Light fixture self-adaptive adjustment method and device based on environment perception

Abstract

The application discloses a lamp self-adaptive adjustment method and device based on environment sensing. The method comprises the following steps: sending an opening control instruction to the lamp when receiving the opening information; acquiring environment detection information collected by an Internet of Things sensor and judging whether the adjustment condition is met; if the adjustment condition is met, analyzing the environment detection information, acquiring adjustment configuration parameters corresponding to the analyzed environment characteristics, and sending corresponding adjustment control instructions to the lamp to adjust the lamp according to the adjustment configuration parameters. Through the above method, the environment detection information can be acquired based on the Internet of Things sensor to realize environment sensing, the adjustment configuration parameters are set based on the environment sensing, and corresponding adjustment control instructions are sent to realize the adjustment of the brightness and color temperature of the lamp based on the environment change, so that the user does not need to manually adjust, the convenience of the lamp adjustment is greatly improved, and the application effect of the lamp adjustment is improved.

Description

Technical Field

[0001] This invention relates to the technical field of Internet of Things (IoT) control, and in particular to a method and apparatus for adaptive adjustment of lighting fixtures based on environmental perception. Background Technology

[0002] Indoor lighting requires illumination, so lamps are typically installed, and users can adjust their brightness and color temperature according to their preferences. However, in practical applications, users need to control the lamps via remote control or mobile phone, resulting in poor ease of adjustment. Furthermore, various changes occur in indoor occupants and the environment, and the lamp adjustments cannot adapt to these changes, affecting the lighting effect. Therefore, existing technical methods for adjusting lamps suffer from poor ease of use. Summary of the Invention

[0003] This invention provides a method and apparatus for adaptive adjustment of lighting fixtures based on environmental perception, aiming to solve the problem of poor adjustment convenience in existing methods for adjusting lighting fixtures.

[0004] In a first aspect, embodiments of the present invention provide a method for adaptive adjustment of lighting fixtures based on environmental perception. The method is applied in a control terminal, which is communicatively connected to both an Internet of Things (IoT) sensor and the lighting fixture. The IoT sensor includes a thermopile sensor and an audio sensor. The method includes:

[0005] If an activation message is received, an activation control command is sent to the lamp.

[0006] The system acquires environmental detection information collected by the IoT sensor and determines whether the environmental detection information meets preset adjustment conditions.

[0007] If the adjustment conditions are met, the environmental detection information is analyzed according to the preset analysis rules to obtain the corresponding environmental analysis features;

[0008] The adjustment configuration parameters corresponding to the environmental analysis features are obtained according to the preset configuration model;

[0009] According to the adjustment configuration parameters, the corresponding adjustment control command is sent to the lamp to adjust the lamp.

[0010] Secondly, embodiments of the present invention provide an environment-aware adaptive lighting device, wherein the device is configured in a control terminal, the control terminal being communicatively connected to an Internet of Things (IoT) sensor and a lighting fixture, the IoT sensor including a thermopile sensor and an audio sensor, and the environment-aware adaptive lighting device being used to execute the environment-aware adaptive lighting method as described in the first aspect above, the device comprising:

[0011] An activation control command sending unit is used to send an activation control command to the lamp if an activation information is received.

[0012] An environmental detection information judgment unit is used to acquire environmental detection information collected by the Internet of Things sensor and to determine whether the environmental detection information meets preset adjustment conditions.

[0013] An environmental monitoring information parsing unit is used to parse the environmental monitoring information according to preset parsing rules if the adjustment conditions are met, so as to obtain the corresponding environmental parsing features.

[0014] The adjustment configuration parameter acquisition unit is used to acquire the adjustment configuration parameters corresponding to the environment parsing features according to the preset configuration model;

[0015] The adjustment control command sending unit is used to send corresponding adjustment control commands to the lamps according to the adjustment configuration parameters to adjust the lamps.

[0016] Thirdly, embodiments of the present invention also provide an adaptive lighting device based on environmental perception, wherein the device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0017] Memory, used to store computer programs;

[0018] When the processor executes the program stored in the memory, it implements the environment-aware adaptive adjustment method for luminaires as described in the first aspect above.

[0019] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the environment-aware adaptive adjustment method for lighting fixtures as described in the first aspect above.

[0020] This invention provides a method and apparatus for adaptive lighting adjustment based on environmental perception. The method includes: upon receiving an activation signal, sending an activation control command to the lighting fixture; acquiring environmental detection information collected by an IoT sensor and determining whether adjustment conditions are met; if met, parsing the environmental detection information and obtaining adjustment configuration parameters corresponding to the parsed environmental features; and sending a corresponding adjustment control command to the lighting fixture according to the adjustment configuration parameters to adjust the lighting fixture. Through this method, environmental perception can be achieved by acquiring environmental detection information based on an IoT sensor, and adjustment configuration parameters can be set and corresponding adjustment control commands issued based on the environmental perception to adjust the brightness and color temperature of the lighting fixture according to environmental changes. This eliminates the need for manual adjustment by the user, significantly improving the convenience of lighting fixture adjustment and enhancing its application effect. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 A flowchart illustrating the adaptive adjustment method for lighting fixtures based on environmental perception, provided in an embodiment of the present invention.

[0023] Figure 2 A schematic diagram illustrating an application scenario of the environmentally aware adaptive adjustment method for lighting fixtures provided in this embodiment of the invention;

[0024] Figure 3 A schematic block diagram of an environmentally aware adaptive lighting device provided in an embodiment of the present invention;

[0025] Figure 4 A schematic block diagram of a computer device provided for an embodiment of the present invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. 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.

[0027] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0028] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0029] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0030] Please see Figure 1 and Figure 2 , Figure 1 This is a flowchart of the adaptive lighting method based on environmental perception provided in an embodiment of the present invention. Figure 2 This is a schematic diagram illustrating an application scenario of the adaptive lighting adjustment method based on environmental perception provided in this embodiment of the invention. This method is applied to a control terminal 10, which is communicatively connected to both an IoT sensor 20 and a lighting fixture 30. The devices can be connected via wired or wireless communication through an IoT gateway device. The IoT sensor 20 includes a thermopile sensor 21 and an audio sensor 22. Typically, one lighting fixture 30 and at least one IoT sensor 20 are configured indoors. The adaptive lighting adjustment method is executed by application software installed in the control terminal 10. The control terminal 10 is the terminal device used to execute the adaptive lighting adjustment method based on environmental perception, adaptively adjusting and controlling the lighting fixture based on collected environmental detection information. The control terminal 10 may be an MCU control chip, FPGA logic circuit, etc., integrated on one side of the IoT gateway device. Figure 1 As shown, the method includes steps S110 to S150.

[0031] S110. If an activation message is received, an activation control command is sent to the lamp.

[0032] Users can input activation information into the control terminal. Upon receiving the activation information, the control terminal can send a corresponding activation control command to the lamp to turn it on. At this time, the lamp operates at the default brightness and default color temperature, for example, the default brightness is 70% of the maximum brightness and the default color temperature is 6500K (K is the unit of color temperature, Kelvin).

[0033] S120. Obtain the environmental detection information collected by the IoT sensor, and determine whether the environmental detection information meets the preset adjustment conditions.

[0034] Furthermore, the system acquires environmental detection information collected by IoT sensors. The control terminal can control the IoT sensors to periodically collect environmental detection information. For example, if the information collection cycle is configured to be 2 minutes in the control terminal, a set of environmental detection information will be collected every 2 minutes. The duration covered by a set of environmental detection information can be 5-20 seconds. For example, if the coverage duration can be set to 10 seconds, then the environmental information sensed within 10 seconds will be collected as a set of environmental detection information. The environmental detection information includes thermopile sensing information collected by the thermopile sensor and audio sensing information collected by the audio sensor. The system determines whether the acquired environmental detection information meets the preset adjustment conditions. If the adjustment conditions are met, the lighting fixtures will be adjusted; if the adjustment conditions are not met, the lighting fixtures will not be adjusted.

[0035] In one embodiment, step S120 specifically includes the following sub-steps: determining whether the thermopile sensing information in the environmental detection information meets the temperature judgment condition in the adjustment conditions; determining whether the audio sensing information in the environmental detection information meets the audio judgment condition in the adjustment conditions; if the temperature judgment condition or the audio judgment condition is met, determining that the environmental detection information meets the adjustment conditions; if neither the temperature judgment condition nor the audio judgment condition is met, determining that the environmental detection information does not meet the adjustment conditions.

[0036] First, it can be determined whether the thermopile sensing information in the environmental monitoring data meets the temperature judgment condition in the adjustment conditions. The thermopile sensing information is a monitoring map used to reflect the temperature at various points in the space environment. The thermopile information includes temperature detection values ​​at multiple points and multiple time points. The maximum temperature detection value is obtained by acquiring the maximum temperature detection value from the thermopile information, and then it is determined whether this maximum temperature detection value is greater than the temperature judgment threshold set in the temperature judgment condition. If the maximum temperature detection value is greater than the temperature judgment threshold, then the thermopile information is determined to meet the temperature judgment condition.

[0037] Further, it is determined whether the audio sensing information in the environmental detection information meets the audio judgment conditions in the adjustment conditions. The audio sensing information is the sensing information used to reflect the sound characteristics in the environment. The average loudness and maximum loudness of the audio sensing information are obtained, and it is determined whether the average loudness is greater than the average loudness threshold set in the audio judgment conditions, and whether the maximum loudness is greater than the maximum loudness threshold set in the audio judgment conditions. If the average loudness is greater than the average loudness threshold, or the maximum loudness is greater than the maximum loudness threshold, then the audio sensing information is determined to meet the audio judgment conditions. If the average loudness is not greater than the average loudness threshold, and the maximum loudness is not greater than the maximum loudness threshold, then the audio sensing information is determined not to meet the audio judgment conditions.

[0038] If the temperature or audio judgment condition is met, the environmental detection information is determined to meet the adjustment conditions, and the adjustment of the lamps is triggered. If neither the temperature nor the audio judgment condition is met, the environmental detection information is determined to not meet the adjustment conditions, and the adjustment of the lamps is not triggered.

[0039] In one embodiment, after step S120, the method further includes the step of: if the adjustment conditions are not met, sending a low-power operation command or a shutdown control command to the lamp.

[0040] If the adjustment conditions are not met, it indicates that there is no human activity in the current environment, or that people are in a resting state (such as being asleep or resting with their eyes closed). In this case, a low-power operation command or a shutdown command can be sent to the lamps to achieve energy-saving operation of the lamps and improve the energy-saving application effect of the lamps.

[0041] S130. If the adjustment conditions are met, the environmental detection information is analyzed according to the preset analysis rules to obtain the corresponding environmental analysis features.

[0042] If the adjustment conditions are met, the environmental monitoring information can be analyzed according to the analysis rules to obtain environmental analysis features. Since the environmental monitoring information includes thermopile induction information and audio induction information, it is necessary to analyze the thermopile induction information and audio induction information separately to obtain the corresponding environmental analysis features. These environmental analysis features can then be used to characterize the activities of personnel in the current environment.

[0043] In one embodiment, step S130 specifically includes the following sub-steps: parsing the thermopile sensing information in the environmental detection information according to the thermopile parsing model in the parsing rules to obtain the corresponding temperature parsing features; parsing the audio sensing information in the environmental detection information according to the audio parsing model in the parsing rules to obtain the corresponding audio parsing features; and combining the temperature parsing features with the audio parsing features to obtain the corresponding environmental parsing features.

[0044] First, the thermopile-induced information can be analyzed using the thermopile analytical model in the analytical rules to obtain temperature analytical features. These features can be used to reflect the level of physical activity of people in the current environment. Next, the audio-induced information can be analyzed using the audio analytical model in the analytical rules to obtain corresponding audio analytical features. These features are used to reflect the emotional state of people's speech in the current environment. Combining the obtained temperature and audio analytical features yields the corresponding environmental analytical features.

[0045] In one embodiment, the step of parsing the thermopile sensing information in the environmental detection information according to the thermopile analysis model in the analysis rules to obtain the corresponding temperature analysis features includes: binarizing the thermopile sensing information according to the temperature analysis parameters in the thermopile analysis model to obtain the corresponding binarized information; and extracting the feature parameters corresponding to each temperature feature item from the binarized information according to the temperature feature items in the thermopile analysis model, as the temperature analysis features.

[0046] Specifically, the thermopile induction information can be binarized based on the temperature analysis parameters in the thermopile analytical model. The thermopile induction information includes thermopile induction maps corresponding to multiple time points. The temperature analysis parameters include a reference temperature range. It can be determined whether the temperature value of each point in the thermopile induction map falls within the reference temperature range. If it does, the value of that point is set to "1"; if it does not, the value is set to "0". By determining the value of each point, the thermopile induction information is binarized, resulting in binarized information corresponding to each thermopile induction map. The reference temperature range matches human body temperature; for example, it can be set to [35.2℃, 37.9℃]. The thermopile analytical model contains multiple temperature feature terms. Further, feature parameters corresponding to each temperature feature term are extracted from the binarized information based on these temperature feature terms, serving as temperature analysis features. Each temperature feature term corresponds to one feature parameter. If the temperature feature includes the percentage of effective sites and the percentage of sites changing, then the percentage of sites with a value of "1" in the binarized information of each thermopile induction map can be obtained and the average value calculated to obtain the feature parameter corresponding to the percentage of effective sites. Further, the number of changing sites in the binarized information of adjacent thermopile induction maps can be obtained. If the value of the same site in the binarized information of adjacent thermopile induction maps changes from "0" to "1" or from "1" to "0", then that site is determined to be a changing site, and the corresponding number of changing sites is counted. If there are n thermopile induction maps, then there are n-1 sets of changing sites. The ratio between the number of changing sites and the total number of sites in a single thermopile induction map is calculated and the average value is calculated to obtain the feature parameter corresponding to the percentage of sites changing. Combining the feature parameters corresponding to each temperature feature yields the temperature analytical feature.

[0047] In one embodiment, the step of parsing the audio sensing information in the environmental detection information according to the audio parsing model in the parsing rules to obtain the corresponding audio parsing features includes: filtering the audio sensing information according to a preset audio segment in the audio parsing model to obtain valid audio corresponding to the preset audio segment; and extracting feature parameters corresponding to each audio feature item from the valid audio according to the audio feature items in the audio parsing model, as the audio parsing features.

[0048] The audio parsing model has preset audio segments, which can be used to filter audio sensing information. This means that audio information within the preset audio segments is selected as the filtered, valid audio. The audio sensing information includes audio information corresponding to each audio frequency. For example, if the preset audio segment is set to [200Hz, 4000Hz], then audio information with frequencies within that preset audio segment can be selected as valid audio.

[0049] Furthermore, based on the audio feature terms in the audio analysis model, the feature parameters corresponding to each audio feature term are obtained in advance from the effective audio. For example, audio feature terms include timbre features, loudness features, and speech rate features. The mean loudness of the effective audio can be obtained as the feature parameter corresponding to the loudness feature. The speech duration and number of words in the effective audio can be obtained, and the ratio between the number of words and the speech duration can be calculated to obtain the feature parameter corresponding to the speech rate feature. Specifically, the Mel-spectral features of the effective audio can be extracted, and speech recognition can be performed on the Mel-spectral features to obtain text information. Based on the text information, the number of words and the corresponding speech duration can be determined. The loudness of each frequency band in the effective audio can be obtained, and the ratio between the loudness of each frequency band can be calculated to obtain the corresponding timbre feature ratio, which is used as the feature parameter corresponding to the timbre feature. For example, multiple frequency bands can be set: low frequency band [200Hz, 599Hz], mid frequency band [600Hz, 1499Hz], mid-high frequency band [1500Hz, 2799Hz], and high frequency band [2800Hz, 4000Hz]. The audio loudness of each frequency band in the effective audio can then be obtained as P1, P2, P3, and P4, respectively. Furthermore, the timbre feature ratios can be obtained as P1 / P2, P1 / P3, P1 / P4, P2 / P3, P2 / P4, and P3 / P4, respectively. Combining the feature parameters corresponding to each audio feature item yields the corresponding audio analytical features.

[0050] S140. Obtain the adjustment configuration parameters corresponding to the environmental analysis features according to the preset configuration model.

[0051] Furthermore, the adjustment configuration parameters corresponding to the environmental analysis characteristics can be obtained based on the configuration model, that is, the configuration parameters that match the environmental analysis characteristics and are used for lighting adjustment control can be obtained.

[0052] In one embodiment, step S140 specifically includes the following sub-steps: identifying the environmental parsing features according to the environmental identification rules in the configuration model to obtain the corresponding environmental feature parameters; and performing parameter configuration mapping on the environmental feature parameters according to the mapping rules in the configuration model to obtain the corresponding adjustment configuration parameters.

[0053] Specifically, the environmental features can be identified according to environmental recognition rules to obtain corresponding environmental feature parameters. The environmental recognition rules can be based on a neural network constructed using artificial intelligence. These rules can be configured with an input layer, an intermediate layer, and an output layer. The input layer includes multiple input nodes, each intermediate layer has multiple intermediate nodes, and the environmental recognition rule can have one or more intermediate layers. The output layer includes multiple output nodes. There is a correlation formula between the input nodes and the intermediate nodes of the first intermediate layer, between the intermediate nodes of adjacent intermediate layers, and between the output nodes and the intermediate nodes of the last intermediate layer. Each input node in the input layer corresponds to a feature parameter in the input environmental features. The intermediate layers perform correlation analysis on the input feature parameters, and the corresponding result is output from the output layer. The output layer can be configured with two output nodes, each outputting a feature value. For example, one output node might output a feature value corresponding to an activity coefficient; a higher activity coefficient indicates higher physical activity. The other output node might output a feature value corresponding to an emotion coefficient; a higher emotion coefficient indicates more excited vocal emotions. The two obtained feature values ​​are both in the range of [0,1]; the feature values ​​of the two output nodes can be combined as the corresponding environmental feature parameters.

[0054] Before using environmental recognition rules, they can be trained. Specifically, a training dataset based on historical data can be constructed to train the environmental recognition rules. For example, multiple sets of environmental parsing features can be obtained from historical data, along with user-reported physical activity scores and voice emotion scores from questionnaires. The physical activity scores are converted into corresponding target activity coefficients, and the voice emotion scores are converted into corresponding target emotion coefficients. Each set of environmental parsing features, along with the corresponding target activity coefficient and target emotion coefficient, forms a training data point in the training dataset. The training data is then input into the environmental recognition rules, and the output activity coefficients and emotion coefficients are obtained. Gradient descent is performed based on the differences between the target activity coefficients and target emotion coefficients and the actual activity coefficients and emotion coefficients, thereby adjusting the parameters of the association formula in the environmental recognition rules in reverse, achieving iterative training. The environmental recognition rules obtained after training are then used for recognition applications.

[0055] Furthermore, the configuration model also includes mapping rules, which in turn include a pattern mapping table. This table contains multiple adjustment modes, each corresponding to a set of parameter ranges (e.g., an activity range [0.5, 0.75], an emotion range [0.3, 0.6]). The obtained environmental feature parameters can be compared with the parameter ranges in the pattern mapping table to obtain the adjustment mode corresponding to the parameter range that matches the environmental feature parameters, thus identifying the target adjustment mode. The target adjustment mode includes target brightness, base color temperature, and adjustment interval time, among other parameters.

[0056] Furthermore, the mapping rules also include an adjustment range function and a rate of change function. The adjustment range function determines the color temperature adjustment range corresponding to the environmental characteristic parameters and the base color temperature, while the rate of change function determines the rate of change corresponding to the environmental characteristic parameters. The ratio of the activity coefficient to the natural constant in the environmental characteristic parameters can be calculated based on the adjustment range function. This ratio is then raised to the power of the natural constant and subtracted by one. The difference is divided by two to obtain the corresponding adjustment coefficient r. Based on the adjustment coefficient r, the corresponding adjustment interval [1-r, 1+r] can be determined. The lower and upper limits of the adjustment interval are multiplied by the base color temperature, and the resulting products are set as the upper and lower limits of the color temperature adjustment range, thus obtaining the color temperature adjustment range corresponding to the environmental characteristic parameters and the base color temperature. The color temperature adjustment range shall not exceed the preset color temperature range of the lamp. If the upper limit of the interval in the obtained product result exceeds the preset color temperature range, the maximum value of the preset color temperature range shall be used as the upper limit of the color temperature adjustment range. If the lower limit of the interval in the obtained product result exceeds the preset color temperature range, the minimum value of the preset color temperature range shall be used as the lower limit of the color temperature adjustment range.

[0057] The product of the activity coefficient and the emotion coefficient in the environmental characteristic parameters is calculated based on the rate of change function. The square root of this product is then calculated, raised to the power of the natural constant, and multiplied by the preset rate coefficient to obtain the final product value. The difference between the maximum and minimum values ​​within the preset color temperature range is used to calculate the corresponding adjustment difference. Dividing this adjustment difference by the product value gives the set rate of change. Combining the obtained target adjustment mode with the color temperature adjustment range and rate of change yields the corresponding adjustment configuration parameters.

[0058] S150. Send the corresponding adjustment control command to the lamp according to the adjustment configuration parameters to adjust the lamp.

[0059] Based on the obtained adjustment configuration parameters, corresponding adjustment control commands are sent to the luminaires to adjust their brightness. Specifically, a brightness adjustment control command can be sent to the luminaires based on the target brightness in the adjustment configuration parameters to adjust the brightness of the luminaires, and a corresponding color temperature adjustment control command can be sent to the luminaires based on the color temperature adjustment range and rate of change to adjust the color temperature of the luminaires; the interval between sending the two sets of color temperature adjustment control commands is equal to the adjustment interval time set in the adjustment configuration parameters.

[0060] After a preset information collection period, the process can return to step S120. If a shutdown message is received, a shutdown command can be sent to the light fixture to control it to turn off, thereby achieving energy-saving effects.

[0061] The adaptive lighting adjustment method based on environmental perception provided in this invention includes: an adaptive lighting adjustment method and apparatus based on environmental perception. The method includes: upon receiving an activation information, sending an activation control command to the lighting fixture; acquiring environmental detection information collected by an IoT sensor and determining whether adjustment conditions are met; if met, parsing the environmental detection information and obtaining adjustment configuration parameters corresponding to the parsed environmental features; and sending corresponding adjustment control commands to the lighting fixture according to the adjustment configuration parameters to adjust the lighting fixture. Through this method, environmental detection information can be acquired based on an IoT sensor to achieve environmental perception; adjustment configuration parameters can be set based on environmental perception, and corresponding adjustment control commands can be issued to achieve adjustment of the brightness and color temperature of the lighting fixture based on environmental changes. This eliminates the need for manual adjustment by the user, significantly improving the convenience of lighting fixture adjustment and enhancing its application effect.

[0062] This invention also provides an environment-aware adaptive lighting device, which can be configured in a control terminal 10. The control terminal 10 is communicatively connected to an IoT sensor 20 and a lighting fixture 30. The devices can be connected via wired or wireless communication through an IoT gateway device. The IoT sensor 20 includes a thermopile sensor 21 and an audio sensor 22. This environment-aware adaptive lighting device is used to execute any embodiment of the aforementioned environment-aware adaptive lighting method. Specifically, please refer to... Figure 3 , Figure 3 This is a schematic block diagram of an environmentally aware adaptive lighting device provided in an embodiment of the present invention.

[0063] like Figure 3 As shown, the ambient perception-based adaptive lighting device 100 includes an on-control command sending unit 110, an ambient detection information judgment unit 120, an ambient detection information parsing unit 130, an adjustment configuration parameter acquisition unit 140, and an adjustment control command sending unit 150.

[0064] The power control command sending unit 110 is used to send a power control command to the lamp if it receives power information.

[0065] The environmental detection information judgment unit 120 is used to acquire the environmental detection information collected by the Internet of Things sensor and to determine whether the environmental detection information meets the preset adjustment conditions.

[0066] The environmental monitoring information parsing unit 130 is used to parse the environmental monitoring information according to a preset parsing rule if the adjustment conditions are met, so as to obtain the corresponding environmental parsing features.

[0067] The adjustment configuration parameter acquisition unit 140 is used to acquire the adjustment configuration parameters corresponding to the environment analysis features according to the preset configuration model.

[0068] The adjustment control command sending unit 150 is used to send corresponding adjustment control commands to the lamps according to the adjustment configuration parameters to adjust the lamps.

[0069] The environmentally-aware adaptive lighting device provided in this embodiment of the invention applies the aforementioned environmentally-aware adaptive lighting method. The method includes: an environmentally-aware adaptive lighting method and device. The method includes: upon receiving an activation information, sending an activation control command to the lighting fixture; acquiring environmental detection information collected by an IoT sensor and determining whether adjustment conditions are met; if met, parsing the environmental detection information and obtaining adjustment configuration parameters corresponding to the parsed environmental features; and sending corresponding adjustment control commands to the lighting fixture according to the adjustment configuration parameters to adjust the lighting fixture. Through this method, environmental detection information can be acquired based on an IoT sensor to achieve environmental perception; adjustment configuration parameters can be set based on environmental perception, and corresponding adjustment control commands can be issued to achieve adjustment of the brightness and color temperature of the lighting fixture based on environmental changes. This eliminates the need for manual adjustment by the user, significantly improving the convenience of lighting fixture adjustment and enhancing its application effect.

[0070] The aforementioned environmentally-aware adaptive lighting control device can be implemented as a computer program, which can be used in various ways, such as... Figure 4 The computer device shown runs on the computer. The computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor; when the computer device executes the computer program, it implements the environmentally aware adaptive lighting method as described in the above embodiments.

[0071] Please see Figure 4 , Figure 4 This is a schematic block diagram of a computer device provided in an embodiment of the present invention. The computer device may be a terminal device for executing an environment-aware adaptive adjustment method for lighting fixtures, receiving audio information, and controlling the lighting source devices 31 included in the lighting source device group 30.

[0072] See Figure 4 The computer device 500 includes a processor 502, a memory, and a communication interface 505 connected via a system bus 501. The memory may include a storage medium 503 and internal memory 504.

[0073] The storage medium 503 may store an operating system 5031 and a computer program 5032. When the computer program 5032 is executed, it causes the processor 502 to execute an environment-aware adaptive adjustment method for the lighting fixtures. The storage medium 503 may be a volatile storage medium or a non-volatile storage medium.

[0074] The processor 502 provides computing and control capabilities to support the operation of the entire computer device 500.

[0075] The internal memory 504 provides an environment for the operation of the computer program 5032 in the storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute an environment-aware adaptive adjustment method for lighting fixtures.

[0076] This communication interface 505 is used for network communication, such as providing data transmission. Those skilled in the art will understand that... Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the computer device 500 to which the present invention is applied. The specific computer device 500 may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0077] The processor 502 is used to run the computer program 5032 stored in the memory to implement the corresponding functions in the above-mentioned adaptive lighting method based on environmental perception.

[0078] Those skilled in the art will understand that Figure 4 The embodiments of the computer device shown do not constitute a limitation on the specific configuration of the computer device. In other embodiments, the computer device may include more or fewer components than illustrated, or combine certain components, or have different component arrangements. For example, in some embodiments, the computer device may include only memory and a processor. In such embodiments, the structure and function of the memory and processor are different from those shown. Figure 4 The embodiments shown are consistent and will not be described again here.

[0079] It should be understood that, in this embodiment of the invention, the processor 502 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0080] In another embodiment of the invention, a computer-readable storage medium is provided. This computer-readable storage medium may be volatile or non-volatile. The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps included in the above-described environment-aware adaptive luminaire adjustment method.

[0081] Those skilled in the art will readily understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention.

[0082] In the embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Units with the same function may be grouped into one unit. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or units, or it may be an electrical, mechanical, or other form of connection.

[0083] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of the present invention, depending on actual needs.

[0084] Furthermore, 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. The integrated unit can be implemented in hardware or as a software functional unit.

[0085] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a computer-readable storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned computer-readable storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), magnetic disks, or optical disks.

[0086] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for adaptive adjustment of lighting fixtures based on environmental perception, characterized in that, The method is applied in a control terminal, which is communicatively connected to an IoT sensor and a lighting fixture. The IoT sensor includes a thermopile sensor and an audio sensor. The method includes: If an activation message is received, an activation control command is sent to the lamp. The system acquires environmental detection information collected by the IoT sensor and determines whether the environmental detection information meets preset adjustment conditions. If the adjustment conditions are met, the environmental detection information is analyzed according to the preset analysis rules to obtain the corresponding environmental analysis features; The adjustment configuration parameters corresponding to the environmental analysis features are obtained according to the preset configuration model; According to the adjustment configuration parameters, send the corresponding adjustment control command to the lamp to adjust the lamp; The step of parsing the environmental detection information according to preset parsing rules to obtain corresponding environmental parsing features includes: The thermopile induction information in the environmental detection information is analyzed according to the thermopile analysis model in the analysis rules to obtain the corresponding temperature analysis features; The audio sensing information in the environmental detection information is analyzed according to the audio analysis model in the analysis rules to obtain the corresponding audio analysis features; The temperature resolution feature is combined with the audio resolution feature to obtain the corresponding environmental resolution feature; The step of analyzing the thermopile induction information in the environmental detection information according to the thermopile analytical model in the analytical rules to obtain the corresponding temperature analytical features includes: The thermopile induction information is binarized according to the temperature analysis parameters in the thermopile analytical model to obtain the corresponding binarized information. The thermopile induction information includes thermopile induction maps corresponding to multiple time points. It is determined whether the temperature value of each point in the thermopile induction map is within the reference temperature range of the temperature analysis parameters. If it is within the reference temperature range, the value of the point is determined to be "1"; if it is not within the reference temperature range, the value of the point is determined to be "0". The corresponding binarized information is obtained by determining the value of each point. Based on the temperature feature terms in the thermopile analytical model, feature parameters corresponding to each temperature feature term are extracted from the binarized information and used as the temperature analytical features. The temperature feature terms include the effective site percentage and the site change percentage. The percentage of sites with a value of "1" in the binarized information of each thermopile induction map is obtained and the average value is calculated to obtain the feature parameters corresponding to the effective site percentage. The number of changing sites in the binarized information of adjacent thermopile induction maps is obtained, the ratio between the number of changing sites and the total number of sites in a single thermopile induction map is calculated and the average value is calculated to obtain the feature parameters corresponding to the site change percentage. The temperature analytical features are used to reflect the level of limb activity of personnel in the current environment.

2. The adaptive lighting method based on environmental perception according to claim 1, characterized in that, The determination of whether the environmental detection information meets the preset adjustment conditions includes: Determine whether the thermopile induction information in the environmental detection information meets the temperature judgment condition in the adjustment conditions; Determine whether the audio sensing information in the environmental detection information meets the audio judgment condition in the adjustment conditions; If the temperature judgment condition or the audio judgment condition is met, the environmental detection information is determined to meet the adjustment condition. If neither the temperature judgment condition nor the audio judgment condition is met, it is determined that the environmental detection information does not meet the adjustment condition.

3. The adaptive lighting method based on environmental perception according to claim 2, characterized in that, The step of parsing the audio sensing information in the environmental detection information according to the audio parsing model in the parsing rules to obtain the corresponding audio parsing features includes: The audio sensing information is filtered according to the preset audio segments in the audio parsing model to obtain the valid audio corresponding to the preset audio segments; Based on the audio feature terms in the audio parsing model, feature parameters corresponding to each audio feature term are extracted from the valid audio and used as the audio parsing features.

4. The adaptive luminaire adjustment method based on environmental perception according to any one of claims 1-3, characterized in that, The step of obtaining the adjustment configuration parameters corresponding to the environmental analysis features based on the preset configuration model includes: The environmental parsing features are identified according to the environmental identification rules in the configuration model to obtain the corresponding environmental feature parameters; The environmental feature parameters are mapped according to the mapping rules in the configuration model to obtain the corresponding adjustment configuration parameters.

5. The adaptive adjustment method for luminaires based on environmental perception according to any one of claims 1-2, characterized in that, After determining whether the environmental detection information meets the preset adjustment conditions, the method further includes: If the adjustment conditions are not met, a low-power operation command or a shutdown control command is sent to the lamp.

6. A lighting fixture adaptive adjustment device based on environmental perception, characterized in that, The device is configured in a control terminal, which is communicatively connected to both an IoT sensor and a lighting fixture. The IoT sensor includes a thermopile sensor and an audio sensor. The environment-aware adaptive lighting fixture adjustment device is used to execute the environment-aware adaptive lighting fixture adjustment method as described in any one of claims 1-5. The device includes: An activation control command sending unit is used to send an activation control command to the lamp if an activation information is received. An environmental detection information judgment unit is used to acquire environmental detection information collected by the Internet of Things sensor and to determine whether the environmental detection information meets preset adjustment conditions. An environmental monitoring information parsing unit is used to parse the environmental monitoring information according to preset parsing rules if the adjustment conditions are met, so as to obtain the corresponding environmental parsing features. The adjustment configuration parameter acquisition unit is used to acquire the adjustment configuration parameters corresponding to the environment parsing features according to the preset configuration model; The adjustment control command sending unit is used to send corresponding adjustment control commands to the lamps according to the adjustment configuration parameters to adjust the lamps.

7. A computer device, characterized in that, The device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; When a processor executes a program stored in a memory, it implements the ambient-aware adaptive adjustment method for luminaires as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the environmentally-aware adaptive adjustment method for luminaires as described in any one of claims 1 to 5.

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