Region detection method, device and system, computing equipment and storage medium

Abstract

The invention provides an area detection method, device and system, computing equipment and a storage medium, and relates to the field of millimeter wave radar sensors. Determining position information of the to-be-measured target in the target area based on the millimeter-wave radar, wherein the position information comprises position coordinates, and residence time and height of the position coordinates; dividing the target area into a detection area and an interference area, determining whether the to-be-detected target is located in the detection area or the interference area based on the position coordinates, if the to-be-detected target is located in the interference area, filtering position information representing that the to-be-detected target is located in the interference area, and if the to-be-detected target is located in the detection area, fitting the position information representing that the to-be-detected target is located in the detection area, generating a motion track of the to-be-detected target; and controlling the plurality of intelligent devices in the target area to execute work based on the motion trail. According to the method, the to-be-detected target data can be acquired and processed, the interference data can be distinguished, the accuracy of the motion trail can be ensured, the intelligent control of the intelligent equipment can be realized, the management level of the target area can be improved, and the user experience can be optimized.

Description

Technical Field

[0001] This application relates to the field of millimeter-wave radar sensors, and in particular to a method, device, system, computing device, and storage medium for area detection. Background Art

[0002] With the rapid development of technology, people's demand for intelligent living and working environments is increasing day by day. The area detection solutions in related technologies have significant limitations. Most of them are based on pre-defined areas and can only determine whether there are people in the area. Only based on the simple state of someone or no one, corresponding linkage controls are implemented, such as basic operations like turning on or off lights and adjusting air conditioner temperature. Only focusing on the judgment of the presence or absence of people in the area, it seriously lacks the ability to detect more complex and in-depth changes in the area.

[0003] Existing solutions are weak in dealing with interference. In the actual use environment, the detection signals emitted by millimeter-wave radars are extremely vulnerable to various interference factors such as obstacles and reflectors in the surrounding environment. These interferences can cause the detection signals to be distorted, reflected, or scattered, etc., and then lead to deviations in the detection results. However, existing technologies are difficult to effectively identify and eliminate these interference factors, which not only greatly reduces the detection accuracy but also seriously affects the precision of intelligent device control, and simply cannot meet the urgent needs of high-precision area detection and intelligent control in fields such as smart home and intelligent security. Summary of the Invention

[0004] To solve the deficiencies of the prior art, the purpose of this application is to provide a method, device, system, computing device, and storage medium for area detection. This method can accurately obtain and process the data of the target to be measured, effectively distinguish interference data, ensure the accuracy of the movement trajectory, and then realize the intelligent control of intelligent devices, improve the intelligent management level of the target area, and optimize the user experience.

[0005] To achieve the above purpose, this application adopts the following technical solutions:

[0006] In the first aspect, this application provides a method for area detection, which includes:

[0007] Based on a millimeter-wave radar, determine the position information of the target to be measured in the target area, where the position information at least includes the position coordinates of the target to be measured, the residence time of the target to be measured at the position coordinates, and the height of the target to be measured;

[0008] Divide the target area into a detection area and an interference area. Based on the position coordinates, determine whether the target to be measured is in the detection area or the interference area. If the target to be measured is in the interference area, filter the position information indicating that the target to be measured is in the interference area. If the target to be measured is in the detection area, fit the position information indicating that the target to be measured is in the detection area to generate the motion trajectory of the target to be measured;

[0009] Based on the motion trajectory, control multiple intelligent devices in the target area to perform work.

[0010] In one embodiment, during the process of fitting the position information indicating that the target to be measured is in the detection area, it includes:

[0011] Based on the detection signal sent by the millimeter-wave radar to the target to be measured, determine whether the target to be measured has a heart rate within the set heart rate threshold range;

[0012] If so, determine that the target to be measured is a person, track the target to be measured based on the height and heart rate of the target to be measured to obtain the position information of the target to be measured at different time nodes, and fit the motion trajectory according to the position information;

[0013] If not, determine that the target to be measured is an electronic device and filter the position information.

[0014] In one embodiment, before generating the motion trajectory of the target to be measured, the method further includes:

[0015] Obtain multiple position information corresponding to different time nodes;

[0016] Based on the pre-established motion trend classification, screen out the mutation information from the multiple position information and filter the mutation information. The difference between the position coordinates of the target to be measured corresponding to the mutation information and the position coordinates of the target to be measured corresponding to the adjacent position information is greater than the set coordinate difference threshold range;

[0017] Correspond the filtered position information to the corresponding time nodes respectively.

[0018] In one embodiment, before screening out the mutation information from the multiple position information, the method further includes:

[0019] Determine the interference points for each position information in the multiple position information;

[0020] During the determination of the interference points, determine a position information as the reference point to obtain the height of the target to be measured corresponding to the reference point and the heart rate of the target to be measured;

[0021] Determine the interference points corresponding to the reference points. The difference in the height of the target to be measured corresponding to the interference points and the height of the target to be measured corresponding to the reference points is less than the set height difference threshold, and the difference in the heart rate of the target to be measured corresponding to the interference points and the heart rate of the target to be measured corresponding to the reference points is less than the set heart rate difference threshold. Filter out the interference points from the multiple position information;

[0022] Fit the multiple position information after filtering out the interference points.

[0023] In one embodiment, the detection area includes at least a first detection area and a second detection area. In the process of controlling multiple intelligent devices in the target area to perform tasks based on the movement trajectory, the method includes:

[0024] During the cross-detection area detection, determine the movement direction of the target to be measured based on the movement trajectory. Based on the movement direction and the position coordinates of the target to be measured at the current time node, if the position coordinates at the current time node are in the second detection area, determine that the target to be measured moves from the first detection area to the second detection area;

[0025] If the residence time of the position coordinates of the target to be measured at the current time node is greater than the set time threshold, determine that the target to be measured is in the second detection area;

[0026] Control the corresponding intelligent devices in the second detection area to perform tasks.

[0027] In one embodiment, in the process of determining the interference area, the method includes:

[0028] Send a detection signal to the target area through a millimeter-wave radar to obtain a feedback signal reflected by the obstacles in the target area;

[0029] Determine whether the signal difference between the feedback signal and the detection signal is greater than the set signal difference threshold range. The signal difference includes amplitude difference, phase difference, and frequency difference. If so, determine that the area where the obstacle is located is the interference area;

[0030] If not, determine that the area where the obstacle is located is the detection area.

[0031] In a second aspect, the present application also provides a region detection device, and the device includes:

[0032] A detection unit, configured to determine the position information of the target to be measured in the target area, where the position information at least includes the position coordinates of the target to be measured, the residence time of the target to be measured at the position coordinates, and the height of the target to be measured;

[0033] A trajectory generating unit is used to divide the target area into a detection area and an interference area, determine whether the target to be measured is in the detection area or the interference area based on the position coordinates, if the target to be measured is in the interference area, filter the position information representing that the target to be measured is in the interference area, if the target to be measured is in the detection area, fit the position information representing that the target to be measured is in the detection area, so as to generate a motion trajectory of the target to be measured;

[0034] The execution unit is used to control multiple intelligent devices in the target area to perform work based on the motion trajectory.

[0035] In a third aspect, the present application also provides an area detection system, which includes: a smart device and an area detection device, wherein the smart device includes at least one of a lamp, an air conditioner, a smart lock and a speaker.

[0036] In a fourth aspect, the present application further provides a computing device, comprising a memory and one or more processors; wherein the memory stores computer program code, and the computer program code comprises computer instructions; when the computer instructions are executed by the processor, the area detection method of the first aspect is executed.

[0037] In a fifth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the area detection method of the first aspect.

[0038] The above-mentioned area detection method obtains the position information of the target to be measured in the target area through millimeter wave radar, including position coordinates, residence time and height. The target area is divided into the detection area and the interference area, and the area where the target to be measured is located is determined according to the position coordinates. When it is in the interference area, the corresponding position information is filtered, and when it is in the detection area, the position information is fitted to generate a motion trajectory. Based on the motion trajectory, multiple smart devices in one or more target areas are controlled to work in conjunction. This method can accurately obtain and process the data of the target to be measured, effectively distinguish interference data, ensure the accuracy of the motion trajectory, and then realize the intelligent control of smart devices, improve the intelligent management level of the target area, and optimize the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a flow chart of the area detection method in the implementation manner of this application;

[0040] Figure 2 A flow chart for determining a target to be measured in an implementation manner of the present application;

[0041] Figure 3 A flowchart of screening location information and corresponding time points in an implementation manner of the present application;

[0042] Figure 4Flowchart for eliminating interference points and performing position fitting in the embodiments of the present application;

[0043] Figure 5 Flowchart for controlling multiple intelligent devices in the target area to perform work based on the motion trajectory in the embodiments of the present application;

[0044] Figure 6 Flowchart for determining the interference area in the embodiments of the present application;

[0045] Figure 7 Diagram of the area detection device in the embodiments of the present application;

[0046] Figure 8 Structural diagram of the computing device in the embodiments of the present application. Detailed implementation manners

[0047] To enable those skilled in the art to better understand the solution of the present application, the technical solutions in the specific embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application.

[0048] The present application provides an area detection method, as Figure 1 shown, the method includes the following steps:

[0049] Step 101: Determine the position information of the target to be measured in the target area based on the millimeter-wave radar. The position information includes at least the position coordinates of the target to be measured, the residence time of the target to be measured at the position coordinates, and the height of the target to be measured.

[0050] The millimeter-wave radar can use its characteristics of transmitting and receiving millimeter-wave signals to determine the position information of the target to be measured in the target area. Among them, the position information includes at least the position coordinates of the target to be measured, the residence time of the target to be measured at the position coordinates, and the height of the target to be measured.

[0051] It should be noted that the position coordinates can be calculated through information such as the time delay of the radar echo and the geometric parameters of the radar itself, and can accurately reflect the specific position of the target to be measured in the two-dimensional or three-dimensional space; the residence time of the target to be measured at the position coordinates can be timed from the moment the target is detected at the position coordinates until the target to be measured leaves the coordinate position; the height of the target to be measured can be calculated by using the reflection characteristics of the radar signal in the vertical direction in combination with a specific algorithm, which can assist in determining whether the target is a standing person or a low-lying pet or other items.

[0052] Step 102: Divide the target area into a detection area and an interference area. Determine whether the target to be measured is in the detection area or the interference area based on the position coordinates. If the target to be measured is in the interference area, filter the position information indicating that the target to be measured is in the interference area. If the target to be measured is in the detection area, fit the position information indicating that the target to be measured is in the detection area to generate the motion trajectory of the target to be measured.

[0053] In area detection, divide the target area into a detection area and an interference area. Among them, the detection area is used to focus on monitoring the target to be measured, and the interference area contains interference factors that may affect the detection. Based on the position coordinates of the target to be measured obtained by the millimeter-wave radar and comparing them with the preset position coordinates of the detection area and the interference area, it is possible to determine whether the target is in the detection area or the interference area.

[0054] If the target to be measured is located in the interference area, in order to avoid the interference information affecting the subsequent analysis and judgment of the target to be measured, the position information indicating that the target to be measured is in the interference area can be directly filtered without further processing. If the target to be measured is in the detection area, in order to deeply understand the activities of the target to be measured in the detection area, the position information of the target to be measured in the detection area is fitted. Among them, the process of fitting the position information of the target to be measured in the detection area can use a certain algorithm to integrate multiple discrete position coordinate points in chronological order, associate information such as position coordinates, residence time, and target height to generate the motion trajectory of the target to be measured in the detection area.

[0055] Step 103: Control multiple intelligent devices in the target area to perform tasks based on the motion trajectory.

[0056] After completing the division of the target area, determining that the target to be measured is in the detection area and generating the motion trajectory of the target to be measured, multiple intelligent devices in the target area can be controlled using the motion trajectory of the target to be measured.

[0057] Furthermore, the association rules between the motion trajectory and the actions of the intelligent devices can be preset. For example, in a smart home scenario, if the motion trajectory shows that the target to be measured enters the living room and walks towards the sofa and sits down, the association rule can make the smart TV turn on automatically and the smart air conditioner adjust to a suitable temperature; in a commercial venue, if it is detected that a customer stays and browses in a certain commodity area, the association rule can make the relevant intelligent marketing devices display commodity information.

[0058] In this embodiment, the area detection method obtains the position information of the target to be measured in the target area through a millimeter-wave radar, including position coordinates, residence time, and height. The target area is divided into a detection area and an interference area. According to the position coordinates, it is judged which area the target to be measured is in. When it is in the interference area, the corresponding position information is filtered. When it is in the detection area, the position information is fitted to generate a motion trajectory. Based on the motion trajectory, multiple intelligent devices in the target area are controlled to work. This method can accurately obtain and process the data of the target to be measured, effectively distinguish interference data, ensure the accuracy of the motion trajectory, and then realize the intelligent control of intelligent devices, improve the intelligent management level of the target area, optimize the user experience, and has important application values in the fields of smart home, security monitoring, etc.

[0059] In one embodiment, as Figure 2 shown, in the process of fitting the position information indicating that the target to be measured is in the detection area, the following steps are included:

[0060] Step 201: Based on the detection signal sent by the millimeter-wave radar to the target to be measured, determine whether the target to be measured has a heart rate within a set heart rate threshold range;

[0061] Specifically, the millimeter-wave radar can not only obtain the position information of the target, but also send a detection signal to the target to be measured. Among them, humans have the physiological characteristic of heart rate. When the detection signal emitted by the millimeter-wave radar irradiates the target to be measured, the heart rate situation of the target to be measured can be analyzed based on the change of the echo signal generated by the minute vibration of the target to be measured's body caused by the heartbeat.

[0062] Furthermore, by comparing with a pre-set heart rate threshold range, it can be determined whether the heart rate of the target to be measured is within the set threshold range. This determination result helps to distinguish whether the target in the detection area is a person with vital signs or an inanimate object.

[0063] Step 202: If so, determine that the target to be measured is a person, track the target to be measured based on the height and heart rate of the target to be measured to obtain the position information of the target to be measured at different time nodes, and fit a motion trajectory according to the position information.

[0064] When it is determined that the target to be measured has a heart rate within the set heart rate threshold range, it can be determined that the target to be measured is a person. It should be noted that heart rate is a physiological characteristic unique to living beings such as humans, and being within a specific heart rate threshold range is the key basis for judging as a person.

[0065] The target to be measured is tracked by combining its height and heart rate. Among them, the height can be used as a specific feature of the person; the heart rate is relatively stable within a certain period of time, which can also be used as a feature to distinguish different people. By continuously monitoring these two features, the position information of the person is obtained at different time nodes. As time goes by, multiple discrete position information can be obtained. Using specific mathematical algorithms and fitting techniques, the position information at different time nodes is integrated and processed in chronological order to form a motion trajectory that can reflect the movement of the person in the detection area.

[0066] Step 203: If not, determine that the target to be detected is an electronic device and filter the location information.

[0067] When a detection signal is sent to a target based on a millimeter wave radar, it is determined through analysis that the target does not have a heart rate within a set heart rate threshold range, which indicates that the target is not a person with vital signs. In common scenarios, the target may be an inanimate object such as an electronic device.

[0068] Furthermore, since the region detection method mainly focuses on the activities of people and the control of smart devices based on the movement trajectory of people, the location information of the electronic device has no practical significance for the core function. In order to avoid irrelevant information interfering with subsequent operations, the location information representing the electronic device can be filtered and no further processing or analysis is performed on it.

[0069] It should be noted that step 202 and step 203 are in parallel relationship, and the order of the two can be step 202 first and then step 203, or step 203 first and then step 202.

[0070] In this embodiment, when fitting the position information of the target to be measured in the detection area, the millimeter wave radar is used to send a detection signal to determine whether the heart rate of the target to be measured is within the set threshold range. If so, it is determined to be a person, and the position information of different time nodes is obtained by combining the height and heart rate tracking and fitting the motion trajectory. If not, it is determined to be an electronic device and the position information is filtered. This method can improve detection accuracy, avoid interference from electronic devices, accurately identify and track people, optimize the intelligent control experience, and allow smart devices to be linked according to the accurate motion trajectory of people.

[0071] In one embodiment, Figure 3 As shown, before generating the motion trajectory of the target to be measured, the method further includes the following steps:

[0072] Step 301: Acquire multiple location information corresponding to different time nodes.

[0073] Before the key operation of generating the motion trajectory of the target to be measured, the target area is monitored in real time based on a millimeter-wave radar. For the target to be measured, its position information is continuously collected at different time nodes. Among them, the division of time nodes can be determined according to a preset time interval. For example, it is recorded once every 1 second or a shorter time. Each time a record is made, based on the characteristics of the millimeter-wave signals transmitted and received by the millimeter-wave radar, by calculating parameters such as the propagation time and reflection angle of the signals, the position coordinates, residence time, height and other position information of the target to be measured at this time node are obtained. As time goes by, multiple position information corresponding to multiple different time nodes can be accumulated.

[0074] Step 302: Based on the pre-established motion trend classification, screen out the mutation information from the multiple position information and filter the mutation information. The difference between the position coordinates of the target to be measured corresponding to the mutation information and the position coordinates of the target to be measured corresponding to the adjacent position information is greater than the set coordinate difference threshold range.

[0075] The pre-established motion trend classification can be categories set based on the possible motion patterns and rules of the target to be measured under normal circumstances. Based on the motion trend classification, the multiple position information obtained can be screened.

[0076] During the screening process, focus on the difference between the position coordinates corresponding to adjacent position information. If the difference between the position coordinates of the target to be measured corresponding to a certain position information and the position coordinates corresponding to the adjacent position information is greater than the set coordinate difference threshold range, this position information can be determined as mutation information. Among them, the mutation information may be caused by factors such as radar detection errors and external interferences, and does not represent the true motion situation of the target to be measured. In order to avoid the abnormal data in the mutation information from affecting the fitting effect of the motion trajectory, the mutation information can be filtered.

[0077] Step 303: Corresponding the filtered position information to the corresponding time nodes respectively.

[0078] The filtered position information is the remaining position information after screening and removing the mutation information, and is an information set that can more accurately reflect the true position of the target to be measured. Further, each position information is obtained under the corresponding time node. The time node records the specific moment when this position information is obtained, which is an important dimension for constructing the motion trajectory.

[0079] Corresponding the filtered position information to the corresponding time nodes respectively, that is, corresponding each screened position information to the specific time when it is detected. This operation can lay a foundation for generating the motion trajectory subsequently. Only when the position information and time information are accurately corresponding one by one, can the position information be connected in chronological order subsequently, so as to depict the motion trajectory of the target to be measured changing with time in the target area.

[0080] In this embodiment, before generating the motion trajectory of the target to be measured, the method obtains a plurality of position information corresponding to different time nodes, filters out mutation information with a position coordinate difference greater than the set coordinate difference threshold range according to the pre-established motion trend classification, and corresponds the filtered position information to the corresponding time nodes. This method effectively improves the data quality, filters out mutation information to avoid the influence of detection errors and external interference, makes the data used to generate the motion trajectory more accurate and reliable, accurately corresponds the position information to the time nodes, and lays a foundation for generating a continuous trajectory that truly reflects the motion state of the target to be measured.

[0081] In one embodiment, as Figure 4 shown, before filtering out the mutation information from the plurality of position information, the method further includes the following steps:

[0082] Step 401: Determine whether there are interference points for each position information among the plurality of position information.

[0083] Since the millimeter-wave radar is affected by various external factors during the actual detection process, such as electromagnetic interference in the surrounding environment, reflection interference from other objects, etc., these factors may cause the obtained position information to be inaccurate or abnormal, that is, interference points may appear.

[0084] Determining whether there are interference points for each position information means analyzing and evaluating each position information in detail according to certain rules and algorithms. For example, it is possible to judge whether a position information is an interference point based on aspects such as the continuity, rationality of the position information, and its relevance to other surrounding position information. If a certain position information significantly deviates from the normal motion pattern or has a large conflict with the surrounding position information, it may be determined as an interference point.

[0085] Step 402: During the determination of interference points, determine a position information as a reference point to obtain the height of the target to be measured corresponding to the reference point and the heart rate of the target to be measured.

[0086] During the determination of interference points, it is necessary to determine a position information as a reference point. Setting the reference point is to provide a stable and comparable benchmark for the determination of interference points. The numerous position information obtained during the detection process is dynamic and complex, and the setting of the reference point can construct a relatively stable comparison standard.

[0087] After determining the reference point, obtain the height and heart rate of the target to be measured corresponding to this reference point. It should be noted that height is an important physical property of the target to be measured in space, and different targets often have different height characteristics; the heart rate is a key physiological indicator reflecting whether the target has vital signs. By obtaining the height and heart rate of the target to be measured at the reference point, the height and heart rate of the target corresponding to other position information can be compared with the characteristics of the reference point. If the height and heart rate of the target corresponding to a certain position information differ greatly from the characteristics of the reference point and exceed the reasonable fluctuation range, then it is very likely that this position information is abnormal data caused by interference and can be determined as an interference point. Based on the characteristics of the reference point, interference points among numerous position information can be identified more accurately.

[0088] Step 403: Determine the interference points corresponding to the reference point. The difference between the height of the target to be measured corresponding to the interference point and the height of the target to be measured corresponding to the reference point is less than the set height difference threshold, and the difference between the heart rate of the target to be measured corresponding to the interference point and the heart rate of the target to be measured corresponding to the reference point is less than the set heart rate difference threshold. Filter out the interference points from the multiple position information.

[0089] Determine the interference points corresponding to the reference point. According to the pre-set rules, find the interference points that meet specific conditions from the multiple position information. Among them, the specific conditions can be that the difference between the height of the target to be measured corresponding to the interference point and the height of the target to be measured corresponding to the reference point is less than the set height difference threshold; and the difference between the heart rate of the target to be measured corresponding to the interference point and the heart rate of the target to be measured corresponding to the reference point is less than the set heart rate difference threshold.

[0090] Under normal circumstances, if the height and heart rate of the target corresponding to a certain position information are very close to the corresponding characteristics of the reference point, then it may be that this position information does not truly reflect the data generated during the movement of the target to be measured, but is repeated or false data caused by external interference (such as abnormal radar signal reflection, environmental electromagnetic interference, etc.). To avoid the negative impact of interference data on the subsequent generation of the movement trajectory and the analysis and control based on the trajectory, the interference points that meet specific conditions can be filtered out from the multiple position information.

[0091] Step 404: Fit the multiple position information after filtering out the interference points.

[0092] After determining the interference points, determining the reference points, and filtering the interference points, the multiple position information after filtering the interference points is fitted. Among them, fitting is a data processing method, and its purpose is to find a curve or trajectory that best conforms to the distribution law of these discrete position information. Each position information includes key data such as the position coordinates and residence time of the target to be measured at a specific time node, and has a certain continuity and correlation in time and space. Through specific mathematical algorithms and models, such as the least squares method, the discrete position information is connected in chronological order, so that these position information fall on the fitted curve as much as possible.

[0093] Furthermore, the fitted motion trajectory can intuitively and accurately display the motion path and behavior pattern of the target to be measured in the target area. It can not only understand how the target to be measured moves in the area, but also provide a basis for subsequent controlling multiple intelligent devices in the target area to perform work based on the motion trajectory. For example, according to the fitted motion trajectory, it is judged whether the target to be measured is moving towards the bedroom or the living room, and then the intelligent devices such as lights and air conditioners in the corresponding area are controlled to make reasonable responses.

[0094] In this embodiment, before screening mutation information from multiple position information, the interference points of each position information are determined first. When determining, a position information is determined as a reference point, and the height and heart rate of the corresponding target to be measured are obtained. The interference points with the differences in height and heart rate from the reference point less than the set thresholds are found and filtered. Finally, the multiple position information after filtering the interference points is fitted. This method improves the data quality. Through the determination and filtering of interference points, the false or duplicate data caused by external interference are removed, so that the fitted motion trajectory can more truly reflect the motion situation of the target to be measured, and provides an accurate and reliable basis for subsequent intelligent device control and behavior analysis based on the motion trajectory.

[0095] In one embodiment, as Figure 5 shown, the detection area includes at least a first detection area and a second detection area. In the process of controlling multiple intelligent devices in the target area to perform work based on the motion trajectory, the method includes the following steps:

[0096] Step 501: During the process of cross-detection area detection, based on the motion trajectory, determine the motion direction of the target to be measured. Based on the motion direction and the position coordinates of the target to be measured at the current time node, if the position coordinates at the current time node are in the second detection area, it is determined that the target to be measured moves from the first detection area to the second detection area.

[0097] Determine the motion direction of the target to be measured based on the generated motion trajectory. Among them, the motion trajectory is fitted by the position information at multiple different time nodes. By analyzing the change trend of the position information over time, it can be judged in which direction the target to be measured is moving.

[0098] Make a comprehensive judgment by combining the movement direction and the position coordinates of the target to be measured at the current time node. If the position coordinates at the current time node show that the target to be measured is in the second detection area, since its movement direction is known and considering the spatial position relationship between the two detection areas, it can be reasonably inferred that the target to be measured has moved from the first detection area to the second detection area.

[0099] Step 502: If the residence time of the position coordinates of the target to be measured at the current time node is greater than the set time threshold, it is determined that the target to be measured is in the second detection area.

[0100] Specifically, a set time threshold can be a standard duration determined in advance according to the actual scenario and requirements. If it is detected that the target to be measured is at the current position coordinates (this position coordinate is in the second detection area), and the residence time of the target to be measured at this coordinate position exceeds the set time threshold, it means that the target to be measured is not just passing by the second detection area briefly, but has a relatively long stay, and it can be determined that the target to be measured is in the second detection area.

[0101] Step 503: Control the corresponding intelligent device in the second detection area to perform work.

[0102] In the overall planning of the target area, association rules between intelligent devices and specific scenarios or user requirements are preset for each detection area. Once it is determined that the target to be measured is in the second detection area, according to the preset association rules, it can be identified which intelligent devices in the second detection area need to be activated and what kind of work to perform.

[0103] Exemplarily, if the second detection area is a bedroom, when it is determined that a person enters the bedroom and the residence time meets the standard, the intelligent light can be controlled to adjust to a soft brightness, the intelligent air conditioner can be adjusted to a temperature suitable for sleeping, and the intelligent curtain can be automatically drawn, etc.

[0104] In this embodiment, when the method includes the first and second detection areas in the detection area, it controls the intelligent devices in the target area based on the movement trajectory. In the cross-detection area detection, it determines the movement direction of the target to be measured according to the movement trajectory, combines the current position coordinates to judge that it moves from the first detection area to the second detection area, determines that it is in the second detection area according to whether the residence time exceeds the threshold, and controls the intelligent devices in this area to work. This method can accurately locate the position and state of the target to be measured, realize the precise control of intelligent devices, provide personalized services for users, and improve the usage experience.

[0105] In one embodiment, the target area may be a room. The first detection area of the detection area in the target area may be the door area, and the second detection area may be the bed area. For the door area, when the target to be measured is located in the door area, if the movement trajectory of the target to be measured is stable within the range of the door area, no status update is performed; when the movement trajectory of the target to be measured is moving from the inside of the door area to the outside of the door area, and the position coordinate of the target to be measured moving to the outside of the door area is greater than the preset threshold range from the position coordinate of the edge of the door area, it can be determined that the target to be measured is in the out-of-door state; when the movement trajectory of the target to be measured is moving from the outside of the door area to the inside of the door area, and the position coordinate of the target to be measured moving to the inside of the door area is greater than the preset threshold range from the position coordinate of the edge of the door area, it can be determined that the target to be measured is in the in-of-door state.

[0106] For the bed area, when the movement trajectory of the target to be measured is moving from the outside of the bed area to the inside of the bed area, timing starts when the target to be measured enters the bed area, and the duration of the target to be measured staying in the bed area is greater than the preset time threshold (this time threshold can be preset in advance), it can be determined that the target to be measured is in the in-bed state; when the movement trajectory of the target to be measured is moving from the inside of the bed area to the outside of the bed area, timing starts after the target to be measured leaves the bed area, and the duration of the target to be measured leaving the bed area is greater than the preset time threshold (this time threshold can be preset in advance), it can be determined that the target to be measured is in the out-of-bed state; when the acceleration of the movement trajectory of the target to be measured in the bed area is relatively large, it cannot be determined whether the target to be measured is in the in-bed state or the out-of-bed state.

[0107] In one embodiment, as Figure 6 shown, in the process of determining the interference area, the method includes the following steps:

[0108] Step 601: Send a detection signal to the target area through a millimeter-wave radar to obtain a feedback signal reflected by an obstacle in the target area.

[0109] The millimeter-wave radar has the ability to emit millimeter-wave signals in a specific frequency band, and the millimeter-wave signals will be directionally emitted into the target area. The target area is usually a space containing various objects, and there are obstacles such as walls, furniture, and large equipment. When the detection signal emitted by the millimeter-wave radar contacts an obstacle during the propagation in the target area, due to the physical characteristics of the obstacle, the signal will be reflected. The reflected signal will return to the millimeter-wave radar along different paths, and the signal returned to the radar is the feedback signal. The feedback signal contains rich information. For example, the distance between the obstacle and the radar can be calculated through the round-trip time of the signal, the approximate azimuth of the obstacle can be determined based on the angle of signal reflection, and some material characteristics of the obstacle can be inferred according to the change of signal strength. By carefully analyzing and processing the feedback signal, the distribution of obstacles in the target area can be outlined.

[0110] Step 602: Determine whether the signal difference between the feedback signal and the detection signal is greater than the set signal difference threshold range. The signal difference includes amplitude difference, phase difference, and frequency difference. If so, determine that the area where the obstacle is located is the interference area.

[0111] The signal difference between the feedback signal and the detection signal can include amplitude difference, phase difference, and frequency difference. Among them, the amplitude difference can reflect the difference in intensity between the detection signal and the feedback signal. Different obstacles have different attenuation degrees for the signal intensity. If the amplitude difference is too large, it can indicate that the signal has been greatly blocked or interfered during propagation. The phase difference can represent the relative position difference in time between the two signals. The presence of an obstacle may change the propagation path of the signal, thereby causing a change in phase. The frequency difference can be the difference in frequency between the detection signal and the feedback signal. Some special obstacles or complex environments may affect the frequency of the signal.

[0112] The preset signal difference threshold range can be a standard boundary that comprehensively considers various factors. After calculating the amplitude difference, phase difference, and frequency difference between the feedback signal and the detection signal, compare these differences with the set signal difference threshold range. If any one of the differences is greater than the set signal difference threshold range, it means that the obstacle has caused significant interference to the detection signal, that is, due to the presence of the obstacle in the area where the obstacle is located, it has a greater impact on the normal propagation and reception of the millimeter-wave radar signal, resulting in obvious abnormalities in the signal. Further, it can be determined that the area where the obstacle is located is the interference area.

[0113] Step 603: If not, determine that the area where the obstacle is located is the detection area.

[0114] Judge whether the signal difference between the feedback signal and the detection signal, that is, the amplitude difference, phase difference, and frequency difference, is greater than the set signal difference threshold range. If the judgment result is no, it means that the differences in amplitude, phase, and frequency between the feedback signal and the detection signal are all within the set signal difference threshold range, that is, after the detection signal emitted by the millimeter-wave radar encounters an obstacle and reflects back, the change in the signal is within the acceptable normal fluctuation range. It means that the obstacle has not caused significant interference to the propagation and reflection of the millimeter-wave radar signal, and the signal can relatively stably and accurately reflect the relevant information of the obstacle, such as its position, approximate contour, etc. In this case, it shows that the area environment where the obstacle is located is relatively stable and will not have a greater negative impact on the detection work of the millimeter-wave radar. Therefore, the area where the obstacle is located can be determined as the detection area.

[0115] It should be noted that step 602 and step 603 are in a parallel relationship, and the sequence of the two can be step 602 first and then step 603, or step 603 first and then step 602.

[0116] In this embodiment, when determining the interference area, the method uses a millimeter-wave radar to send a detection signal to the target area and obtain the feedback signal reflected by the obstacle, and compares whether the amplitude, phase, and frequency difference between the feedback signal and the detection signal are greater than the set signal difference threshold range. If it is greater, it is determined that the area where the obstacle is located is the interference area; if it is less, it is determined as the detection area. This method can distinguish areas with different degrees of interference from obstacles in the target area, mark the area with greater interference as the interference area, and determine the area with less interference and stable signal as the detection area.

[0117] Based on the same inventive concept, the embodiment of the present application also provides a region detection device. The implementation solution provided by this device to solve the problem is similar to the implementation solution described in the above method. Therefore, the specific limitations in one or more of the following region detection device embodiments can refer to the limitations on the region detection method in the above text, and will not be repeated here.

[0118] In one embodiment, as Figure 7 shown, the embodiment of the present application also provides a region detection device, which includes:

[0119] A detection unit 701, configured to determine the position information of the target to be measured in the target area, where the position information at least includes the position coordinates of the target to be measured, the residence time of the target to be measured at the position coordinates, and the height of the target to be measured;

[0120] A trajectory generation unit 702, configured to divide the target area into a detection area and an interference area, determine whether the target to be measured is in the detection area or the interference area based on the position coordinates. If the target to be measured is in the interference area, filter the position information indicating that the target to be measured is in the interference area. If the target to be measured is in the detection area, fit the position information indicating that the target to be measured is in the detection area to generate the motion trajectory of the target to be measured;

[0121] An execution unit 703, configured to control a plurality of intelligent devices in the target area to perform work based on the motion trajectory.

[0122] In one embodiment, during the process of fitting the position information indicating that the target to be measured is in the detection area, the trajectory generation unit 702 is specifically configured to: based on the detection signal sent by the millimeter-wave radar to the target to be measured, determine whether the target to be measured has a heart rate within a set heart rate threshold range; if so, determine that the target to be measured is a person, track the target to be measured based on the height and heart rate of the target to be measured to obtain the position information of the target to be measured at different time nodes, and fit a motion trajectory according to the position information; if not, determine that the target to be measured is an electronic device and filter the position information.

[0123] In one embodiment, before generating the motion trajectory of the target to be measured, the trajectory generation unit 702 is specifically configured to: obtain a plurality of position information corresponding to different time nodes; based on a pre-established motion trend classification, screen out mutation information from the plurality of position information and filter the mutation information, where the difference between the position coordinates of the target to be measured corresponding to the mutation information and the position coordinates of the target to be measured corresponding to the adjacent position information is greater than a set coordinate difference threshold range; and correspond the filtered position information to the corresponding time nodes respectively.

[0124] In one embodiment, before screening out the mutation information from the plurality of position information, the trajectory generation unit 702 is specifically configured to: determine interference points for each position information in the plurality of position information; during the determination of interference points, determine a position information as a reference point to obtain the height of the target to be measured corresponding to the reference point and the heart rate of the target to be measured; determine the interference points corresponding to the reference point, where the difference between the height of the target to be measured corresponding to the interference point and the height of the target to be measured corresponding to the reference point is less than a set height difference threshold, and the difference between the heart rate of the target to be measured corresponding to the interference point and the heart rate of the target to be measured corresponding to the reference point is less than a set heart rate difference threshold, and filter out the interference points from the plurality of position information; and fit the plurality of position information after filtering out the interference points.

[0125] In one embodiment, before screening out the mutation information from the plurality of position information, the execution unit 703 is specifically configured to: determine interference points for each position information in the plurality of position information; during the determination of interference points, determine a position information as a reference point to obtain the height of the target to be measured corresponding to the reference point and the heart rate of the target to be measured; determine the interference points corresponding to the reference point, where the difference between the height of the target to be measured corresponding to the interference point and the height of the target to be measured corresponding to the reference point is less than a set height difference threshold, and the difference between the heart rate of the target to be measured corresponding to the interference point and the heart rate of the target to be measured corresponding to the reference point is less than a set heart rate difference threshold, and filter out the interference points from the plurality of position information;

[0126] Fit the plurality of position information after filtering out the interference points.

[0127] In one embodiment, the detection area of the execution unit 703 includes at least a first detection area and a second detection area. During the process of controlling multiple intelligent devices in the target area to perform tasks based on the movement trajectory, it is specifically configured to: during the cross-detection area detection, determine the movement direction of the target to be measured based on the movement trajectory, and based on the movement direction and the position coordinates of the target to be measured at the current time node, if the position coordinates at the current time node are in the second detection area, determine that the target to be measured moves from the first detection area to the second detection area; if the residence time of the position coordinates of the target to be measured at the current time node is greater than the set time threshold, determine that the target to be measured is in the second detection area; control the corresponding intelligent device in the second detection area to perform tasks.

[0128] In one embodiment, during the process of determining the interference area, the execution unit 703 is specifically configured to: send a detection signal to the target area through a millimeter-wave radar to obtain a feedback signal reflected by an obstacle in the target area; determine whether the signal difference between the feedback signal and the detection signal is greater than the set signal difference threshold range, and the signal difference includes an amplitude difference, a phase difference, and a frequency difference; if so, determine that the area where the obstacle is located is the interference area; if not, determine that the area where the obstacle is located is the detection area.

[0129] Based on the same concept, the present application further provides a region detection system including: intelligent devices and a region detection device, wherein the intelligent devices include at least one of a lamp, an air conditioner, an intelligent lock, and a speaker.

[0130] Specifically, the region detection device is responsible for detecting the target area. For example, by means of technologies such as millimeter-wave radar, it can obtain information such as the positions and movement trajectories of targets in the area, and can also determine different functional areas such as interference areas and detection areas. The intelligent devices are the carriers for realizing specific functions and services, covering at least one of a lamp, an air conditioner, an intelligent lock, and a speaker. The intelligent devices and the region detection device work together, and based on the detected region information and target status, realize intelligent control and services, improving the practicability and user experience of the entire system.

[0131] Based on the same concept, the present application further provides a computing device including a memory and a processor, where the memory stores a computer program, and the processor executes the region detection method in the computer program.

[0132] In one embodiment, a computing device is provided, including a memory and a processor. The computing device may be a terminal, and its internal structure diagram may be as Figure 8As shown in the figure. The computing device includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computing device is used to provide computing and control capabilities. The memory of the computing device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computing device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a region detection method. The display screen of the computing device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computing device can be a touch layer covered on the display screen, or a button, a trackball, or a touchpad provided on the housing of the computing device, or an external keyboard, a touchpad, or a mouse, etc.

[0133] Those skilled in the art can understand that Figure 8 the structure shown in the figure is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computing device to which the solution of the present application is applied. The specific computing device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0134] Based on the same concept, the present application also provides a computer-readable storage medium, on which a computer program is stored, and the computer program is executed by the processor to perform the region detection method of the computer program.

[0135] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, a database, or other media used in the embodiments provided by the present application can include at least one of non-volatile and volatile memories. The databases involved in the embodiments provided by the present application can include at least one of relational databases and non-relational databases.

[0136] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered to be within the scope described in this specification.

[0137] The above embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation to the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A region detection method, characterized in that: The method comprises: Determine the position information of the target to be measured in the target area based on the millimeter wave radar, wherein the position information includes at least the position coordinates of the target to be measured, the residence time of the target to be measured at the position coordinates, and the height of the target to be measured; The target area is divided into a detection area and an interference area, and based on the position coordinates, it is determined whether the target to be measured is in the detection area or the interference area; if the target to be measured is in the interference area, the position information representing that the target to be measured is in the interference area is filtered; if the target to be measured is in the detection area, the position information representing that the target to be measured is in the detection area is fitted to generate a motion trajectory of the target to be measured; Based on the motion trajectory, multiple smart devices in the target area are controlled to perform work.

2. The method according to claim 1, characterized in that: In the process of fitting the position information characterizing that the target to be detected is in the detection area, the method includes: Determining whether the target to be measured has a heart rate within a set heart rate threshold range based on a detection signal sent by the millimeter wave radar to the target to be measured; If yes, it is determined that the target to be measured is a person, the target to be measured is tracked based on the height and heart rate of the target to be measured to obtain the position information of the target to be measured at different time nodes, and the motion trajectory is fitted according to the position information; If not, it is determined that the target to be detected is an electronic device, and the location information is filtered.

3. The method according to claim 2, characterized in that Before generating the motion trajectory of the target to be measured, the method further includes: Acquire the plurality of location information corresponding to different time nodes; Based on the pre-established motion trend classification, the mutation information is screened out from the plurality of the position information, and the mutation information is filtered, and the difference between the position coordinates of the target to be measured corresponding to the mutation information and the position coordinates of the target to be measured corresponding to the adjacent position information is greater than a set coordinate difference threshold range; The filtered location information corresponds to corresponding time nodes respectively.

4. The method according to claim 3, characterized in that Before screening out mutation information from the plurality of position information, the method further comprises: Performing interference point determination on each of the plurality of position information; In the process of determining the interference point, determining one of the position information as a reference point to obtain the height of the target to be measured and the heart rate of the target to be measured corresponding to the reference point; Determine an interference point corresponding to the reference point, the difference between the height of the target to be measured corresponding to the interference point and the height of the target to be measured corresponding to the reference point is less than a set height difference threshold, the difference between the heart rate of the target to be measured corresponding to the interference point and the heart rate of the target to be measured corresponding to the reference point is less than a set heart rate difference threshold, and filter out the interference point from the multiple position information; The plurality of position information after filtering out the interference points are fitted.

5. The method according to claim 1, characterized in that The detection area includes at least a first detection area and a second detection area. In the process of controlling a plurality of smart devices in the target area to perform work based on the motion trajectory, the method includes: In the process of cross-detection area detection, the moving direction of the target to be detected is determined based on the moving trajectory, and based on the moving direction and the position coordinates of the target to be detected at the current time node, if the position coordinates of the current time node are in the second detection area, it is determined that the target to be detected is moving from the first detection area to the second detection area; If the residence time of the target to be detected at the position coordinates at the current time node is greater than a set time threshold, it is determined that the target to be detected is in the second detection area; The corresponding smart device in the second detection area is controlled to perform work.

6. The method according to claim 1, characterized in that In determining the interference zone, the method includes: Sending a detection signal to the target area through the millimeter wave radar to obtain a feedback signal after being reflected by obstacles in the target area; Determine whether the signal difference between the feedback signal and the detection signal is greater than a set signal difference threshold range, the signal difference including an amplitude difference, a phase difference, and a frequency difference; if so, determine that the area where the obstacle is located is the interference area; If not, the area where the obstacle is located is determined as the detection area.

7. A region detection device, characterized in that: include: A detection unit, used to determine the position information of the target to be measured in the target area, wherein the position information at least includes the position coordinates of the target to be measured, the residence time of the target to be measured at the position coordinates, and the height of the target to be measured; A trajectory generating unit, used for dividing the target area into a detection area and an interference area, determining whether the target to be measured is in the detection area or the interference area based on the position coordinates, if the target to be measured is in the interference area, filtering the position information representing that the target to be measured is in the interference area, if the target to be measured is in the detection area, fitting the position information representing that the target to be measured is in the detection area, so as to generate a motion trajectory of the target to be measured; An execution unit is used to control multiple smart devices in the target area to perform work based on the motion trajectory.

8. A region detection system, characterized in that: include: A smart device and an area detection apparatus as claimed in claim 8, wherein the smart device comprises at least one of a lamp, an air conditioner, a smart lock and a speaker.

9. A computing device, characterized in that The computing device comprises a memory and one or more processors; wherein the memory stores computer program code, and the computer program code comprises computer instructions; when the computer instructions are executed by the processor, the method according to any one of claims 1 to 6 is executed.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, it implements the method according to one or more of claims 1 to 6.

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