifies the type of target object, and analyzes its direction of movement and speed to determine whether it has the intention to open the door. When the intention to open the door is determined, the door opening action is executed through the door control execution unit.

8. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor, configured to implement the steps of the TOF-based contactless indoor door opening method as described in claim 7 when executing the computer program.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, it implements the steps of the TOF-based contactless indoor door opening method as described in claim 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the TOF-based non-sensory indoor door opening method as described in claim 7.

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