Human body detection method and device, intelligent device and computer readable storage medium

Abstract

This invention provides a human body detection method, apparatus, intelligent device, and computer-readable storage medium, relating to the field of sensor technology. When detecting a human body, a photosensitive sensor first acquires the current environmental value and several target environmental values, and then obtains benchmark data based on these target environmental values. The benchmark data includes limit values ​​and average environmental values. Next, a first judgment result is obtained based on the comparison between the current environmental value and the average environmental value. Finally, the target detection result is determined based on the first judgment result, the current environmental value, and the limit values. This method can actively sense human movement with high accuracy, thus simplifying user operation and improving intelligence and user experience when applied to waking up intelligent devices.

Description

Technical Field

[0001] This invention relates to the field of sensor technology, and in particular to a human body detection method, apparatus, intelligent device, and computer-readable storage medium. Background Technology

[0002] Currently, the wake-up of smart devices such as electric toothbrushes relies on human active triggering. This human active triggering wake-up method is relatively complicated for users, has low intelligence, and results in a poor user experience. Summary of the Invention

[0003] The purpose of this invention is to provide a human body detection method, device, smart device, and computer-readable storage medium to actively sense the human body. When applied to the wake-up of a smart device, it simplifies user operation and improves intelligence and user experience.

[0004] In a first aspect, embodiments of the present invention provide a human body detection method, the human body detection method comprising:

[0005] The current environmental value and several target environmental values ​​are acquired by a photosensitive sensor, and benchmark data is obtained based on the several target environmental values, wherein the benchmark data includes limit values ​​and average environmental values;

[0006] Based on the comparison between the current environmental value and the average environmental value, a first judgment result is obtained;

[0007] The target detection result is determined based on the first judgment result, the current environmental value, and the limit value.

[0008] In one possible implementation of the first aspect, the limit value includes a maximum environmental value and a minimum environmental value; determining the target detection result based on the first judgment result, the current environmental value, and the limit value includes:

[0009] When the first judgment result is that the current environmental value is less than the average environmental value, it is then determined whether the current environmental value is less than the minimum environmental value to obtain a second judgment result.

[0010] When the first determination result is that the current environmental value is greater than the average environmental value, it is determined whether the current environmental value is greater than the maximum environmental value, and a third determination result is obtained.

[0011] The target detection result is obtained based on the second judgment result or the third judgment result.

[0012] In one possible implementation of the first aspect, obtaining the target detection result based on the second judgment result or the third judgment result includes:

[0013] When the second determination result is that the current environmental value is less than the minimum environmental value, determine whether the current environmental value meets the first preset condition, and obtain the first detection result;

[0014] When the third determination result is that the current environmental value is greater than the maximum environmental value, it is determined whether the current environmental value meets the second preset condition, and a second detection result is obtained.

[0015] The target detection result is obtained based on the first detection result or the second detection result.

[0016] In one possible implementation of the first aspect, the reference data further includes the difference between the current environmental value and the average environmental value, and an environmental difference, wherein the difference between the current environmental value and the average environmental value includes a first difference and a second difference;

[0017] The first preset condition includes: within a preset time period, the number of times the first difference is continuously detected to be greater than the environmental difference is less than a preset number threshold;

[0018] The second preset condition includes: within a preset time period, the number of times the second difference is continuously detected to be greater than the environmental difference is less than the preset number threshold.

[0019] In one possible implementation of the first aspect, the preset duration includes 3 seconds, and the preset number threshold includes 6.

[0020] In one possible implementation of the first aspect, the first preset condition further includes: the first value obtained by reducing the average environmental value by a first preset factor is less than or equal to the current environmental value;

[0021] The second preset condition also includes: the second value obtained by multiplying the average environmental value by a second preset factor is greater than or equal to the current environmental value.

[0022] In one possible implementation of the first aspect, both the first preset multiple and the second preset multiple are not less than 4.

[0023] Secondly, embodiments of the present invention also provide a human body detection device, the human body detection device comprising:

[0024] The data acquisition module is used to acquire the current environmental value and several target environmental values ​​through a photosensitive sensor, and to obtain benchmark data based on the several target environmental values, wherein the benchmark data includes limit values ​​and average environmental values;

[0025] The comparison and judgment module is used to obtain a first judgment result based on the comparison result between the current environmental value and the average environmental value;

[0026] The target detection module is used to determine the target detection result based on the first judgment result, the current environmental value, and the limit value.

[0027] Thirdly, embodiments of the present invention also provide an intelligent device, including a memory and a processor. The memory stores a computer program that can run on the processor. When the processor executes the computer program, it implements the steps of the human body detection method of the first aspect.

[0028] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the human body detection method of the first aspect.

[0029] The human body detection method, apparatus, smart device, and computer-readable storage medium provided in this invention, when performing human body detection, first acquire the current environmental value and several target environmental values ​​through a photosensitive sensor, and obtain benchmark data based on the several target environmental values, wherein the benchmark data includes limit values ​​and average environmental values; then, based on the comparison result between the current environmental value and the average environmental value, a first judgment result is obtained; and then, based on the first judgment result, the current environmental value, and the limit values, the target detection result is determined. This allows for proactive sensing of human movement with high accuracy, thereby simplifying user operation and improving intelligence and user experience when applied to waking up smart devices. Attached Figure Description

[0030] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0031] Figure 1 This is a flowchart illustrating a human body detection method provided in an embodiment of the present invention;

[0032] Figure 2 This is a graph showing the relationship between the resistance value of a photosensitive sensor and ambient light.

[0033] Figure 3 This is a graph showing the relationship between the sampling voltage of the photosensitive sensor and ambient light.

[0034] Figure 4 This is a schematic diagram of the sampling voltage change of a photosensitive sensor when a human body passes through a recognition area, provided as an embodiment of the present invention.

[0035] Figure 5This is a schematic diagram of the sampling voltage change of a photosensitive sensor when a human body passes through the recognition area, provided in another embodiment of the present invention.

[0036] Figure 6 A flowchart illustrating another human body detection method provided in an embodiment of the present invention;

[0037] Figure 7 This is a schematic diagram of the voltage change detected by a pyroelectric infrared sensor when a human passes through a recognition area.

[0038] Figure 8 A flowchart illustrating a human movement detection method based on a pyroelectric infrared sensor, provided in an embodiment of the present invention;

[0039] Figure 9 This is a schematic diagram illustrating the change in RSSI value of a moving beacon as a human passes through a recognition area.

[0040] Figure 10 This is a schematic diagram of the structure of a human body detection device provided in an embodiment of the present invention;

[0041] Figure 11 This is a schematic diagram of the structure of a smart device provided in an embodiment of the present invention. Detailed Implementation

[0042] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] Currently, waking up smart devices such as electric toothbrushes relies on active human intervention, such as touch or accelerometer sensors. This method is complex for users, lacks intelligence, and results in a poor user experience. Therefore, this invention provides a human detection method, apparatus, smart device, and computer-readable storage medium that can be used to passively trigger the waking up or entry into working mode of smart devices. Because the smart device can actively sense the user's state, operation is simple and quick, allowing for more intelligent and efficient use of the device, significantly improving the user experience.

[0044] To facilitate understanding of this embodiment, a human body detection method disclosed in this embodiment of the invention will first be described in detail.

[0045] This invention provides a human body detection method, which can be applied to smart devices connected to a photosensor. See also... Figure 1The diagram shows a flowchart of a human body detection method, which mainly includes the following steps:

[0046] Step S102: Obtain the current environmental value and several target environmental values ​​through a photosensitive sensor, and obtain benchmark data based on the several target environmental values, wherein the benchmark data includes limit values ​​and average environmental values.

[0047] The target environmental values ​​can be a preset number of environmental values ​​sampled by the photosensor, or multiple environmental values ​​collected by the photosensor within a preset time period and stable within a preset fluctuation range. The environmental values ​​correspond to the sampled values ​​of the ambient brightness. A photosensor is a sensor that converts light signals into electrical signals (voltage, current, or resistance, etc.); therefore, the sampled values ​​can be resistance, voltage, or current values. The number of target environmental values ​​can be set according to actual needs and is not limited here; for example, 40 target environmental values.

[0048] In some possible embodiments, the aforementioned limit values ​​may include a maximum environmental value and a minimum environmental value, and the baseline data may also include an environmental difference; wherein, the maximum environmental value is the maximum value among several target environmental values, the minimum environmental value is the minimum value among several target environmental values; the average environmental value is the average of the maximum environmental value and the minimum environmental value, and the environmental difference is the difference between the maximum environmental value and the minimum environmental value.

[0049] Step S104: Based on the comparison between the current environmental value and the average environmental value, obtain the first judgment result.

[0050] Considering that when a human passes through the preset recognition area, a shadow may be cast on the sensing area of ​​the photosensitive sensor, causing the ambient value to be lower than the average ambient value, or light may be reflected onto the sensing area, causing the ambient value to be higher than the average ambient value, the current ambient value is compared with the average ambient value to distinguish between the two situations when a human passes through the recognition area.

[0051] Step S106: Determine the target detection result based on the first judgment result, the current environmental value, and the limit value.

[0052] Considering that when a human passes through the preset recognition area, if a shadow is generated in the sensing area of ​​the photosensitive sensor, the environmental value will be less than the minimum environmental value among the limits. If the reflected light is reflected into the sensing area, the environmental value will be greater than the maximum environmental value among the limits. Based on this, the above step S106 can be implemented through the following process: when the first judgment result is that the current environmental value is less than the average environmental value, determine whether the current environmental value is less than the minimum environmental value to obtain the second judgment result; when the first judgment result is that the current environmental value is greater than the average environmental value, determine whether the current environmental value is greater than the maximum environmental value to obtain the third judgment result; based on the second judgment result or the third judgment result, obtain the target detection result.

[0053] Considering the influence of environmental factors, the step of obtaining the target detection result based on the second or third judgment result can be implemented through the following process: When the second judgment result is that the current environmental value is less than the minimum environmental value, it is initially determined that the current situation may be that a human body casts a shadow on the sensing area of ​​the photosensitive sensor, and it is further determined whether the current environmental value meets the first preset condition to obtain the first detection result; when the third judgment result is that the current environmental value is greater than the maximum environmental value, it is initially determined that the current situation may be that a human body reflects light onto the sensing area, and it is further determined whether the current environmental value meets the second preset condition to obtain the second detection result; the target detection result is obtained based on the first or second detection result. The first preset condition corresponds to the influence of environmental factors when a human body casts a shadow on the sensing area of ​​the photosensitive sensor, and the second preset condition corresponds to the influence of environmental factors when a human body reflects light onto the sensing area.

[0054] Considering that the human body may be in the recognition area for an extended period of time, in some possible embodiments, the aforementioned benchmark data may also include the difference between the current environmental value and the average environmental value, and an environmental difference. The difference between the current environmental value and the average environmental value includes a first difference and a second difference. The first difference is the difference obtained by subtracting the current environmental value from the average environmental value when the current environmental value is less than the minimum environmental value. The second difference is the difference obtained by subtracting the average environmental value from the current environmental value when the current environmental value is greater than the maximum environmental value. The aforementioned first preset condition may include: within a preset time period, the number of times the first difference is continuously detected to be greater than the environmental difference is less than a preset number threshold. The aforementioned second preset condition may include: within a preset time period, the number of times the second difference is continuously detected to be greater than the environmental difference is less than a preset number threshold.

[0055] The preset duration and preset number threshold can both be set based on the sampling interval of the photosensitive sensor. For example, when the sampling interval is 100ms, the preset duration can be 3s and the preset number threshold can be 6.

[0056] Considering the impact of environmental changes, in some possible embodiments, the first preset condition further includes: the first value obtained by reducing the average environmental value by a first preset factor is less than or equal to the current environmental value; the second preset condition further includes: the second value obtained by expanding the average environmental value by a second preset factor is greater than or equal to the current environmental value.

[0057] The first and second preset multipliers can be set according to actual conditions, and are not limited here. Preferably, both the first and second preset multipliers are not less than 4, so as to effectively distinguish the changes in ambient light between day and night, or the drastic changes in ambient light intensity caused by switching lights on and off. For example, both the first and second preset multipliers are 4.

[0058] In some possible embodiments, human movement detection can be performed directly based on a photosensitive sensor. That is, when the first detection result is yes or the second detection result is yes, the target detection result is determined to be that human movement has been detected; when the first detection result is no or the second detection result is no, the target detection result is determined to be that human movement has not been detected.

[0059] In other possible embodiments, the smart device is also connected to an auxiliary sensing device, enabling direct human movement detection based on the photosensor and the auxiliary sensing device. That is, the aforementioned human detection method further includes: detecting whether a human body has passed through a preset recognition area using the auxiliary sensing device, obtaining a third detection result; wherein the auxiliary sensing device includes one or more of an image recognition sensor, a pyroelectric infrared sensor, a millimeter-wave human body sensor, and a moving beacon; the target detection result can be determined through the following process: when both the first and third detection results are positive, or when both the second and third detection results are positive, the target detection result is determined to be that human movement has been detected; otherwise, the target detection result is that no human movement has been detected. This human detection method combined with auxiliary sensing devices provides more accurate target detection results.

[0060] Furthermore, when the target detection result is that no human movement is detected, step S102 can be repeated to update the baseline data.

[0061] The human detection method provided in this invention first acquires the current environmental value and several target environmental values ​​using a photosensitive sensor, and then obtains benchmark data based on the target environmental values. The benchmark data includes limit values ​​and average environmental values. Next, a first judgment result is obtained based on the comparison between the current environmental value and the average environmental value. Finally, the target detection result is determined based on the first judgment result, the current environmental value, and the limit values. This method can actively sense human movement with high accuracy, thus simplifying user operation and improving intelligence and user experience when applied to waking up smart devices.

[0062] To facilitate understanding, the following example illustrates the working principle of a human detection method based on a photosensitive sensor, using the conversion of light signals into voltage by a photosensitive sensor: When a human passes through the sensing area of ​​the photosensitive sensor, the brightness of the ambient light detected by the photosensitive sensor changes. This change causes a change in the internal resistance (resistance value) of the photosensitive sensor. This change in internal resistance can be converted into a voltage change by a circuit, and then processed by a corresponding software algorithm to detect the change when a human passes through a certain area (i.e., the preset recognition area).

[0063] See Figure 2The graph shows the relationship between the resistance of the photosensitive sensor and ambient light. The higher the ambient light level (higher lumens), the lower the resistance of the photosensitive sensor. (See also...) Figure 3 The graph shown illustrates the relationship between the sampling voltage of the photosensitive sensor and ambient light. When the ambient light is higher (the higher the lumens), the voltage detected by the photosensitive sensor (sampling voltage) is higher.

[0064] Figure 4 This is a schematic diagram of the sampling voltage change of a photosensitive sensor when a human body passes through a recognition area, provided by an embodiment of the present invention. Figure 5 This is a schematic diagram of the sampling voltage change of a photosensitive sensor when a human body passes through a recognition area, provided as an embodiment of the present invention. The area from A1 to B1 represents the process of a human body passing through the recognition area, where A1 is the instant the human body enters the recognition area and B1 is the instant the human body exits the recognition area. Figure 4 As shown, when a human body passes through, creating a shadow effect (a shadow is generated in the sensing area of ​​the photosensitive sensor when a human body passes through the recognition area), the voltage first decreases, then stabilizes (fluctuating within a certain range), and then increases; as... Figure 5 As shown, when a human body reflects strong light (when a human body passes through the recognition area, the reflected light reaches the sensing area), the voltage first rises, then becomes relatively stable (fluctuating within a certain range), and then falls.

[0065] For ease of understanding, taking the current environmental value as voltage, the preset duration as 3 seconds, the preset number of attempts as 6, and the first and second preset multiples both as 4 as an example, the judgment process for the above first and second preset conditions is as follows:

[0066] If the current ambient value is lower than the average ambient value, it is determined that a human body may have entered (shadow detected). In this case, if the current ambient value is determined to be lower than the minimum ambient value, a flag indicating a valid human body is triggered. After the flag is triggered, a first preset condition is determined: if the difference between the average ambient value and the current ambient value is greater than the ambient difference, enable is triggered, and the valid sensor counter accumulates. If it accumulates 6 times within 3 seconds (indicating continuous triggering of the valid flag, i.e., a human body stays in the recognition area / continuously triggers), the first detection result is determined to be negative, and resampling and updating of the baseline data are required (i.e., the baseline data is corrected); if the number of consecutive increments within 3 seconds is less than 6, and the average ambient value divided by 4 is still greater than the current ambient value (indicating a significant change in the surrounding environment, i.e., it becomes particularly bright), the first detection result is determined to be negative, and resampling and updating of the baseline data are required; if the number of consecutive increments within 3 seconds is less than 6, and the average ambient value divided by 4 is less than or equal to the current ambient value, the first detection result is determined to be positive.

[0067] If the current ambient value is greater than the average ambient value, it is determined that a human body may have entered (light reflection is detected on the photosensitive device). In this case, if the current ambient value is determined to be greater than the maximum ambient value, a flag indicating a valid human body is triggered. After the flag is confirmed to be valid, a second preset condition is determined: if the difference between the current ambient value and the average ambient value is greater than the ambient difference, an enable condition is triggered, and the valid sensor counter accumulates. If it accumulates 6 times consecutively within 3 seconds (indicating continuous triggering of the valid flag, i.e., a human body is staying in the recognition area / continuously triggering), the second detection result is determined to be negative, and resampling and updating of the baseline data are required; if the number of consecutive increments within 3 seconds is less than 6, and the average ambient value multiplied by 4 is still smaller than the current ambient value (indicating a significant change in the surrounding environment, i.e., it has become very dark), the second detection result is determined to be negative, and resampling and updating of the baseline data are required; if the number of consecutive increments within 3 seconds is less than 6, and the average ambient value multiplied by 4 is greater than or equal to the current ambient value, the second detection result is determined to be positive.

[0068] In a specific implementation, taking human movement detection directly based on a photosensitive sensor as an example, see [link to relevant documentation]. Figure 6 The diagram shows another human detection method, which includes the following steps:

[0069] Step S602: Sample 40 environmental values ​​as several target environmental values.

[0070] Step S604: Based on several target environmental values, determine the maximum environmental value E. MAX Minimum environmental value E MIN Average environmental value E A Environmental difference E B .

[0071] Step S606: Obtain the current environment value.

[0072] Step S608: Determine whether the current environmental value is greater than E. A If yes, proceed to step S610; otherwise, proceed to step S626.

[0073] Step S610: Determine if the current environmental value is greater than E. MIN If yes, proceed to step S612; otherwise, repeat step S606.

[0074] Step S612, determine E A Is the difference between this value and the current environmental value greater than E? B If yes, proceed to step S616; otherwise, proceed to step S614.

[0075] In step S614, it is determined that the human body sensor is invalid, and the number of valid attempts is set to 0. Then, step S606 is executed again.

[0076] Step S616: Determine that the human body is being sensed and increment the number of valid attempts by 1.

[0077] Step S618: Determine if the number of valid attempts is greater than or equal to 6. If yes, repeat step S602; otherwise, proceed to step S620.

[0078] Step S620: Determine whether the effective duration of human body sensing reaches 3 seconds. If yes, proceed to step S622; otherwise, repeat step S606.

[0079] Step S622, determine E A Is / 4 greater than the current environment value? If yes, then repeat step S602; if no, then repeat step S624.

[0080] Step S624: Determine the first detection result as "yes" and the target detection result as "human movement detected". End of process.

[0081] Step S626: Determine whether the current environmental value is greater than E. MAX If yes, proceed to step S628; otherwise, repeat step S606.

[0082] Step S628, determine the current environmental value and E A Is the difference greater than E? B If yes, proceed to step S632; otherwise, proceed to step S630.

[0083] In step S630, it is determined that the human body sensor is invalid, and the number of valid attempts is set to 0. Then, step S606 is executed again.

[0084] Step S632: Determine that the human body is being sensed and increment the number of valid attempts by 1.

[0085] Step S634: Determine if the number of valid attempts is greater than or equal to 6. If yes, repeat step S602; otherwise, proceed to step S636.

[0086] Step S636: Determine whether the effective duration of human body sensing reaches 3 seconds. If yes, proceed to step S638; otherwise, repeat step S606.

[0087] Step S638, determine E A Is ×4 less than the current environmental value? If yes, then repeat step S602; if no, then repeat step S640.

[0088] Step S640: Determine the second detection result as yes, and the target detection result as detecting human movement. End of process.

[0089] This human body detection method is low in cost, simple in structure, and easy to perform.

[0090] To facilitate understanding, the above-mentioned auxiliary sensing devices are described below:

[0091] (1) Image recognition sensor: It can recognize human bodies by capturing images with a camera.

[0092] (2) Millimeter-wave human body sensor: It can use short and long waves in the millimeter range with a working frequency of 76-81GHz and a corresponding wavelength of about 1.25mm to detect human movement. The millimeter-wave human body sensor has the advantages of high measurement accuracy, low power consumption, high sensitivity, wide detection range, stable performance and strong anti-interference ability.

[0093] (3) Pyroelectric infrared sensor: When some crystals are heated, equal but opposite charges will be generated at both ends of the crystal. This polarization phenomenon caused by thermal change is called the pyroelectric effect. Pyroelectric infrared sensors are also called PIR (Passive infrared detectors).

[0094] The principle of human movement detection based on pyroelectric infrared sensors is as follows: Normally, the bound charges generated by the spontaneous polarization of a crystal are neutralized by free electrons attached to the crystal surface from the air, and its spontaneous polarization moment cannot be manifested. When the temperature changes, the centers of gravity of positive and negative charges in the crystal structure shift relative to each other, changing the spontaneous polarization. This results in charge depletion on the crystal surface, the degree of which is proportional to the degree of polarization. Pyroelectric infrared sensors can detect infrared radiation emitted by the human body and convert it into an electrical signal output, detecting human movement based on the generated electrical signal.

[0095] Figure 7 The diagram illustrates the voltage change of a pyroelectric infrared sensor when a human body passes through a detection area. The area from A1 to B1 represents the process of a human body passing through the sensing area, with A1 being the instant the human body enters the sensing area and B1 being the instant the human body leaves the sensing area.

[0096] See Figure 8 The diagram shows a flowchart of a human movement detection method based on a pyroelectric infrared sensor. The method includes:

[0097] Step S802: Sample the input AD value of the current input PIR to obtain the current data.

[0098] The raw PIR data is amplified and then subjected to AD sampling conversion.

[0099] Step S804: Perform mean filtering on the current data.

[0100] Step S806: Determine whether the current data remains stable within a certain range within a unit of time. If yes, proceed to step S808; otherwise, proceed to step S810.

[0101] Step S808: Use the current data as the environmental baseline value. Then, re-execute step S802.

[0102] Step S810: Extract the slope and depth of data change per unit time.

[0103] Step S812: Determine whether the slope and change depth meet the preset trigger thresholds. If yes, proceed to step S816; otherwise, proceed to step S814.

[0104] The trigger threshold can be set according to the actual situation; no limit is set here.

[0105] Step S814: Determine that no human movement has been detected. Then, repeat step S802.

[0106] Step S816: Confirm that human movement has been detected. Process ends.

[0107] The human movement detection method based on pyroelectric infrared sensors is stable and has sensitive triggering.

[0108] (4) Mobile beacon: refers to a low-power electronic device that uses Bluetooth, NFC (Near Field Communication) or other low-power radio technologies to measure the distance between nodes by detecting RSSI (Received Signal Strength Indication).

[0109] This can be achieved by utilizing the Bluetooth or Wi-Fi modules within smart devices to detect the proximity of Bluetooth or Wi-Fi modules on mobile terminals such as smartphones. See also Figure 9The diagram illustrates the change in RSSI value of a moving beacon when a human passes through a detection area. The closer the distance, the higher the RSSI value. Taking a Bluetooth module as an example, the principle of human movement detection based on moving beacons is as follows: The Bluetooth module of a mobile phone and the Bluetooth module of a smart device pair and connect. The mobile phone's Bluetooth module generates a random broadcast name and synchronizes the broadcast name to the Bluetooth module of the smart device. When the connection is broken, the mobile phone's Bluetooth module broadcasts a Bluetooth name N1. When a user's mobile phone with a Bluetooth module approaches a smart device such as a toothbrush, the toothbrush's Bluetooth module actively scans the mobile phone's RSSI value. Based on the change in the RSSI value corresponding to the specific broadcast name N1, it determines whether a human has passed by, and can then wake up or turn on the smart device.

[0110] Corresponding to the above-described human body detection method, this embodiment of the invention also provides a human body detection device. See [link to related documentation]. Figure 10 The diagram shown illustrates the structure of a human body detection device, which includes:

[0111] The data acquisition module 1002 is used to acquire the current environmental value and several target environmental values ​​through a photosensitive sensor, and to obtain benchmark data based on the several target environmental values, wherein the benchmark data includes limit values ​​and average environmental values;

[0112] The comparison and judgment module 1004 is used to obtain a first judgment result based on the comparison result between the current environmental value and the average environmental value;

[0113] The target detection module 1006 is used to determine the target detection result based on the first judgment result, the current environmental value, and the limit value.

[0114] The human detection device provided in this embodiment of the invention first acquires the current environmental value and several target environmental values ​​through a photosensitive sensor during human detection. Based on these target environmental values, it obtains benchmark data, which includes limit values ​​and average environmental values. Then, based on the comparison between the current environmental value and the average environmental value, a first judgment result is obtained. Finally, based on the first judgment result, the current environmental value, and the limit values, the target detection result is determined. This method can actively sense human movement with high accuracy, thus simplifying user operation and improving intelligence and user experience when applied to waking up smart devices.

[0115] Furthermore, the aforementioned limit values ​​include the maximum environmental value and the minimum environmental value; the target detection module 1006 is specifically used for:

[0116] When the first judgment result is that the current environmental value is less than the average environmental value, the second judgment result is obtained by judging whether the current environmental value is less than the minimum environmental value.

[0117] When the first judgment result is that the current environmental value is greater than the average environmental value, the third judgment result is obtained by judging whether the current environmental value is greater than the maximum environmental value.

[0118] The target detection result is obtained based on the second or third judgment result.

[0119] Furthermore, the aforementioned target detection module 1006 is also used for:

[0120] When the second judgment result is that the current environmental value is less than the minimum environmental value, it is determined whether the current environmental value meets the first preset condition, and the first detection result is obtained.

[0121] When the third judgment result is that the current environmental value is greater than the maximum environmental value, it is determined whether the current environmental value meets the second preset condition, and the second detection result is obtained.

[0122] The target detection result is obtained based on the first or second detection result.

[0123] Furthermore, the aforementioned benchmark data also includes the difference between the current environmental value and the average environmental value, and the environmental difference, wherein the difference between the current environmental value and the average environmental value includes a first difference and a second difference;

[0124] The first preset condition includes: within a preset time period, the number of times the first difference is detected to be greater than the environmental difference is less than a preset number threshold.

[0125] The second preset condition includes: within a preset time period, the number of times the second difference is detected to be greater than the environmental difference is less than a preset number threshold.

[0126] Furthermore, the preset duration includes 3 seconds, and the preset number of times threshold includes 6.

[0127] Furthermore, the first preset condition also includes: the first value obtained by reducing the average environmental value by a first preset factor is less than or equal to the current environmental value;

[0128] The second preset condition also includes: the second value obtained by multiplying the average environmental value by a second preset factor is greater than or equal to the current environmental value.

[0129] Furthermore, both the first preset multiple and the second preset multiple mentioned above are not less than 4.

[0130] The human body detection device provided in this embodiment has the same implementation principle and technical effect as the aforementioned human body detection method embodiment. For the sake of brevity, any parts not mentioned in the human body detection device embodiment can be referred to the corresponding content in the aforementioned human body detection method embodiment.

[0131] like Figure 11As shown in the figure, an intelligent device 1100 provided in this embodiment of the invention includes: a processor 1101, a memory 1102, a photosensor 1103, and a bus. The photosensor 1103 is connected to the memory 1102 and is used to store collected environmental value data in the memory 1102. The memory 1102 stores a computer program that can run on the processor 1101. When the intelligent device 1100 is running, the processor 1101 and the memory 1102 communicate via the bus. When the processor 1101 executes the computer program, it implements the aforementioned human body detection method. The environmental value data includes the current environmental value and several target environmental values.

[0132] Specifically, the memory 1102 and processor 1101 mentioned above can be general-purpose memory and processor, without any specific limitations here.

[0133] Furthermore, the aforementioned intelligent device 1100 may also include an auxiliary sensing device connected to the memory 1102. The auxiliary sensing device may include one or more of the following: an image recognition sensor, a pyroelectric infrared sensor, a millimeter-wave human body sensor, and a mobile beacon. The auxiliary sensing device can store the detected sensing data in the memory 1102. When the processor 1101 executes the computer program, it processes the sensing data in the memory 1102 to obtain a third detection result, and then determines the target detection result.

[0134] The aforementioned human detection method can be applied to the wake-up recognition of the smart device 1100. Taking the smart device 1100 as an electric toothbrush as an example, it can specifically include the following aspects:

[0135] ① Wake-up function of the electric toothbrush screen or special indicator:

[0136] Features include electric toothbrush screen wake-up, effect display, electric toothbrush access and power-on, welcome prompt, and different toothbrush identifiers for different users.

[0137] ② Bluetooth quick broadcast or near-field Bluetooth on electric toothbrushes:

[0138] When a person approaches the electric toothbrush, the toothbrush uses a fast Bluetooth broadcast to allow mobile devices such as smartphones to connect to the toothbrush more quickly.

[0139] When a person gets close to the electric toothbrush, a device pop-up window can be displayed on the user's mobile phone via a near-field broadcast, prompting the user to connect the electric toothbrush, etc.

[0140] ③ Electric toothbrush reminder (after connecting the electric toothbrush to the mobile app, a reminder will be displayed on the mobile app):

[0141] The device will display a warning when the remaining days for the brush head are too low.

[0142] The device will display a warning when the battery level is low.

[0143] The device will remind you when it's time to brush your teeth.

[0144] This invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the human detection method described in the preceding method embodiments. The computer-readable storage medium includes various media capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), RAM, magnetic disk, or optical disk.

[0145] In all the examples shown and described here, any specific values ​​should be interpreted as merely examples.

[0146] This is not a limitation, and therefore other examples of the exemplary embodiments may have different values ​​of 5.

[0147] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of methods and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable 0 instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may also be...

[0148] The events may occur in a different order than those shown in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the block diagram and / or flowchart...

[0149] The combination of boxes in the diagram can be implemented using a dedicated hardware-based system that performs the specified functions or actions, or it can be implemented using a combination of dedicated hardware and computer instructions.

[0150] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and other methods may be used in actual implementation.

[0151] The division method, for example, allows multiple units or components to be combined or integrated into another system, or some features to be ignored or not executed. Another point is that the coupling or direct coupling or communication connection shown or discussed can be indirect coupling or communication connection through some communication interface, device, or unit, and can be electrical, mechanical, or other forms.

[0152] The unit described as a separate component may or may not be physically separate.

[0153] The components displayed as units may or may not be physical units; that is, they may be located in one location or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0154] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0155] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for human body detection, characterized in that, The human detection method, applicable to smart devices including electric toothbrushes, includes: A photosensitive sensor acquires the current environmental value and several target environmental values, and benchmark data is obtained based on the target environmental values. The benchmark data includes limit values ​​and average environmental values. The limit values ​​include a maximum environmental value and a minimum environmental value. The average environmental value is the average of the maximum and minimum environmental values. The benchmark data also includes the difference between the current environmental value and the average environmental value, and an environmental difference. The difference between the current environmental value and the average environmental value includes a first difference or a second difference. The first difference is the difference obtained by subtracting the current environmental value from the average environmental value when the current environmental value is less than the minimum environmental value. The second difference is the difference obtained by subtracting the average environmental value from the current environmental value when the current environmental value is greater than the maximum environmental value. The environmental difference is the difference between the maximum and minimum environmental values. Based on the comparison between the current environmental value and the average environmental value, a first judgment result is obtained; Based on the first judgment result, the current environmental value, and the limit value, the target detection result is determined; The step of determining the target detection result based on the first judgment result, the current environmental value, and the limit value includes: When the first judgment result is that the current environmental value is less than the average environmental value, it is determined whether the current environmental value is less than the minimum environmental value to obtain a second judgment result; when the second judgment result is that the current environmental value is less than the minimum environmental value, it is determined whether the current environmental value meets a first preset condition to obtain a first detection result; wherein, the first preset condition includes: within a preset time period, the number of times the first difference is detected to be greater than the environmental difference is less than a preset number threshold, and the first value obtained by reducing the average environmental value by a first preset factor is less than or equal to the current environmental value; When the first judgment result is that the current environmental value is greater than the average environmental value, it is determined whether the current environmental value is greater than the maximum environmental value to obtain a third judgment result; when the third judgment result is that the current environmental value is greater than the maximum environmental value, it is determined whether the current environmental value meets a second preset condition to obtain a second detection result; wherein, the second preset condition includes: within a preset time period, the number of times the second difference is continuously detected to be greater than the environmental difference is less than the preset number threshold, and the second value obtained by expanding the average environmental value by a second preset multiple is greater than or equal to the current environmental value; The target detection result is obtained based on the first detection result or the second detection result.

2. The human body detection method according to claim 1, characterized in that, The preset duration includes 3 seconds, and the preset number of times threshold includes 6.

3. The human body detection method according to claim 1, characterized in that, Both the first preset multiple and the second preset multiple are not less than 4.

4. A human body detection device, characterized in that, The human body detection device, applicable to smart devices including electric toothbrushes, comprises: A data acquisition module is used to acquire current environmental values ​​and several target environmental values ​​through a photosensitive sensor, and to obtain benchmark data based on the several target environmental values. The benchmark data includes limit values ​​and average environmental values. The limit values ​​include a maximum environmental value and a minimum environmental value. The average environmental value is the average of the maximum environmental value and the minimum environmental value. The benchmark data also includes the difference between the current environmental value and the average environmental value, and an environmental difference. The difference between the current environmental value and the average environmental value includes a first difference or a second difference. The first difference is the difference obtained by subtracting the current environmental value from the average environmental value when the current environmental value is less than the minimum environmental value. The second difference is the difference obtained by subtracting the average environmental value from the current environmental value when the current environmental value is greater than the maximum environmental value. The environmental difference is the difference between the maximum environmental value and the minimum environmental value. The comparison and judgment module is used to obtain a first judgment result based on the comparison result between the current environmental value and the average environmental value; The target detection module is used to determine the target detection result based on the first judgment result, the current environmental value, and the limit value; The target detection module is specifically used for: When the first judgment result is that the current environmental value is less than the average environmental value, it is determined whether the current environmental value is less than the minimum environmental value to obtain a second judgment result; when the second judgment result is that the current environmental value is less than the minimum environmental value, it is determined whether the current environmental value meets a first preset condition to obtain a first detection result; wherein, the first preset condition includes: within a preset time period, the number of times the first difference is detected to be greater than the environmental difference is less than a preset number threshold, and the first value obtained by reducing the average environmental value by a first preset factor is less than or equal to the current environmental value; When the first judgment result is that the current environmental value is greater than the average environmental value, it is determined whether the current environmental value is greater than the maximum environmental value to obtain a third judgment result; when the third judgment result is that the current environmental value is greater than the maximum environmental value, it is determined whether the current environmental value meets a second preset condition to obtain a second detection result; wherein, the second preset condition includes: within a preset time period, the number of times the second difference is continuously detected to be greater than the environmental difference is less than the preset number threshold, and the second value obtained by expanding the average environmental value by a second preset multiple is greater than or equal to the current environmental value; The target detection result is obtained based on the first detection result or the second detection result.

5. A smart device, comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the human body detection method according to any one of claims 1-3.

6. A computer-readable storage medium storing a computer program thereon, characterized in that, The computer program is executed by the processor to perform the steps of the human body detection method according to any one of claims 1-3.

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