A method for selectively capturing presence sensor data for diagnosis

Abstract

A method (600) for selectively capturing presence sensor data for diagnosis purpose in a presence detection based control apparatus (300), wherein the control apparatus (300) is configured to provide TURN-ON and TURN-OFF controls to one or more electronic devices, the method (600) comprising steps of the control apparatus (300): measuring (S601) a first average occurrence of distinctive TURN-ON controls with each distinctive TURN-ON 5 control followed by a TURN-OFF control within a first time interval; measuring (S602) a second average occurrence of distinctive TURN-OFF controls with each distinctive TURN-OFF control followed by a TURN-ON control within a second time interval; entering (S603) a diagnosis mode for data capturing; capturing (S604), in the diagnosis mode, presence sensor data that triggers distinctive TURN-ON controls and / or presence sensor data that 10 triggers distinctive TURN-OFF controls.

Description

[0001] 2024PF80244

[0002] 1

[0003] A method for selectively capturing presence sensor data for diagnosis

[0004] FIELD OF THE INVENTION

[0005] The present invention generally relates to a method for more efficient sensor data capturing for diagnosis in a presence detection based control apparatus or system.

[0006] BACKGROUND OF THE INVENTION

[0007] Motion or presence detection based control is used in various applications, particularly in smart building scenarios. For instance, it can be used to control HVAC (heating, ventilation, and air conditioning) systems in a building. By detecting the presence or absence of people in different rooms, the HVAC system can adjust the temperature settings automatically to optimize energy consumption and create a comfortable indoor environment. Similarly, motion or presence detection sensors can be used to control other devices in a smart building, such as window blinds, thermostats, and lighting systems. In these cases, motion or presence detection based control provide an automated, convenient and efficient way to monitor and control various devices and systems.

[0008] Similarly, a motion detection based lighting control system is a type of lighting automation system that uses sensors to detect the presence of people or objects in a room or area. When motion is detected, the system turns on the lights in the area, and when there is no motion, the lights turn off automatically. This type of system is commonly used in public or private spaces, such as offices, schools, hospitals, and homes, to save energy and reduce costs associated with lighting.

[0009] Typical malfunctions of a motion / occupancy sensor are false trigger and false negative (i.e., light turns off when people are still in the space). Debugging a motion or presence detection based control system can be challenging when it is deployed on the customer side. For example, the system may be affected by environmental factors that were not accounted for during the development phase, such that the motion detection sensors may be triggered by pets, or the lighting conditions in the room may be different than what was expected. Another challenge is that the system may be integrated with other devices or systems, which can make it difficult to isolate and diagnose issues. Furthermore, different from the product development stage, it can be very difficult to acquire sensor data related to 2024PF80244

[0010] 2 these malfunctions once a sensor is released and installed in a customer’s space, given the amount of data may be required to store or transfer.

[0011] US2012153868A1 relates to a lighting controller configured to optimize a timeout value for both energy saving and improving occupant comfort.

[0012] SUMMARY OF THE INVENTION

[0013] It is recognized by the inventor that it is beneficial to implement a method for selectively capturing sensor data for a more effective data storage / transfer and eventually a more effective diagnosis. More particularly, the goal of this invention is achieved by a method as claimed in claim 1, by a control apparatus as claimed in claim 8, by a lighting fixture as claimed in claim 12, and by an electronic system as claimed in claim 13.

[0014] In accordance with a first aspect of the invention a method is provided. A method for selectively capturing presence sensor data for diagnosis purpose in a presence detection based control apparatus, wherein the control apparatus is configured to provide TURN-ON and TURN-OFF controls to one or more electronic devices, the method comprising steps performed by the control apparatus: measuring, in a normal mode, a first average occurrence of distinctive TURNON controls with each distinctive TURN-ON control being a TURN-ON control followed by a TURN-OFF control within a first time interval; measuring, in the normal mode, a second average occurrence of distinctive TURN-OFF controls with each distinctive TURN-OFF control being a TURN-OFF control followed by a TURN-ON control within a second time interval; entering a diagnosis mode for data capturing; capturing, in the diagnosis mode, presence sensor data selectively, such that only presence sensor data that triggers further distinctive TURN-ON controls and / or further distinctive TURN-OFF controls are captured.

[0015] The presence sensor or motion detection sensor may be one of a radar sensor, a passive infrared sensor, an ultrasonic sensor, a microwave sensor, an image sensor, a radio frequency (RF) sensor.

[0016] To capture only relevant and useful data will improve the accuracy and speed of a diagnosis process, as providing a dataset that is a mix of relevant data and large amounts of irrelevant data will not only slow down the diagnostic process but may also lead to inaccurate diagnostic results. Moreover, to store and / or transfer the large amount of data can cause other problems in practice. 2024PF80244

[0017] 3

[0018] The present invention discloses a method of identifying potentially relevant data and capturing only those potentially relevant data for diagnosis. For example, for the presence detection based control apparatus, some special or irregular control events may be resulted from some coincidental events (e.g., no error in the presence detection), but they may also be an indication of an error in the presence detection. Sensor data that results in an error in the presence detection (e.g., miss detection or false alarm) is valuable for diagnosis.

[0019] Beneficially, the step of entering the diagnosis mode is performed when receiving a command or an error report from a user, or when detecting an increase in the occurrence of distinctive TURN-ON controls as compared to the first average occurrence exceeding a first threshold, or when detecting an increase in the occurrence of distinctive TURN-OFF controls as compared to the second average occurrence exceeding a second threshold.

[0020] Thus, the step of entering the diagnosis mode may be triggered externally, such as by a user command or error report, or automatically by the control apparatus itself.

[0021] By calculating an average number of occurrences of a type of special control events and detecting an increase or deviation from that average number, it is then possible for the control apparatus to start the diagnosis mode automatically.

[0022] Since the distinctive TURN-ON controls and distinctive TURN-OFF controls may have different impacts on the user experience and are triggered by different factors, the first threshold may be the same or different from the second threshold. The first threshold may also be defined as a relative percentage or ratio as compared to the first average occurrence, and the same for the second threshold. As one example, the first or the second threshold may be set to indicate a 20%-50% increase in distinctive control events as compared to an average occurrence. In another example, the first or the second threshold may be set to indicate 1.2-2 times increase in distinctive control events as compared to an average occurrence.

[0023] Advantageously, the captured presence sensor data is either stored locally in the control apparatus or transferred to a remote server.

[0024] For example, the method may comprise a step of either storing the captured presence sensor data in a local storage unit comprised in the control apparatus or transferring the captured presence sensor data to a remote server via a communication interface comprised in the control apparatus after entering the diagnosis mode.

[0025] There are several approaches to processing sensor data for diagnosis purpose. One option is to process the captured sensor data on a backend server, such as the remote 2024PF80244

[0026] 4 server. This involves sending the sensor data to the server where it can be analysed using various algorithms and / or machine learning techniques. Another approach is to process the sensor data locally on the device itself or by the user on the spot. This approach can be useful for real-time analysis and for devices that may not always be connected to the server.

[0027] When the control apparatus comprises a communication interface, the captured sensor data can be sent directly to the remote server or backend server for diagnosis. When the control apparatus comprises a local storage unit, the captured sensor data can be stored in the local storage unit, and the user may be able to read out the sensor data for diagnosis or provide the sensor data to the vendor for diagnosis.

[0028] Preferably, in the diagnosis mode, the first average occurrence or the second average occurrence is either stored locally in the control apparatus or transferred to the remote server along with the captured presence sensor data.

[0029] To provide more insight for diagnosis, it is also beneficial that the first average occurrence and / or the second average occurrence are stored or transferred along with the captured presence sensor data.

[0030] In one example, the increase in the occurrence of distinctive TURN-ON or TURN-OFF controls is detected in a sliding time window.

[0031] There are different aspects to be considered when determining the duration of the sliding time window, such as application requirements and the desired time resolution. For example, if the goal is to detect short-term changes in the detection performance, a smaller window size may be more appropriate. If the goal is to capture longer-term trends, a larger window size may be necessary. In the meanwhile, the size of the time window should provide adequate time resolution to capture changes in the detection performance over time. A smaller window size will provide higher time resolution, while a larger window size will help to filter out accidental errors.

[0032] Advantageously, the duration of the sliding time window is predefined or configurable.

[0033] In one example, the duration of the sliding time window is one of a week, a day, an hour, or another time unit configured by a user.

[0034] Beneficially, the increase in the occurrences of distinctive TURN-ON or TURN-OFF controls are detected by further distinguishing the occurrences according to a time period of a day and / or a day of a week.

[0035] The presence or occupancy of people in a public or private space can vary depending on the time period of a day and / or a day of the week. For example, during 2024PF80244

[0036] 5 weekdays, a workplace will likely have higher occupancy during regular business hours, with more people arriving in the morning and leaving in the evening; and on weekends, the occupancy will be lower as most people will be off work. In a retail store, the occupancy may be higher during weekends and holidays as people have more time to shop, while during weekdays, the occupancy may be lower. In a residential building, the occupancy may be higher during evenings and weekends as people are more likely to be at home. Overall, the presence or occupancy of people in a public or private space can vary in different deployment scenarios. Therefore, it can be beneficial to distinguish a time period of a day and / or a day of a week when observing the occurrences of distinctive TURN-ON or TURN-OFF controls, such that variations resulted from other (non-technical) factors can be excluded.

[0037] In one example, the first time interval is equal to or slightly longer than a hold period, with the hold period defined as a time duration to turn off the one or more light devices since the most recent presence detection.

[0038] The hold period is also called hold on period, which refers to the time during which the light will stay on after motion has been detected. When there is no follow-up motion detected, a high probability of space unoccupancy is confirmed so that the lamp can be turned off.

[0039] In accordance with a second aspect of the invention a control apparatus is provided. A control apparatus configured to provide TURN-ON and TURN-OFF controls to one or more electronic devices based on presence detection, and to selectively capture presence sensor data for diagnosis purpose; the control apparatus comprising: a presence sensor configured to carry out presence detection for generating the TURN-ON and TURN-OFF controls; and a controller configured to: measure, in a normal mode, a first average occurrence of distinctive TURNON controls with each distinctive TURN-ON control being a TURN-ON control followed by a TURN-OFF control within a first time interval; measure, in the normal mode, a second average occurrence of distinctive TURN-OFF controls with each distinctive TURN-OFF control being a TURN-OFF control followed by a TURN-ON control within a second time interval; control the control apparatus to enter a diagnosis mode for data capturing; capture, in the diagnosis mode, presence sensor data selectively, such that only presence sensor data that triggers further distinctive TURN-ON controls and / or further distinctive TURN-OFF controls are captured. 2024PF80244

[0040] 6

[0041] The presence sensor or motion detection sensor may be one of a radar sensor, a passive infrared sensor, an ultrasonic sensor, a microwave sensor, an image sensor, a radio frequency (RF) sensor.

[0042] Diagnosis mode for a presence detection-based control apparatus enables finetuning and troubleshooting to optimize its performance by leveraging raw data analysis and parameter adjustments. Raw RF data, such as reflections, signal strength, frequency shifts, or time-of-flight information, may be obtained to identify environmental factors like noise, interference, or patterns that may impact detection accuracy. This data provides valuable insights into how motion or objects in the environment affect sensor readings. Additionally, diagnosis mode allows for adjusting detection thresholds to balance sensitivity and reliability. For instance, thresholds can be increased to filter out minor movements (e.g., small animals or environmental noise) or lowered to detect subtle activity (e.g., breathing or slight gestures), ensuring the sensor performs optimally for its intended application.

[0043] Beneficially, the control apparatus further comprises a local storage unit or a communication interface, wherein the controller is further configured to control the control apparatus to store the captured presence sensor data in the local storage unit or transfer the captured presence sensor data to a remote server via the communication interface when the control apparatus is in a diagnosis mode.

[0044] The local storage unit may be a removable storage, such that the local storage unit can be removed from the electronic device and used in other devices. The local storage unit may be memory cards, such as SD cards, microSD cards, or CompactFlash cards. Alternatively, the local storage unit may also be USB flash drives that can be plugged into a USB port on a computer or other electronic device.

[0045] The communication interface may be related to a wired or wireless communication interface. For example, the control apparatus may connect to the remote server via an Ethernet interface, a powerline communication (PLC) interface, a Wi-Fi interface, or another short range wireless communication interface (e.g., the remote server is connected to the same wireless network).

[0046] In one example, the controller is further configured to: control the control apparatus to enter the diagnosis mode when detecting an increase in the occurrence of distinctive TURN-ON controls as compared to the first average occurrence exceeding a first threshold or detecting an increase in the occurrence of distinctive TURN-OFF controls as compared to the second average occurrence exceeding a second threshold. 2024PF80244

[0047] 7

[0048] In another example, the control apparatus further comprises a user interface, wherein the controller is further configured to: control the control apparatus to enter the diagnosis mode when an error report is received from a user via the user interface.

[0049] The user interface can be a button or a touch screen on the electronic device. The user interface may also be a remote control use to control one or more settings of the electronic device. The user interface may also be an interface for receiving voice commands from a user. The user interface may also be mobile app, which allows a user to control the electronic device from their smartphone or tablet.

[0050] When the user observes mal function of the control of the electronic device, he or she can immediately trigger the control apparatus to enter the diagnosis mode.

[0051] In accordance with a third aspect of the invention a lighting fixture is provided. A lighting fixture comprising a light source and a control apparatus according to the present invention; wherein the control apparatus is configured to control the light source.

[0052] In accordance with a further aspect of the invention an electronic system is provided. An electronic system comprises one or more electronic devices and a control apparatus according to the present invention; wherein the control apparatus is configured to control the one or more electronic devices; wherein at least one of the one or more electronic devices is connected to the control apparatus via a wired or wireless communication interface.

[0053] The one or more electronic devices may be related to one or more same or different electronic devices in a smart home or smart building scenario. For example, an electronic device may be related to an air conditioner, a heating, ventilation, and air conditioning (HVAC) system, a lighting device, a smart lock and security device, or a smart appliance, such as a smart TV or an entertainment system.

[0054] Beneficially, the one or more electronic devices are lighting devices, and the electronic system is a lighting system.

[0055] In a further option, the lighting system may comprise more than one group of lighting devices, with each group of lighting devices controlled by one control apparatus.

[0056] The wired communication interface may be according to a Digital Addressable Lighting Interface (DALI) protocol or a Digital Multiplex (DMX) protocol. The wireless communication interface may be according to a Bluetooth, ZigBee, Z-Wave, or Wi-Fi protocol. 2024PF80244

[0057] 8

[0058] BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In the drawings, like reference characters generally refer to the same parts throughout the different figures. Also, the drawings are not necessarily to scale, emphasis instead generally being placed upon illustrating the principles of the invention.

[0060] Fig. 1 illustrates an electronic system comprising a plurality of electronic devices and a control apparatus;

[0061] Fig. 2 exemplarily illustrates a block diagram of a control apparatus;

[0062] Fig. 3 exemplarily illustrates a block diagram of a lighting fixture; and

[0063] Fig. 4 shows a flow diagram of a method for selectively capturing presence sensor data for diagnosis purpose in a presence detection based control apparatus.

[0064] DETAILED DESCRIPTION OF EMBODIMENTS

[0065] The embodiments set forth below represent information to enable those skilled in the art to practice the embodiments. Upon reading the following description in light of the accompanying drawings, those skilled in the art will understand the concepts of the disclosure and will recognize applications of these concepts not particularly addressed herein. It should be understood that these concepts and applications fall within the scope of the disclosure.

[0066] FIG. 1 illustrates an electronic system 100 comprising a plurality of electronic devices 200 and a control apparatus 300. The control apparatus 300 is configured to control the one or more electronic devices 200 based on presence detection. Beneficially, at least one of the one or more electronic devices 200 is connected to the control apparatus 300 via a wired or wireless communication interface, such that the control command is provided by the control apparatus 300 to the one or more electronic devices 200 via the wired or wireless communication interface.

[0067] For an electronic device 200, a wired communication interface may be related to Ethernet or powerline communication (PLC), and a wireless communication interface may operate according to a short range wireless communication protocol, such as Wi-Fi, Bluetooth, BLE, Zigbee, Z-wave, or Thread.

[0068] As shown in the example of FIG. 1, the electronic system may be deployed in a same room, and the control apparatus may be placed close to the entrance of the room and is configured to control one or more electronic devices 200 in the room. This example only shows one control apparatus in the system. Alternatively, the electronic system may comprise 2024PF80244

[0069] 9 more than one group of electronic devices 200, with each group of electronic devices 200 controlled by one control apparatus 300.

[0070] In one example, the one or more electronic devices 200 are lighting devices and the electronic system 100 is a lighting system. The presence detection based TURN_ON or TURN OFF controls are related to the control of one or more light sources comprised in a lighting device, such that the TURN ON and TURN OFF controls are LIGHT ON and LIGHT OFF controls.

[0071] For a lighting system, the wired communication interface may be according to a Digital Addressable Lighting Interface (DALI) protocol, a Digital Multiplex (DMX) protocol, or a PLC protocol. The wireless communication interface may be according to a Bluetooth, BLE, ZigBee, Z-Wave, Thread, or Wi-Fi protocol.

[0072] The presence sensor or motion detection sensor may be one of a radar sensor, a passive infrared sensor, an ultrasonic sensor, a microwave sensor, an image sensor, a radio frequency (RF) sensor. Different sensors employ different detection principles and have different advantages and disadvantages in practical applications.

[0073] Passive Infrared Sensors, PIRs, operate by registering incident IR radiation and when e.g. people move in front of the PIR the intensity distribution on the PIR sensor changes which can be taken as an indication that people are present in front of the sensor. A drawback with PIRs is, however, that they are not very sensitive and small motions. In other words, the PIRs are prone to high false negative rates meaning that PIRs often fail to sense motion when there in fact is motion to detect.

[0074] Radar sensors are active sensors which transmit a radar signal into the environment and measure the reflected radar signal. If an object (e.g. a human) moves this will alter the reflected radar signal and this alteration can be used as an indication of motion. Radar sensors tend to be much more sensitive compared to PIRs such that even small motions can be detected which reduced the false negative rate. On the other hand, radar sensors are in some scenarios too sensitive leading to an increase in false positive rates. That is, radar sensors are prone to detecting motion even when no people are present. For example, since radar signals can penetrate dry wall and glass, it is possible that motion in a completely separate room is detected by the radar sensor or that a person passing-by a room equipped with a radar sensor is registered by the radar sensor. Therefore, diagnosis sometimes is needed to improve the performance of a radar sensor by further customizing the settings according to the actual deployment. 2024PF80244

[0075] 10

[0076] Analysing sensor data such as raw sensor signal is an effective method for problem diagnosis. During product development stage, sensor data related to a certain problem can be acquired via properly designed test. For example, if a radar sensor has false trigger, one can put the sensor in a space for a certain period and make sure no person enters the space during the period. Then each motion detection by the sensor in the period is a false trigger. Then sensor data related to each motion detection can be acquired and marked as a sensor data segment of a false trigger for diagnosis. In other words, getting sensor data segments corresponding to a certain type of problem is key for effective diagnosis.

[0077] After a sensor product is released and being used in the space of customers, it is almost unavoidable that some sensors will function improperly leading to customer complaints. Typical malfunctions of a motion / occupancy sensor (e.g., radar based) are false trigger and false negative (i.e., light turns off when people are still in the space). Different from the product development stage, it is very difficult to acquire sensor data related to these malfunctions once a sensor is released and installed in a customer’s space. One method is to capture sensor data segments related to all the light ONs and OFFs without discriminate which data segments are related to malfunctions. This makes the analysis inefficient. For a sensor with network connection, this also means huge amounts of data uploading which could be costly and even not allowed (e.g., data rate limitations, data security / privacy considerations). For a sensor without network connection, these sensor data can only be stored in its local storage which usually has a limited storage capacity (e.g., a typical MCU with flash memory from 32KB to 4MB).

[0078] It is therefore desirable to selectively capture sensor data which are related to sensor malfunctions to enable efficient diagnosis, and the present invention discloses a method to capture sensor data which are highly possible related to false triggers or false negatives of a presence or motion sensor.

[0079] FIG. 2 exemplarily illustrates a block diagram of a control apparatus 300 that is configured to provide TURN-ON and TURN-OFF controls to one or more electronic devices based on presence detection. As an example, the control apparatus 300 comprises at least a presence sensor 301 and a controller 302.

[0080] The presence sensor 301 may be one of a passive infrared sensor, an ultrasonic sensor, a microwave sensor, an image sensor, and a radio frequency sensor.

[0081] The presence sensor 301 is configured to carry out presence detection for generating the TURN-ON and TURN-OFF controls.

[0082] The controller 302 is configured to: 2024PF80244

[0083] 11 measure a first average occurrence of distinctive TURN-ON controls with each distinctive TURN-ON control followed by a TURN-OFF control within a first time interval; measure a second average occurrence of distinctive TURN-OFF controls with each distinctive TURN-OFF control followed by a TURN-ON control within a second time interval; control the control apparatus 300 to enter a diagnosis mode for data capturing; capture, in the diagnosis mode, presence sensor data that triggers distinctive TURN-ON controls and / or presence sensor data that triggers distinctive TURN-OFF controls.

[0084] Optionally, the control apparatus 300 may further comprise a local storage unit 303 or a communication interface 304. When the control apparatus 300 comprises a local storage unit 303, the controller 302 is further configured to control the control apparatus 300 to store the captured presence sensor data in the local storage unit 303 when the control apparatus 300 is in the diagnosis mode. When the control apparatus 300 comprises a communication interface 304, the controller 302 is further configured to control the control apparatus 300 to transfer the captured presence sensor data to a remote server via the communication interface 304 when the control apparatus 300 is in the diagnosis mode.

[0085] When the control apparatus 300 comprises both a local storage unit 303 and a communication interface 304, the controller 302 may be configured to preferably to control the control apparatus 300 to transfer the captured presence sensor data to the remote server via the communication interface 304, or to carry out both.

[0086] The control apparatus 300 may be triggered to enter the diagnosis mode according to different options or settings. When there is a customer complaint about a sensor, e.g., the customer found the sensor has false triggers or false negatives, the customer may then be informed / instructed to set the control apparatus to work as diagnostic mode. This user-initiated operation (i.e., setting the sensor to diagnostic mode) can be important because it indicates that the sensor has malfunctions recently. Alternatively, the control apparatus may be configured to enter the diagnostic mode automatedly, such as upon detection the increase of the occurrence of distinctive TURN-ON or TURN-OFF control.

[0087] For example, the controller 302 may be configured to: control the control apparatus 300 to enter the diagnosis mode when detecting an increase in the occurrence of distinctive TURN-ON controls as compared to the first average occurrence exceeding a first threshold or detecting an increase in the occurrence of 2024PF80244

[0088] 12 distinctive TURN-OFF controls as compared to the second average occurrence exceeding a second threshold.

[0089] In another example, the control apparatus 300 may further comprise a user interface 305. The controller 302 is further configured to: control the control apparatus 300 to enter the diagnosis mode when an error report is received from a user via the user interface 305.

[0090] FIG. 3 exemplarily illustrates a block diagram of a lighting fixture 200’. As a basic setup, a lighting fixture 200’ comprises a light source 201 and a control apparatus 300 according to the present invention. The control apparatus 300 is configured to control the light source, and the TURN-ON and TURN-OFF controls are related to LIGHT ON and LIGHT OFF controls of the light source.

[0091] FIG. 4 shows a flow diagram of a method 600 for selectively capturing presence sensor data for diagnosis purpose in a presence detection based control apparatus 300. With the control apparatus 300 configured to provide TURN-ON and TURN-OFF controls to one or more electronic devices, the method 600 comprises steps of the control apparatus 300: measuring, in step S601, a first average occurrence of distinctive TURN-ON controls with each distinctive TURN-ON control followed by a TURN-OFF control within a first time interval; measuring, in step S602, a second average occurrence of distinctive TURNOFF controls with each distinctive TURN-OFF control followed by a TURN-ON control within a second time interval; entering, in step S603, a diagnosis mode for data capturing; capturing in step S604, in the diagnosis mode, presence sensor data that triggers distinctive TURN-ON controls and / or presence sensor data that triggers distinctive TURN-OFF controls.

[0092] The step of entering the diagnosis mode may be performed based on different scenarios, such as when receiving a command or an error report from a user, or when detecting an increase in the occurrence of distinctive TURN-ON controls as compared to the first average occurrence exceeding a first threshold, or when detecting an increase in the occurrence of distinctive TURN-OFF controls as compared to the second average occurrence exceeding a second threshold.

[0093] Since the distinctive TURN-ON controls and distinctive TURN-OFF controls may have different impacts on the user experience and are triggered by different factors, the 2024PF80244

[0094] 13 first threshold may be the same or different from the second threshold. The first threshold may also be defined as a relative percentage or ratio as compared to the first average occurrence, and the same for the second threshold. As one example, the first or the second threshold may be set to indicate a 20%-50% increase in distinctive control events as compared to an average occurrence. In another example, the first or the second threshold may be set to indicate 1.2-2 times increase in distinctive control events as compared to an average occurrence.

[0095] In the diagnosis mode, the captured presence sensor data may be either stored locally in the control apparatus 300 or transferred to a remote server.

[0096] In the diagnosis mode, the first average occurrence or the second average occurrence may be either stored locally in the control apparatus 300 or transferred to the remote server along with the captured presence sensor data.

[0097] The increase in the occurrence of distinctive TURN-ON or TURN-OFF controls may be detected in a sliding time window, and the duration of the sliding time window is predefined or configurable. Preferably, the duration of the sliding time window is one of a week, a day, an hour, or another time unit configured by a user.

[0098] In one example, the increase in the occurrences of distinctive TURN-ON or TURN-OFF controls are detected by further distinguishing the occurrences according to a time period of a day and / or a day of a week.

[0099] The first time interval is equal to or slightly longer than a hold period, with the hold period defined as a time duration to turn off the one or more electronic devices since the most recent presence detection.

[0100] To take lighting control as an example, when operating at the normal mode, the control apparatus records certain types of LIGHT ON and LIGHT OFF. Specifically, if a LIGHT ON (e.g., triggered by motion detection of the sensor) is followed by a LIGHT OFF just or slight after the hold-time (e.g., 5 min), the LIGHT ON is identified as a distinctive LIGHT ON and counted. Such a LIGHT ON could be triggered by the sensor detecting a person passing by then no new motions afterwards till the hold-time has elapsed. However, such a LIGHT ON could also be due to a false trigger from the sensor. If a LIGHT OFF is followed by a LIGHT ON in a rather short time (e.g., a few seconds), the LIGHT OFF is counted as a distinctive LIGHT OFF. In reality, such a LIGHT OFF could be a correct operation because the space has been unoccupied for the hold-time, and the LIGHT ON shortly after the LIGHT OFF is triggered by a valid motion such as a person entering the space just after the LIGHT OFF. In the meanwhile, such a LIGHT OFF could also be a false 2024PF80244

[0101] 14 negative, e.g., the sensor failed to detect any motion of a person in the space who is rather still. Then right after the LIGHT OFF which is a wrong operation, the person intentionally does some motions (e.g., waving arm) to trigger the LIGHT_ON.

[0102] The control apparatus may count average number of distinctive LIGHT ON and LIGHT OFF for each day (24 hours) respectively. Once entering the diagnostic mode, the sensor compares the number of distinctive LIGHT ON and LIGHT OFF in a sliding time window, such as a short recent period (e.g., past few days), to the average numbers over a longer past period (e.g., 1 month before the past few days). If the numbers of distinctive LIGHT ON in the past few days are significantly higher than the average number of distinctive LIGHT ON, the malfunction reported by the customer is determined as false trigger. If the numbers of LIGHT OFF in the past few days are significantly higher than the average number of LIGHT OFF, the malfunction reported by the customer is determined as false negative. If the determined malfunction is false negative, the control apparatus needs to log all the LIGHT OFF events to determine whether a LIGHT ON follows shortly after a LIGHT OFF, and then transfers the sensor data that triggers the distinctive LIGHT OFF from the buffer to the storage and deletes other sensor data that is irrelevant to the distinctive LIGHT OFF from the buffer. If the determined malfunction is false trigger, the control apparatus needs to log all the LIGHT ON events to determine whether a LIGHT OFF follows just or slightly after the hold-time, and transfers sensor data that triggers the distinctive LIGHT ON from the buffer to the storage and deletes other sensor data that is irrelevant to the distinctive LIGHT ON from the buffer.

[0103] Once the storage is full, or the required duration for diagnosis (e.g., 48 hours) is reached, the sensor exists the diagnostic mode and indicates the user to get the captured sensor data from the storage for diagnosis.

[0104] The method according to the present invention may be implemented on a computer as a computer implemented method, or in dedicated hardware, or in a combination of both.

Claims

2024PF8024415CLAIMS:

1. A method (600) for selectively capturing presence sensor data for diagnosis purpose in a presence detection based control apparatus (300), wherein the control apparatus (300) is configured to provide TURN-ON and TURN-OFF controls to one or more electronic devices, the method (600) comprising steps performed by the control apparatus (300): measuring (S601), in a normal mode, a first average occurrence of distinctive TURN-ON controls with each distinctive TURN-ON control being a TURN-ON control followed by a TURN-OFF control within a first time interval; measuring (S602), in the normal mode, a second average occurrence of distinctive TURN-OFF controls with each distinctive TURN-OFF control being a TURNOFF control followed by a TURN-ON control within a second time interval; entering (S603) a diagnosis mode for data capturing; capturing (S604), in the diagnosis mode, presence sensor data selectively, such that only presence sensor data that triggers further distinctive TURN-ON controls and / or further distinctive TURN-OFF controls are captured; wherein the step of entering (S603) the diagnosis mode is performed when receiving a command or an error report from a user, or when detecting an increase in the occurrence of distinctive TURN-ON controls as compared to the first average occurrence exceeding a first threshold, or when detecting an increase in the occurrence of distinctive TURN-OFF controls as compared to the second average occurrence exceeding a second threshold.

2. The method (600) of claim 1, wherein the captured presence sensor data is either stored locally in the control apparatus (300) or transferred to a remote server.

3. The method (600) of any one of the previous claims, wherein the increase in the occurrence of distinctive TURN-ON or TURN-OFF controls is detected in a sliding time window.

4. The method (600) of claim 3, wherein the duration of the sliding time window is predefined or configurable.2024PF80244165. The method (600) of claim 3 or 4, wherein the duration of the sliding time window is one of a week, a day, an hour, or another time unit configured by a user.

6. The method (600) of any one of the previous claims, wherein the increase in the occurrences of distinctive TURN-ON or TURN-OFF controls are detected by further distinguishing the occurrences according to a time period of a day and / or a day of a week.

7. The method (600) of any one of the previous claims, wherein the first time interval is equal to or slightly longer than a hold period, with the hold period defined as a time duration to turn off the one or more electronic devices since the most recent presence detection.

8. A control apparatus (300) configured to provide TURN-ON and TURN-OFF controls to one or more electronic devices based on presence detection, and to selectively capture presence sensor data for diagnosis purpose; the control apparatus (300) comprising: a presence sensor (301) configured to carry out presence detection for generating the TURN-ON and TURN-OFF controls; and a controller (302) configured to: measure, in a normal mode, a first average occurrence of distinctive TURNON controls with each distinctive TURN-ON control being a TURN-ON control followed by a TURN-OFF control within a first time interval; measure, in the normal mode, a second average occurrence of distinctive TURN-OFF controls with each distinctive TURN-OFF control being a TURN-OFF control followed by a TURN-ON control within a second time interval; control the control apparatus (300) to enter a diagnosis mode for data capturing; capture, in the diagnosis mode, presence sensor data selectively, such that only presence sensor data that triggers further distinctive TURN-ON controls and / or further distinctive TURN-OFF controls are captured; wherein the controller is configured to control the control apparatus (300) to enter the diagnosis mode when it receives a command or an error report from a user, or when it detects an increase in the occurrence of distinctive TURN-ON controls as compared to the first average occurrence exceeding a first threshold, or when it detects an increase in the2024PF8024417 occurrence of distinctive TURN-OFF controls as compared to the second average occurrence exceeding a second threshold.

9. The control apparatus (300) of claim 8 further comprising a local storage unit (303) or a communication interface (304), wherein the controller (302) is further configured to control the control apparatus (300) to store the captured presence sensor data in the local storage unit (303) or transfer the captured presence sensor data to a remote server via the communication interface (304).

10. The control apparatus (300) of claim 8 or 9, wherein the controller (302) is further configured to: control the control apparatus (300) to enter the diagnosis mode when detecting an increase in the occurrence of distinctive TURN-ON controls as compared to the first average occurrence exceeding a first threshold or detecting an increase in the occurrence of distinctive TURN-OFF controls as compared to the second average occurrence exceeding a second threshold.

11. The control apparatus (300) of claim 8 or 9 further comprising a user interface (305), wherein the controller (302) is further configured to: control the control apparatus (300) to enter the diagnosis mode when an error report is received from a user via the user interface (305).

12. A lighting fixture (200’) comprising a light source (201) and a control apparatus (300) according to any one of the previous claims 8-11; wherein the control apparatus (300) is configured to control the light source.

13. An electronic system (100) comprising one or more electronic devices (200) and a control apparatus (300) according to any one of the previous claims 8-11; wherein the control apparatus (300) is configured to control the one or more electronic devices (200); wherein at least one of the one or more electronic devices (200) is connected to the control apparatus (300) via a wired or wireless communication interface.

14. The electronic system (100) of claim 13, wherein the one or more electronic devices (200) are lighting devices, and the electronic system (100) is a lighting system.

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