Sensor device and method for evaluating the effects of airflow

Abstract

A sensor device (100) and a method (800) for assessing the effect of air flow on sensor data are provided. The sensor device receives sensor data S d a thermal sensor (130) for detecting the airflow (170) and audio data A generated from the airflow (170) d The system includes a microphone (150) for sensing the thermal sensor and a processor (200) coupled to the thermal sensor and the microphone, the processor obtaining sensed sensor data and sensed audio data, and determining at least one characteristic P of the air flow based on the obtained audio data. i and estimating at least one correlation criterion C between the sensor data and the audio data. c At least one characteristic P of the air flow to the sensor data based on i Impact level L f The method is configured to estimate

Description

[Technical Field]

[0001] The present invention generally relates to sensor devices and methods for evaluating the effects of airflow. In particular, the present invention relates to sensor devices and methods capable of detecting "false" triggers caused by airflow(s). [Background technology]

[0002] In the prior art, there are many devices and systems that include one or more sensors capable of detecting the presence and / or movement of a person. These types of devices are widely used in all kinds of spaces, such as offices and homes, to switch lights on (or off) when one or more people enter the space.

[0003] However, if not placed carefully, these (sensor) devices may react to "false" triggers, such as switching on lights even when no one is in the space and / or is not present. For example, if the device is placed near heating, ventilation, and air conditioning (HVAC) vents, false triggers due to airflow are likely to occur. That said, it should be noted that this cannot always be prevented, especially in offices, due to factors such as existing HVAC infrastructure, desk position(s), and lighting grids. [Overview of the project] [Problems that the invention aims to solve]

[0004] Therefore, it is desirable to provide a device and method that may be able to register sensor data (such as the presence and / or movement of one or more people), and that can evaluate the influence of airflow(s) on sensor data in order to detect, for example, false triggers in sensor data.

[0005] The object of the present invention is to provide a device and method capable of detecting sensor data and evaluating the influence of the airflow(s) present on the sensor data. [Means for solving the problem]

[0006] These and other objectives are achieved by providing sensor devices and methods having the features of the independent claims. Preferred embodiments are defined in the dependent claims.

[0007] Therefore, according to a first aspect of the present invention, a sensor device is provided for evaluating the influence of airflow on sensor data. The sensor device receives sensor data S d A thermal sensor to detect and audio data A generated from airflow d The system includes a microphone for detecting and a processor connected to a thermal sensor and microphone. The processor obtains the detected sensor data and detected audio data, and, based on the obtained audio data, determines at least one characteristic P of the airflow. i The processor is configured to estimate at least one correlation criterion C between sensor data and audio data. c Based on this, at least one characteristic P of the airflow to the sensor data i Influence level L f It is configured to estimate.

[0008] A second aspect of the present invention provides a method for evaluating the influence of airflow on sensor data. The method includes the steps of detecting sensor data, detecting audio data generated from the airflow, obtaining the detected sensor data and the detected audio data, and determining at least one characteristic P of the airflow based on the obtained audio data. i The method further includes the step of estimating a correlation criterion C between sensor data and audio data. cBased on this, at least one characteristic P of the air flow on the sensor data i and the level of influence L f including the step of estimating.

[0009] Thus, the present invention is based on the idea of evaluating the influence of air flow on sensor data, and by extension, can reveal the "false" triggers of sensor data (e.g., presence and / or motion sensor data) caused by air flow. The sensor device estimates one or more characteristics P of the air flow from audio data (i.e., sound), and accordingly, one or more correlations C i between the detected sensor data and the audio data are used to estimate the influence of the air flow on the sensor data. Therefore, the present invention efficiently uses audio data, sensor data, and their correlation relationship C c (s) in the evaluation of the influence of air flow on sensor data. i (plural possible) in the evaluation of the influence of air flow on sensor data.

[0010] The present invention is advantageous in that the sensor device is particularly effective in detecting air flow and estimating its influence on sensor data. Thus, the sensor device is efficient in detecting and / or recognizing false triggers of sensor data (i.e., air flow can potentially affect sensor data such that, for example, the (false) presence / motion of a person (s) can be triggered from the air flow even when no person (s) is present in the space). The sensor device is particularly advantageous when the space or room includes heating, ventilation, and air conditioning (HVAC) outlets. This is because the air flow from these configurations can cause "false triggers" in the sensor data. By evaluating the impact or influence of air flow on sensor data, the sensor device can conveniently and efficiently contribute to the management or processing of sensor data, for example, to compensate for and / or ignore a part of the sensor data.

[0011] The present invention is further advantageous in that the ability of the sensor device to estimate the influence of airflow on sensor data, for example, the consequent ability to more accurately determine whether there is a person present in a space or room, leads to improved energy efficiency and / or avoidance of unintended lighting. For example, if there is no person present in a space or room, but airflow is generated and / or present in the space or room, the evaluation by the sensor device can be used by the lighting system or configuration coupled to the sensor device to control the lighting accordingly (e.g., keep the lights off). In other words, airflow(s) that trigger a “false” motion event could lead to a lighting system or configuration inadvertently turning on a light(s) even though the space or room is non-occupied, but the present invention prevents this situation.

[0012] The present invention is further advantageous in that the sensor device comprises relatively few components, which has several beneficial effects. For example, the present invention offers advantages such as easy installation, inconspicuousness (due to its relatively small size), and a structure that is less prone to malfunction.

[0013] A sensor device for evaluating the influence of airflow on sensor data according to a first aspect of the present invention is provided, which receives sensor data S dThe sensor device includes a thermal sensor for detecting airflow. Here, “thermal sensor” means substantially any thermal sensor, such as a passive infrared (PIR) sensor, an infrared (IR) sensor, a thermopile sensor, etc. Thus, “sensor data” means data detected by the thermal sensor, and the sensor data may be generated from, for example, a moving person, a moving fan, and / or a combination thereof. The sensor device further includes a microphone for detecting audio data generated from the airflow. Thus, the microphone of the sensor device detects audio data generated by the airflow, for example, in the form of noise. The sensor device further includes a processor connected to the sensor and microphone, the processor configured to obtain the detected sensor data and the detected audio data. Thus, the processor, which may be connected to the sensor and microphone by wireless or wired connection, acquires or receives the detected sensor data and the audio data. Based on the obtained audio data, the processor determines at least one characteristic P of the airflow i It is configured to estimate one or more characteristics of the airflow present, P i The processor is configured to estimate the following. The term "property" means substantially any characteristic or feature of the airflow, such as the magnitude (size, amplitude, or intensity) of the airflow. The processor further includes at least one correlation criterion C between the sensor data and the audio data. c Based on this, at least one characteristic P of the airflow to the sensor data i Influence level L f The processor is configured to estimate one or more correlation criteria C between sensor data and audio data. c Based on this, the characteristics of the airflow to the sensor data (multiple characteristics possible) P i Influence level L f , in other words, the characteristics of airflow (multiple characteristics possible) P iIt is configured to estimate the degree or extent to which it affects the sensor data. "Correlation criterion" means a substantially arbitrary criterion regarding the interrelationship and / or connection between the sensor data and the audio data. The correlation criterion may be predetermined. The correlation criterion may be stored in memory or on the processor.

[0014] According to one embodiment of the present invention, audio data A d This may include an audio spectrogram of amplitude as a function of frequency. Therefore, audio data A generated from airflow d This is audio data A d The amplitude of audio data A d It may include a (frequency) spectrogram, which is a function of frequency. Audio data A d The spectrogram may show one or more characteristics Pi of the airflow, and this embodiment is configured such that the processor has these characteristics P i It may be configured to infer and / or estimate the sensor data S d Characteristics (multiple possible) of P i Influence level L f It should be noted that this is advantageous in improving estimation. For example, a spectrogram may show the magnitude of airflow, and the processor may be configured to infer and / or estimate the magnitude of airflow based on the spectrogram. Therefore, in this embodiment, the sensor device receives sensor data S d This is advantageous because it allows for efficient evaluation of the effects of airflow on the system.

[0015] According to one embodiment of the present invention, at least one characteristic P i This may include the magnitude of the airflow. Here, "magnitude" refers to the size, degree, intensity, and velocity of the airflow. The magnitude of a relatively large airflow is measured using sensor data S. dIt should be noted that this embodiment has the advantage of being able to improve the efficiency of detecting and / or recognizing false triggers in sensor data, which could have a significant impact. For example, when the processor estimates a relatively small magnitude of airflow, the processor uses sensor data S d The relatively low or limited level of influence of airflow to L f It may be estimated that... In contrast, if the processor estimates a relatively large magnitude of airflow, the processor will use sensor data S d Relatively large or significant level of influence of airflow to L f It is also possible to estimate this.

[0016] In one embodiment, the thermal sensor may have a setting for detecting the movement of at least one object in space, and the processor receives sensor data S d At least one characteristic P of the airflow to i Estimated impact level L f The settings may be configured to adapt based on the above. The settings may be, for example, the sensitivity of the thermal sensor. If the estimated impact level exceeds a predetermined threshold, the processor may control the thermal sensor to reduce its sensitivity.

[0017] For example, in one embodiment, the thermal sensor may have sensing sensitivity, and the processor may be configured to control the thermal sensor to reduce the sensitivity if the estimated influence level of at least one characteristic exceeds a predetermined threshold.

[0018] The aforementioned setting may, for example, be the detection mode for a thermal sensor.

[0019] For example, if the estimated impact level exceeds a predetermined threshold, the processor may control the thermal sensor to turn off detection, i.e., to operate in non-detecting detection mode, and / or, if the estimated impact level falls below a predetermined threshold, the processor may control the thermal sensor to continue detection, i.e., to operate in detecting detection mode, i.e., to turn on detection.

[0020] For example, in a different embodiment, the processor is configured to control the thermal sensor to stop detecting sensor data, temporarily stop detecting sensor data, or stop sensing altogether if the estimated influence level of at least one characteristic exceeds a predetermined threshold.

[0021] Such embodiments reduce false triggers because the thermal sensor is either off or has reduced sensitivity, and therefore will not be falsely triggered by detected airflow, such as that provided by HVAC.

[0022] According to one embodiment of the present invention, the sensor device further includes at least one element comprising at least one of an opening, a cavity, and a recess, configured to generate an audible resonance with respect to airflow, and the resulting audio data may include an audible resonance. Thus, the element(s) of the sensor device can generate an audible resonance with respect to airflow by standing waves in the opening, cavity, and / or recess. In this embodiment, the sensor device may use one or more characteristics of airflow as a function of the characteristics of the audible resonance, such as the magnitude of the airflow. i This is advantageous in that it can be conveniently detected. As a result, this is the sensor data S from the sensor device. d Level L of the influence of airflow on the airflow f This will lead to even better estimations.

[0023] According to one embodiment of the present invention, the sensor device further generates first vibration data V from the airflow d1 The system includes a first accelerometer for detecting vibrations, and the processor is connected to the first accelerometer and the detected first vibration data V d1 The processor may be configured to obtain the sensor data and the first vibration data V d1 at least one correlation criterion C between d Based on the sensor data S d At least one characteristic P of the airflow to i Influence level L f The sensor device is configured to estimate the first vibration data V that is detected from the airflow. d1 It is advantageous in that it can conveniently detect one or more characteristics of the airflow based on this. As a result, sensor data S d Characteristics of airflow to P (multiple selections possible) i Influence level L f Further improved estimation can be achieved by sensor devices.

[0024] According to one embodiment of the present invention, the processor further processes the obtained audio data A d The processor is configured to determine the operation of at least one fan based on the sensor data S. d at least one correlation criterion C between and the operation of at least one fan c2 Based on the sensor data S d Level L of the influence of airflow on the airflow f The sensor device is configured to estimate the level of influence L of the airflow characteristics (which can be multiple) on the sensor data. f This may be estimated. In this embodiment, sensor data S as a result of air fan operation d This is advantageous in that it may be possible to achieve a more accurate estimation of the effect of airflow on it.

[0025] According to one embodiment of the present invention, the sensor device further generates magnetic data M from the operation of at least one fan. d The processor may include a magnetometer for detecting magnetic fields, and the processor may be connected to the magnetometer and configured to obtain detected magnetic data. The processor may further include at least one correlation criterion C between the sensor data and the magnetic data. e Based on the sensor data S d Level L of influence of at least one characteristic of the airflow to f The system is configured to estimate the following. Therefore, the processor may determine the operation of one or more fans, and since the operating fan(s) can generate a magnetic field, the sensor device may estimate the effect of airflow on the sensor data based on the correlation between the sensor data and the magnetic data. Thus, in addition to the correlation between the sensor data and the audio data, the correlation between the sensor data and the magnetic data is also considered by the sensor device when estimating the effect of airflow on the sensor data. This embodiment is advantageous in that the sensor device can achieve a more accurate estimation of the effect of airflow on the sensor data.

[0026] According to one embodiment of the present invention, the sensor device further includes a first temperature sensor for detecting temperature data, the first temperature sensor being located within a predetermined distance d1 from a thermal sensor and connected to a processor. The processor further obtains the detected temperature data and, based on the obtained temperature data, generates sensor data S d At least one characteristic P of the airflow to i Influence level L f It is configured to estimate the following. The expression "arranged within a predetermined distance, d1" here means within a relatively small distance d1 or radius from the thermal sensor. Therefore, the first temperature sensor may detect the temperature of the sensor device, or at least the temperature near the sensor device, which is correlated with the ambient temperature. This embodiment uses sensor data Sd Characteristics of airflow to P (multiple selections possible) i Influence level L f It is advantageous in terms of a more accurate estimation.

[0027] According to one embodiment of the present invention, the sensor device further includes a second temperature sensor for detecting ambient temperature data, the second temperature sensor being located beyond a predetermined distance d2 from the thermal sensor and connected to a processor. The processor further obtains the detected ambient temperature data and, based on the obtained ambient temperature data, generates sensor data S d At least one characteristic P of the airflow to i Influence level L f It is configured to estimate the following. The expression "arranged beyond a predetermined distance, d2" here means beyond a relatively large distance d2 or radius from the thermal sensor. Therefore, in addition to audio data and sensor data, the processor of the sensor device estimates the sensor data S d (Ambient) temperature data may also be considered to estimate the effect of airflow on the temperature. For example, it may be assumed or expected that airflow will affect the temperature (e.g., by temperature rise, fall, and / or fluctuation). This embodiment describes the characteristics of the airflow P i A more accurate decision can be achieved, and as a result, the sensor device of the present invention can determine the sensor data S d Characteristics of airflow to P (multiple selections possible) i This is advantageous in that it leads to a more accurate estimation of the effects.

[0028] According to one embodiment of the present invention, a sensor arrangement is provided for detecting the movement of at least one object in space, the sensor arrangement comprising a sensor device according to any of the preceding embodiments. The processor further provides sensor data S d At least one characteristic P of the airflow to i Estimated impact level L fconfigured to detect the movement of at least one object in space. The term "object" here usually means one or more persons. This embodiment is particularly advantageous in terms of detecting "false" triggers of sensor data (e.g., presence and / or movement sensor data of the object(s)) due to air flow. For example, sensor data S d to the characteristic(s) P of the air flow i to the estimated impact level L f is relatively high, the sensor device may estimate or determine that the possibility of the presence or movement of an object (person) in the space is relatively low. In contrast, for sensor data S d to the characteristic(s) P of the air flow i to the estimated impact level L f is relatively low, the sensor device may estimate or determine that the likelihood of an object(s) (person(s)) in the space is high.

[0029] According to an embodiment of the present invention, a sensor configuration including at least one fan is provided, and audio data A d is further generated from audible sounds caused by the operation of at least one fan.

[0030] According to an embodiment of the present invention, the sensor configuration further includes a second accelerometer for detecting second vibration data V d2 generated from at least one fan, the processor is connected to the second accelerometer and is configured to obtain the detected second vibration data V d2 and the processor is further based on at least one correlation criterion C d between the sensor data S d2 and the second vibration data V g to the at least one characteristic P of the air flow d to the impact level L i of the air flow fIt may be configured to estimate the following: Thus, the fan(s) may generate vibrations during operation, which may be detected by a second accelerometer, for example, via the ceiling, and the processor uses sensor data S based on these vibrations. d It may be configured to estimate the effect of airflow on the first vibration data V generated from the airflow. d1 A first accelerometer for detecting and a second vibration data V generated from the fan(s) d2 The second accelerometer for detecting the magnetic field may be a different accelerometer, or alternatively, a single accelerometer may be configured. When the (second) accelerometer of this embodiment is combined with a magnetometer embodiment of the sensor device, it should be noted that vibrations causing vibration / movement of the fan(s) may cause a fluctuating magnetic field relative to the stationary magnetic field.

[0031] According to one embodiment of the present invention, the sensor configuration further includes a microphone and a storage medium connected to a processor, the storage medium being configured to store detected audio data. The processor is configured to determine the disrupted operation of at least one fan based on the stored audio data. In this embodiment, the sensor configuration can detect a malfunction and / or breakdown of a fan(s), and this information is used by the sensor configuration to determine the characteristics of one or more airflows to the sensor data P i It is advantageous in that it can be used in estimating the effects of [the phenomenon].

[0032] According to one embodiment of the present invention, a lighting system is provided which includes at least one light source and a sensor configuration according to one or more of the preceding embodiments. The sensor device is connected to at least one light source, and the sensor device receives sensor data S d At least one characteristic P of the airflow to i Estimated impact level L fThe system is configured to operate at least one light source based on the movement of at least one object in the space detected based on the sensor data S. d At least one characteristic P of the airflow to i Relatively high estimated impact level L f The evaluation by the sensor device may be used by the lighting system to appropriately control the lighting (e.g., to keep the lights off). In other words, airflow(s) that trigger a “false” motion event may lead to the lighting system or configuration inadvertently turning on the lights(s) even though the space or room is not occupied.

[0033] Further objects, features, and advantages of the present invention will become apparent upon consideration of the following detailed disclosure, drawings, and appended claims. Those skilled in the art will recognize that various features of the present invention can be combined to produce embodiments other than those described below. [Brief explanation of the drawing]

[0034] Herein, this and other aspects of the present invention will be described in more detail with reference to the accompanying drawings illustrating (multiple) embodiments of the present invention. [Figure 1a] Figure 1a schematically shows a sensor device according to an exemplary embodiment of the present invention. [Figure 1b] Figure 1b schematically shows the operation of a sensor device according to an exemplary embodiment of the present invention. [Figure 1c] Figure 1c schematically shows a sensor device according to an exemplary embodiment of the present invention. [Figure 2] Figures 2a and 2b schematically show the correlation between sensor data and audio data according to exemplary embodiments of the present invention. [Figure 3]Figures 3a to 3f schematically show the correlations according to exemplary embodiments of the present invention. [Figure 4] Figure 4 schematically shows a lighting system according to an exemplary embodiment of the present invention. [Figure 5] Figure 5 schematically shows a method according to an exemplary embodiment of the present invention. [Modes for carrying out the invention]

[0035] Figure 1a schematically shows a sensor device 100 according to an exemplary embodiment of the present invention. The characteristics of the sensor device 100 in Figure 1a, such as the arrangement of its components, format apportionment, size, etc., are provided for illustrative purposes only, and it should be understood that the disclosed sensor device 100 constitutes only one example. The sensor device 100 includes a thermal sensor 130 for detecting sensor data, which may arise from, for example, a moving person, a moving fan, and / or a combination thereof. Although only a single thermal sensor 130 is shown, it should be understood that the sensor device 100 may alternatively include multiple thermal sensors 130. The thermal sensor 130 may be, for example, a passive infrared (PIR) sensor, an infrared (IR) sensor, a thermopile sensor, etc., or may include these. The thermopile sensor may be a single-element thermopile sensor or a multi-element (array / matrix) thermopile sensor. The sensor device 100 is preferably positioned in a space or room such that the thermal sensor 130 can conveniently detect its sensor data in the space or room. The sensor device 100 further includes a microphone 150 for detecting audio data. Although only a single microphone 150 is shown, it should be understood that the sensor device 100 may alternatively include multiple microphones 150. The audio data may be in the form of noise generated by, for example, an airflow 170, the airflow 170 in Figure 1a being exemplified as an airflow 170 generated by a fan or HVAC outlet 180 during operation. However, it should be understood that the airflow 170 may be generated from substantially any other elements and / or circumstances, such as a window and / or door being slightly open, and / or a window and / or door being opened. The audio data may include, for example, a spectrogram of amplitude as a function of frequency. Thus, the audio data generated from the airflow 170 may include a (frequency) spectrogram in which the amplitude of the audio data is a function of the frequency of the audio data.

[0036] The sensor device 100 further includes a processor 200 connected to a thermal sensor 130 and a microphone 150. While the processor 200 is only schematically shown by a dashed line in Figure 1a, it should be noted that the processor 200 may be integrated into the sensor device 100, or alternatively, located remotely from the housing of the sensor device 100. Therefore, the processor 200 may be connected to the sensor 130 and microphone 150 by wireless or wired connection.

[0037] Figure 1b schematically shows the operation of the sensor device 100 illustrated in Figure 1a according to an exemplary embodiment of the present invention. In the leftmost portion of Figure 1b, sensor data S detected by the thermal sensor 130 is shown. d and audio data A detected by microphone 150 d However, it is acquired or received by processor 200. The resulting audio data A d Based on this, the processor 200 determines at least one characteristic P of the airflow i It is configured to estimate the following. For example, the processor 200 may be configured to estimate the magnitude (size, intensity) of the airflow. The processor 200 further uses sensor data S d and audio data A d at least one correlation criterion C between c Based on the sensor data S d At least one characteristic P of the airflow to i Influence level L f The processor 200 is configured to estimate one or more airflow characteristics P. i Estimate the sensor data S d and audio data A d One or more correlation criteria C between c Based on the sensor data S d Characteristics of airflow to P (multiple selections possible) i Influence level L f , in other words, the characteristics of airflow (multiple characteristics possible) P iSensor data S d To estimate the extent of the impact. Audio data A d However, if the spectrogram includes amplitude as a function of frequency, the spectrogram will show one or more characteristics P of the airflow 170. i This can be shown, and thereby the processor 200 can process the sensor data S d Characteristics (multiple possible) of P i Influence level L f For estimation of these (these) properties P i The processor 200 may be configured to infer and / or estimate the magnitude of the airflow 170. For example, the spectrogram may show the magnitude of the airflow 170, and the processor 200 may be configured to infer and / or estimate the magnitude of the airflow 170 based on the spectrogram.

[0038] Figure 1c schematically shows a sensor device 100 according to an exemplary embodiment of the present invention. Note that the sensor device 100 in Figure 1c has many features in common with the sensor device 100 illustrated in Figure 1a and the associated text, and with its operation illustrated in Figure 1b and the associated text; refer to this text and / or figure for better understanding. The sensor device 100 in Figure 1c further includes a first temperature sensor 300 for detecting temperature data. The first temperature sensor 300 is illustrated to be located in the housing of the sensor device 100. Alternatively, the first temperature sensor 300 may be located within a predetermined distance d1 from the thermal sensor 130. Thus, the processor 200 obtains temperature data detected by the first temperature sensor 300 and, based thereon, sensor data S d At least one characteristic P of the airflow to i Influence level L fThe sensor device 100 may further include a second temperature sensor 310 for detecting ambient temperature data, the second temperature sensor 310 may be positioned beyond a (second) predetermined distance d2 from the thermal sensor 130. This allows the processor 200 to obtain the detected ambient temperature data and, based thereon, the sensor data S d At least one characteristic P of the airflow to i Influence level L f It may be configured to estimate the temperature. If the sensor device 100 has a first temperature sensor 300 and a second temperature sensor 310, the first temperature sensor 300 may be located near the thermal sensor 310, and the second temperature sensor 310 may be located remotely from the thermal sensor 310 such that d2 >> d1.

[0039] The sensor device 100 in Figure 1c further includes a microphone 150 and a storage medium 620 connected to a processor 200. The storage medium 620 is configured to store detected audio data, and the processor 200 is configured to determine a fan(s) malfunction based on the stored audio data.

[0040] Figure 2a shows sensor data S according to an exemplary embodiment of the present invention. d and audio data A d The correlation between the two is schematically shown. In this exemplary setup, a ceiling fan was used and operated. The ceiling fan was switched "on" and "off" six times consecutively for each of the ceiling fan speeds of low setting S1, medium setting S2, and high setting S3. Here, the "on" and "off" periods were 10 seconds and 5 seconds, respectively. The noise from the airflow generated by the ceiling fan, i.e., audio data A shown at the top of Figure 2a, is represented. d However, this was recorded (detected) by the sensor device's microphone. Furthermore, the sensor device's thermal sensor recorded raw dual-channel data S d As shown at the bottom of Figure 2a, sensor data S resulting from the operation of the ceiling fan. dIt was detected. Figure 2a shows the sensor data S (which is shown even more clearly in the enlarged view of Figure 2b). d and audio data A d This shows a correlation between the two. Sensor data S d and audio data A d One or more correlation criteria C between c Based on this, the sensor device receives sensor data S d Level L of influence of the characteristics of airflow to (multiple characteristics possible) f It is configured / arranged to estimate.

[0041] Figures 3a-3f schematically illustrate the correlations for estimating the level of influence of at least one characteristic of airflow on sensor data according to exemplary embodiments of the present invention.

[0042] Figure 3a shows the processor of the sensor device of the present invention, which processes sensor data S d and audio data A d at least one correlation criterion C between c Based on the sensor data S d Level L of influence of at least one characteristic of the airflow to f This shows an example of a configuration that estimates this.

[0043] In Figure 3b, the processor further processes the sensor data S d and audio data A d The magnitude (size, intensity) of the airflow estimated based on A s Correlation criterion C between c Based on the first correlation criterion Cc1, the sensor data S d Level L of influence of at least one characteristic of the airflow to f It is configured to estimate.

[0044] In Figure 3c, the processor processes the sensor data S from Figure 3a. d and audio data A d Correlation criterion C between c and sensor data S dand the first vibration data V generated from the airflow d1 Correlation criterion C between d Through both, sensor data S d Level L of influence of at least one characteristic of the airflow to f It is configured to estimate.

[0045] In Figure 3d, the processor receives the obtained audio data A d Based on this, at least one fan operates L l The processor is configured to determine the sensor data S. d and the determined operation of at least one fan L l at least one correlation criterion C between e Based on the sensor data S d Level L of influence of at least one characteristic of the airflow to f It is configured to estimate.

[0046] In Figure 3e, the processor generates detected magnetic data M from the operation of the fan(s). d The processor is configured to obtain the sensor data S shown in Figure 3a. d and audio data A d Correlation criterion C between c and sensor data S d and magnetic data M d Correlation criterion C between f Through both, sensor data S d Level L of influence of at least one characteristic of the airflow to f It is configured to estimate.

[0047] In Figure 3f, the processor processes the sensor data S from Figure 3a. d and audio data A d Correlation criterion C between c and sensor data S d and second vibration data V generated from at least one fan d2 Correlation criterion C between g Through both, sensor data Sd Level L of influence of at least one characteristic of the airflow to f It is configured to estimate.

[0048] Figure 4 schematically illustrates a lighting system 700 according to an exemplary embodiment of the present invention. The lighting system 700 includes at least one light source 710, exemplified as a luminaire positioned on the ceiling of a space or room 120. The lighting system 700 further includes a sensor configuration, including a sensor device 100, according to any of the earlier embodiments of the present invention, connected to the light source(s) 710. The arrangement of the sensor device 100 on / in the light source 710 is shown only as an example of the lighting system 700, and it should be understood that the sensor device 100 may, alternatively, be positioned separately from the light source(s) 710. According to one or more of the earlier embodiments of the present invention, a processor (not shown) of the sensor device 100 in the sensor configuration is configured to detect the movement 185 of at least one object(s) 110 in the space 120 based on the estimated level of influence of at least one characteristic of airflow on the sensor data. As shown in the example in Figure 4, the sensor configuration may include, for example, an HVAC vent 180 located on the ceiling of a space or room 120, which generates an airflow 170 during operation. However, it should be understood that the airflow 170 may be generated from substantially any other elements and / or circumstances that generate the airflow 170, such as open windows and / or open doors in the space or room 120. This operation of the sensor device 100 for evaluating the influence of the airflow 170 on the sensor data can be described and illustrated as follows. The thermal sensor (not shown) of the sensor device 100 receives sensor data S in the form of presence and / or motion data 185 of a person 110, motion of a ceiling fan 180, etc. d It is positioned to detect the airflow 170. The microphone (not shown) of the sensor device 100 receives audio data A generated from the airflow 170. d It is positioned to detect the sensor data S. d and audio data A dBased on the correlation criteria (multiple) between the sensor data and the sensor device 100, the sensor device 100 is configured to estimate the level of influence of the characteristics (multiple) of the airflow 170 on the sensor data S d The light source(s) 710 is configured to operate based on the estimated influence level of at least one characteristic of the airflow 170. Thus, the sensor device 100 is positioned / configured to detect "false" triggers in sensor data caused by the airflow 170 and to compensate for this when detecting the movement 185 of objects(s) (people(s)) 110 in space 120.

[0049] Figure 5 schematically illustrates Method 800 for evaluating the influence of airflow on sensor data. Method 800 includes the steps of detecting sensor data 810 and detecting audio data generated from the airflow 820. Method 800 further includes the steps of obtaining the detected sensor data and the detected audio data 830 and estimating at least one characteristic of the airflow based on the obtained audio data 840. Method 800 further includes at least one correlation criterion C between the sensor data and the audio data c Based on this, the influence level L of at least one characteristic of airflow on the sensor data f This includes step 850, which estimates the value.

[0050] Those skilled in the art will recognize that the present invention is by no means limited to the preferred embodiments described above. Rather, many modifications and variations are possible within the scope of the appended claims. For example, the size, number, positioning, etc., of one or more elements of the sensor device 100 may differ from those shown.

Claims

1. A sensor device for evaluating the effect of airflow on sensor data, wherein the sensor device is A thermal sensor for detecting sensor data, A microphone for detecting audio data generated from airflow, A processor connected to the thermal sensor and the microphone, The processor includes, To obtain the detected sensor data and the detected audio data, Based on the audio data obtained, at least one characteristic of the airflow is estimated, and Based on at least one correlation criterion between the sensor data and the audio data, the level of influence of at least one characteristic of the airflow on the sensor data is estimated. A sensor device configured in such a way.

2. The sensor device according to claim 1, wherein the audio data includes an audio spectrogram of amplitude as a function of frequency.

3. The sensor device according to claim 1, wherein the at least one characteristic includes the magnitude of the airflow.

4. The sensor device according to claim 1, wherein the thermal sensor has sensing sensitivity, and the processor is configured to control the thermal sensor to reduce the sensitivity if the estimated influence level of the at least one characteristic exceeds a predetermined threshold.

5. The sensor device according to claim 1, wherein the processor is configured to control the thermal sensor to stop detecting sensor data if the estimated influence level of the at least one characteristic exceeds a predetermined threshold.

6. The sensor device according to claim 1, comprising at least one element including at least one of an opening, a cavity, and a recess, configured to generate an audible resonance with respect to the airflow, wherein the resulting audio data includes the audible resonance.

7. The sensor device is A first accelerometer for detecting first vibration data generated from the airflow, Includes, The processor is connected to the first accelerometer and configured to obtain the detected first vibration data, and the processor, Based on at least one correlation criterion between the sensor data and the first vibration data, the level of influence of the at least one characteristic of the airflow on the sensor data is estimated. The sensor device according to claim 1, configured as described above.

8. The aforementioned processor, Based on the audio data obtained, the operation of at least one fan is determined. The processor is configured in such a way that, Based on at least one correlation criterion between the sensor data and the operation of at least one fan, the level of influence of the at least one characteristic of the airflow on the sensor data is estimated. The sensor device according to claim 1, configured as described above.

9. The sensor device includes a first temperature sensor for detecting temperature data, the first temperature sensor is located within a predetermined distance from the thermal sensor and is connected to the processor, the processor is Obtain the detected temperature data, and Based on the temperature data obtained, the level of influence of at least one characteristic of the airflow on the sensor data is estimated. The sensor device according to claim 1, configured as described above.

10. A sensor configuration for detecting the movement of at least one object in space, wherein the sensor configuration is A sensor device according to any one of claims 1 to 9, Includes, The aforementioned processor, The motion of at least one object in space is detected based on the estimated level of influence of the at least one characteristic of the airflow on the sensor data. A sensor configuration as shown above.

11. The sensor configuration is, At least one fan, Includes, The sensor configuration according to claim 10, wherein the audio data is generated from audible sounds produced by the operation of the at least one fan.

12. The sensor configuration is, A second accelerometer for detecting second vibration data generated from at least one of the fans, Includes, The processor is connected to the second accelerometer and configured to obtain the detected second vibration data, and the processor, Based on at least one correlation criterion between the sensor data and the second vibration data, the level of influence of the at least one characteristic of the airflow on the sensor data is estimated. The sensor configuration according to claim 11, configured as described above.

13. The sensor configuration is, The microphone and the storage medium connected to the processor, The sensor configuration according to claim 11, comprising, wherein the storage medium is configured to store the detected audio data, and the processor is configured to determine an operational failure of the at least one fan based on the stored audio data.

14. At least one light source, A sensor configuration according to claim 10, wherein the sensor device is connected to the at least one light source, and the sensor device is configured to operate the at least one light source based on the movement of the at least one object in the space detected based on the estimated level of influence of the at least one characteristic of the airflow on the sensor data, A lighting system, including a lighting system.

15. A method for evaluating the effect of airflow on sensor data, wherein the method is Steps to detect sensor data, A step to detect audio data generated from airflow, The steps include obtaining the detected sensor data and the detected audio data, The steps include: estimating at least one characteristic of the airflow based on the audio data obtained above; A step of estimating the level of influence of the at least one characteristic of the airflow on the sensor data based on at least one correlation criterion between the sensor data and the audio data, Methods that include...

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