Campus light environment intelligent treatment method and system based on OEOT

Abstract

The embodiment of the invention relates to the technical field of information, in particular to an OEOT-based campus light environment intelligent treatment method and system. The method comprises the following steps: reading environment color temperature and environment light intensity detected by an environment light color temperature sensor and an environment light intensity sensor arranged in a classroom; the human body approaching state of the human body sensor on the learning position on each learning table is polled according to a preset period, a learning position list with human body approaching is obtained, the learning positions in the learning position list are traversed, and the following steps are executed: video data and sound data obtained by the camera and the microphone on the learning position within a preset time length are read; identifying a personnel activity state according to the video data and the sound data; generating a light supplementing scheme according to the personnel activity state, the environment color temperature and the environment light intensity; controlling the brightness and color temperature of the double-color LED lamp according to the light supplementing scheme; and correcting the color temperature of the double-color LED lamp according to the detection value of the color temperature sensor of the learning bit.

Description

Technical Field

[0001] Multiple embodiments of this specification relate to the field of information technology, and more particularly to an intelligent governance method and system for campus light environment based on OEOT. Background Art

[0002] With the development of information technology and the improvement of people's requirements for the quality of learning and working environments, how to optimize the light environment on campus has become an important research direction. Traditional lighting systems often use lamps with fixed brightness and color temperature, and cannot be flexibly adjusted according to actual needs, which to a certain extent affects the learning efficiency of students and the teaching effect of teachers. Especially in different time periods or weather conditions, the change of external natural light will have a significant impact on the indoor light, making the fixed lighting settings difficult to meet the best visual experience all day long. Therefore, it is necessary to study intelligent governance technologies for campus light environment. Summary of the Invention

[0003] Multiple embodiments of this specification describe an intelligent governance method and system for campus light environment based on OEOT.

[0004] In a first aspect, an embodiment of this specification provides an intelligent governance method for campus light environment based on OEOT, including the steps of: Reading the ambient color temperature and ambient light intensity detected by the ambient light color temperature sensor and the ambient light intensity sensor set in the classroom; Polling the human proximity status of the human body sensors on each study position on each study desk at a preset period to obtain a list of study positions with human proximity, and traversing the study positions in the list of study positions, and performing the following steps: Reading the video data and sound data obtained by the cameras and microphones on the study positions for a preset time length; Identifying the personnel activity status according to the video data and the sound data; Generating a supplementary lighting plan according to the personnel activity status, the ambient color temperature and the ambient light intensity; Controlling the brightness and color temperature of the dual-color LED lamp according to the supplementary lighting plan; Correcting the color temperature of the dual-color LED lamp according to the detection value of the color temperature sensor of the study position.

[0005] In a second aspect, an embodiment of this specification provides an intelligent governance system for campus light environment based on OEOT, including: An environment module that reads the ambient color temperature and ambient light intensity detected by the ambient light color temperature sensor and the ambient light intensity sensor set in the classroom; The processing module polls the human proximity status of the human body sensors on each study position on the study table at a preset period, obtains a list of study positions with human proximity, traverses the study positions in the list of study positions, and triggers the following modules to work: The reading module reads the video data and sound data obtained by the camera and microphone on the study position for a preset time length; The recognition module recognizes the personnel activity status according to the video data and the sound data; The calculation module generates a supplementary lighting scheme according to the personnel activity status, the ambient color temperature and the ambient light intensity; The control module controls the brightness and color temperature of the dual-color LED lamp according to the supplementary lighting scheme; The correction module corrects the color temperature of the dual-color LED lamp according to the detection value of the color temperature sensor of the study position.

[0006] In a third aspect, an embodiment of the present specification provides an electronic device, including a processor and a memory; The processor is connected to the memory; The memory is used to store executable program codes; The processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to execute the method described in any of the above aspects.

[0007] In a fourth aspect, an embodiment of the present specification provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method described in any of the above aspects is implemented.

[0008] In a fifth aspect, an embodiment of the present specification provides a computer program product, including a computer program, and when the computer program is executed by a processor, the method described in any of the above aspects is implemented.

[0009] The beneficial effects brought by the technical solutions provided by some embodiments of the present specification at least include: In multiple embodiments of the present specification, the intelligent campus light environment governance solution provided can provide more suitable lighting conditions for learning and rest by real-time monitoring of the ambient color temperature and light intensity in the classroom and dynamically adjusting the color temperature and brightness of the lights according to different activity states of students. It can adaptively change the lighting according to the specific personnel activity status on different study positions, realizing a more personalized lighting experience. Selecting appropriate color temperature and light intensity can not only protect eyesight, but also affect the spatial atmosphere and people's psychological state, which helps to improve work efficiency and quality of life. Using Internet of Things technology and sensor networks, the intelligent management and control of the classroom lighting system are realized, reducing the need for manual intervention and improving efficiency.

[0010] Other features and advantages of multiple embodiments of this specification will be further revealed in the following detailed description and the accompanying drawings. Description of the Drawings

[0011] To more clearly illustrate the technical solutions in the embodiments of this specification, the accompanying drawings required for the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of this specification. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0012] Figure 1 Schematic flowchart of the intelligent governance method for the campus light environment provided by the embodiments of this specification.

[0013] Figure 2 Schematic diagram of the classroom provided by the embodiments of this specification.

[0014] Figure 3 Schematic diagram of the architecture of the intelligent governance system for the campus light environment provided by the embodiments of this specification.

[0015] Figure 4 Schematic diagram of the structure of the study desk provided by the embodiments of this specification.

[0016] Figure 5 Schematic diagram of the structure of the crossbeam provided by the embodiments of this specification.

[0017] Figure 6 Schematic diagram of the structure of the partition provided by the embodiments of this specification.

[0018] Figure 7 Schematic flowchart of the method for identifying the activity status of personnel provided by the embodiments of this specification.

[0019] Figure 8 Schematic flowchart of the method for tension scoring provided by the embodiments of this specification.

[0020] Figure 9 Schematic diagram of the intelligent governance system for the campus light environment provided by the embodiments of this specification.

[0021] Figure 10 Schematic diagram of the electronic device provided by the embodiments of this specification. Detailed Description of the Embodiments

[0022] The technical solutions in the embodiments of this specification will be explained and illustrated below with reference to the accompanying drawings of the embodiments of this specification. However, the following embodiments are only the preferred embodiments of this specification, not all of them. Based on the embodiments in the implementation manners, other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of this specification.

[0023] In the description, claims, and the above-mentioned drawings of this specification, the terms "first", "second", "third", etc. are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally further include steps or units not listed, or may optionally further include other steps or units inherent to these processes, methods, products, or devices.

[0024] In the following description, the use of terms such as "inside", "outside", "above", "below", "left", "right", etc. to indicate orientation or positional relationship is only for the convenience of describing embodiments and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this specification.

[0025] The data involved in this application are all information and data authorized by users or fully authorized by all parties, and the collection of relevant data complies with the relevant laws, regulations, and standards of the relevant countries and regions.

[0026] Before introducing the technical solutions described in this specification, the application scenarios and related technologies of the technical solutions will be introduced.

[0027] OEOT (Optimized Environmental Optical Technology) is one of the cutting-edge technologies and is suitable for the light environment governance in the campus environment. It uses a sensor network to monitor the indoor environmental color temperature and environmental light intensity in real time, and combines with a human body sensor 41 to judge whether a learning position is occupied and its specific activity state, so as to achieve precise supplementary light control. For example, when it is recognized that a student is reading, the system will automatically adjust the light to a low color temperature and high brightness mode to relieve eye fatigue; while during the rest period, it will switch to a low color temperature and natural light brightness mode to create a relaxing atmosphere. Although the OEOT technology can be used to improve the quality of the campus light environment and provide a more suitable light environment for students. However, the application of the OEOT technology relies on the recognition of the personnel state. And currently, the recognition of the personnel state needs to be obtained from the teaching plan. It cannot be targeted at the real-time switching changes of the personnel state, nor can it make adaptive lighting changes for different personnel.

[0028] In view of the fact that this application will involve some professional terms, therefore, the following will first introduce these professional terms.

[0029] Color temperature Color temperature is a method of representing the color characteristics of a light source, measured in Kelvin (K). It is based on the color of light emitted by an idealized blackbody radiator when heated to different temperatures. Low color temperatures (such as 2000K - 3000K) usually appear as warm tones, such as yellow or orange, giving people a warm and comfortable feeling; while high color temperatures (such as above 5000K) appear as cold tones, such as blue, giving a fresh and bright feeling. In lighting design, choosing the appropriate color temperature can affect the spatial atmosphere and people's psychological state.

[0030] Dual - color LED lamp 54 The dual - color LED lamp 54 refers to an LED lighting fixture that can emit two different color temperature lights. Such fixtures usually have two types of LED chips built - in. One is used to produce warm white light (lower color temperature), and the other is used to produce cold white light (higher color temperature). By adjusting the brightness ratio of these two LEDs, the dual - color LED lamp 54 can adjust the color temperature of the output light within a large range, thus adapting to different usage requirements and environmental conditions. For example, in a work environment where concentration is required, a higher color temperature setting may be preferred, while in a rest area, a lower color temperature can be chosen to create a relaxing atmosphere.

[0031] Luminous intensity Luminous intensity refers to the luminous intensity of a light source in a specific direction, and the international unit is candela (cd). It is a physical quantity that measures the luminous ability of a light source in a certain direction. Simply put, the higher the luminous intensity, the stronger the light emitted from the light source. For indoor lighting, luminous intensity directly affects the brightness and visual comfort of the space. Appropriate luminous intensity not only helps protect eyesight but also improves work efficiency and quality of life. In practical applications, in addition to considering luminous intensity, factors such as uniformity and contrast also need to be comprehensively considered to ensure the overall lighting effect.

[0032] This specification provides an intelligent governance method for campus light environment based on OEOT. Please refer to the appendix Figure 1 , including the steps: Step S101) Read the ambient color temperature and ambient light intensity detected by the ambient light color temperature sensor 21 and the ambient light intensity sensor 22 set in the classroom; Step S102) Poll the human proximity status of the human sensors 41 on each learning position on each study desk 10 at a preset cycle to obtain a list of learning positions with human proximity. Traverse the learning positions in the list of learning positions and perform the following steps: Step S103) Read the video data and sound data obtained by the camera 43 and the microphone 42 on the learning position for a preset time length; Step S104) Identify the personnel activity status according to the video data and the sound data; Step S105) Generate a supplementary lighting scheme based on the personnel activity status, ambient color temperature, and ambient light intensity; Step S106) Control the brightness and color temperature of the dual-color LED lamp 54 according to the supplementary lighting scheme; Step S107) Correct the color temperature of the dual-color LED lamp 54 according to the detection value of the color temperature sensor 45 at the learning position.

[0033] Please refer to the appendix Figure 2 , which shows the layout of the study desk 10 and its examples in the classroom where the technical solution described in this specification is applied. There are multiple study desks 10 placed in a classroom, and each study desk 10 is equipped with independent sensors and controllable light sources. Please refer to the appendix Figure 3 , the technical solution described in this specification uses Internet of Things technology. An ambient light color temperature sensor 21 and an ambient light intensity sensor 22 are set in each classroom. Both the ambient light color temperature sensor 21 and the ambient light intensity sensor 22 are connected to a server 30. A human body sensor 41, a microphone 42, a camera 43, a light controller 44, and a color temperature sensor 45 are set on each study desk 10. The human body sensor 41, the microphone 42, the camera 43, the light controller 44, and the color temperature sensor 45 are all connected to the server 30. The server 30 serves as the control center of the OEOT technology, which can not only read the data of all sensors but also independently control the lighting of each learning position on each study desk 10 through each light controller 44.

[0034] Please refer to the appendix Figure 4 and the appendix Figure 5 , in an embodiment, the study desk 10 includes four learning positions. The study desk 10 includes a desktop, and columns 51 and a crossbeam 53 are arranged on the desktop. The crossbeam 53 is supported by the columns 51. Four dual-color LED lamps 54, a manual switch 52, two partitions 55, four groups of sensors corresponding to each learning position, and a light controller 44 are arranged on the crossbeam 53. Each group of sensors includes a human body sensor 41, a microphone 42, a camera 43, and a color temperature sensor 45. The manual switch 52 is used to turn on the dual-color LED lamp 54, the light controller 44, and the sensors. After the manual switch 52 is turned on, the light controller 44 and the sensors will be connected to the server 30, and the server 30 will be able to receive the detection values of the relevant sensors and send control instructions to the light controller 44. The light controller 44 can control the dual-color LED lamp 54 according to the control instructions.

[0035] Please refer to the appendix Figure 6, a partition 55 is located between two dual-color LED lights 54 to separate the interference between the two dual-color LED lights 54. The partition 55 includes a base 551, a reflective layer 552 and an inclined plate 553. The base 551 is fixed on the cross beam 53 and located between the two dual-color LED lights 54. The inclined plate 553 is installed on the base 551, and both sides of the inclined plate 553 have inclined angles. Reflective layers 552 are attached to both sides of the inclined plate 553.

[0036] In another embodiment, the study table 10 only includes two study positions on one side. In this embodiment, the orientations of all the study positions can be unified in one direction. This is suitable for the situation where all students participate in the same activity. On the other hand, the study table 10 can also only include one study position. It is only necessary to adaptively reduce the dual-color LED lights 54 and the sensor group.

[0037] The human body sensor 41 is implemented in a manner already disclosed in the art. Exemplarily, an infrared sensor is used as the human body sensor 41.

[0038] Please refer to the appendix Figure 7 , the method for identifying the activity state of a person according to the video data and the audio data includes: Step S201) Identify the focus object and the tension score of the person in each frame of the video data.

[0039] Step S202) Obtain the number of focus objects according to the focus objects in all frames of the video data, and obtain the focus rating according to the number of focus objects.

[0040] Step S203) Obtain the tension rating according to the tension score and the pre-configured division interval.

[0041] Step S204) Identify the activity state of the person according to the focus rating and the tension rating.

[0042] Among them, the method for identifying the focus object of the person in each frame of the video data includes: Identify the items on the desktop of the study position and the positions of the items; Identify the face position and the face orientation; Obtain the focus object of the person according to the face position, the face orientation and the item position.

[0043] There is a notebook, a pen and an open book on the desktop. The student's face is facing the book, so it is determined that the focus object is the "book".

[0044] When a person is studying, the only object of focus is a book. When a person is reading, the objects of focus include the book, the blank space on the table, and the objects outside the table. Because when reading, usually when achieving emotional resonance, the person will briefly shift their gaze away from the book. That is, they will focus on the blank space on the table or the objects outside the table.

[0045] When a person is doing manual work, they will use a lot of tools, such as a utility knife, scissors, glue, wooden sticks, paper, etc. Therefore, when doing manual work, the number of objects of focus is relatively large, and it is necessary to constantly shift the focus. Since multiple objects share the focus, the degree of focus at this time will be relatively low.

[0046] On the other hand, please refer to the appendix Figure 8 , and the method for identifying the tension score of the person in each frame of the video data includes: Step S301) Identify the face in each frame of the image to obtain the facial expression. Extract the face from each frame of the image and analyze the facial expression. Different expressions may reflect different degrees of emotional states, such as anxiety, relaxation, etc.

[0047] Step S302) According to the preset reference library, obtain the initial tension score corresponding to the facial expression. Based on the preset reference library (including the tension scores corresponding to different facial expressions), assign an initial tension score to the facial expression in each frame. Exemplarily, in the video data, most of the time the person's expression is calm, and the initial tension score at this time is 0.2, but at some moments, the person shows a slight frown, and the initial tension score is 0.6.

[0048] Step S303) Obtain the number of types of facial expressions in all frames of the video data. If only calm and frowning appear, the number of types of facial expressions is 2. Even if calm and frowning alternate many times, the number of types of facial expressions is still 2.

[0049] Step S304) According to the number of types and the initial tension score, obtain the tension score of the person in each frame of the image. When the number of types of facial expressions is relatively large, that is, greater than a set reference value, multiply the initial tension score by a coefficient less than 1 to obtain the final tension score. When the number of types of facial expressions is relatively small, that is, not greater than a set reference value, multiply the initial tension score by a coefficient greater than 1 to obtain the final tension score. Exemplarily, a tension score of 0 - 3 indicates low tension, and a tension score above 3 indicates high tension.

[0050] Among them, the method for obtaining the focus level according to the number of objects of focus includes: Read the preset focus level table, and the focus level table records the association relationship between the focus level and the range of the number of objects of focus; Obtain the concentration rating according to the concentration rating form.

[0051] Exemplarily, if the number of objects of concentration is 1, it is rated as high concentration; if the number of objects of concentration is between 2 and 5, it is rated as medium concentration; if there are more than 5 different objects of concentration, it is rated as low concentration.

[0052] In this embodiment, the activity states of the person include rest, manual work, painting, learning, reading, and discussion. A concentration rating, a tension rating, and a sound state are associated with the activity states of the person. The concentration rating includes high concentration, medium concentration, and low concentration. The tension rating includes high tension and low tension. The sound state includes having sound and no sound.

[0053] Among them, the method for identifying the activity state of a person according to the concentration rating, the tension rating, and the sound state includes: When the concentration is high, the tension is low, and there is no sound, identify the activity state of the person as reading; When the concentration is low, the tension is low, and there is no sound, identify the activity state of the person as rest; When the concentration is low, the tension is high, and there is no sound, identify the activity state of the person as manual work; When the concentration is medium, the tension is high, and there is no sound, identify the activity state of the person as painting; When the concentration is high, the tension is high, and there is no sound, identify the activity state of the person as learning; When there is sound, identify the activity state of the person as discussion.

[0054] On this basis, the method for generating a supplementary lighting scheme according to the activity state of the person, the ambient color temperature, and the ambient light intensity includes: When the activity state of the person is reading, generate a supplementary lighting scheme with a low color temperature and high brightness as the goal; When the activity state of the person is rest, generate a supplementary lighting scheme with a low color temperature and natural light brightness as the goal; When the activity state of the person is manual work, generate a supplementary lighting scheme with a natural color temperature and high brightness as the goal; When the activity state of the person is painting, generate a supplementary lighting scheme with a natural color temperature and natural brightness as the goal; When the activity state of the person is learning, generate a supplementary lighting scheme with a high color temperature and high brightness as the goal; When the activity state of the person is discussion, generate a supplementary lighting scheme with a low color temperature and high brightness as the goal; The natural brightness is the ambient light intensity collected on any sunny day in a preset month, and the natural color temperature is the ambient color temperature collected on any sunny day in a preset month.

[0055] Exemplarily, when the human activity status is reading, the target is a low color temperature, about 3000K, and high brightness, such as 500 lux. The dual-color LED lamp 54 is adjusted to produce warm but bright light, reducing eye fatigue while providing sufficient illumination. When the human activity status is rest, the target is a low color temperature, about 3000K, and natural light brightness, such as 300 lux. The light brightness is reduced and the warm color tone is maintained to create a relaxing and comfortable atmosphere, which helps to relieve stress and restore energy.

[0056] When the human activity status is manual work, the target is a natural color temperature, about 5000K, and high brightness, such as 700 lux. The color temperature close to natural daylight and higher brightness are used to ensure that details are clearly visible, improving work efficiency and accuracy.

[0057] When the human activity status is painting, the target is a natural color temperature, about 5000K. The natural brightness is such as 500 lux. Simulating natural lighting conditions makes the color performance more real and accurate, which is beneficial to artistic creation.

[0058] When the human activity status is learning, the target is a high color temperature, about 6500K, and high brightness, such as 800 lux. The strong light with a cold white tone is adopted to enhance the concentration of attention, which is suitable for long-term learning tasks.

[0059] When the human activity status is discussion, the target is a low color temperature, about 3000K, and high brightness, such as 600 lux. Creating a warm and bright space encourages open communication, while avoiding the overly dazzling light from affecting the communication quality.

[0060] The natural brightness refers to the ambient light intensity collected on any sunny day in the preset month. For example, the average outdoor illuminance value measured on a sunny day in May of spring. The natural color temperature refers to the ambient color temperature measured under the conditions of a sunny day in the preset month. For example, at noon on a sunny day in May of spring, the color temperature of natural light is approximately 5000K to 6000K.

[0061] On the other hand, this specification provides a campus light environment intelligent governance system based on OEOT. Please refer to the appendix Figure 9 , including: The environment module 100 reads the ambient color temperature and ambient light intensity detected by the ambient light color temperature sensor 21 and the ambient light intensity sensor 22 set in the classroom; The processing module 200 polls the human proximity status of the human body sensors 41 on each study position on each study desk 10 at a preset cycle, obtains a list of study positions with human proximity, traverses the study positions in the list of study positions, and triggers the following modules to work: A reading module 300 reads video data and audio data obtained by a camera 43 and a microphone 42 on a learning bit for a preset time length. An identification module 400 identifies the activity status of a person according to the video data and the audio data. A calculation module 500 generates a fill light scheme according to the activity status of the person, the ambient color temperature, and the ambient light intensity. A control module 600 controls the brightness and color temperature of the dual-color LED lamp 54 according to the fill light scheme. A correction module 700 corrects the color temperature of the dual-color LED lamp 54 according to the detection value of the color temperature sensor 45 on the learning bit.

[0062] Please refer to Figure 10 the schematic structural diagram of an electronic device provided by an embodiment of the present specification shown in

[0063] As Figure 10 shown, the electronic device 1100 may include: at least one processor 1101, at least one network interface 1104, a user interface 1103, a memory 1105, and at least one communication bus 1102. Among them, the communication bus 1102 can be used to realize the connection and communication of the above-mentioned various components. Among them, the user interface 1103 may include buttons, and the optional user interface may further include a standard wired interface and a wireless interface. Among them, the network interface 1104 may include, but is not limited to, a Bluetooth module, an NFC module, a Wi-Fi module, etc. Among them, the processor 1101 may include one or more processing cores. The processor 1101 connects various parts within the entire electronic device 1100 through various interfaces and lines, and by running or executing instructions, programs, code sets, or instruction sets stored in the memory 1105, and by calling data stored in the memory 1105, it executes various functions of the routing device 1100 and processes data. Optionally, the processor 1101 may be implemented in at least one hardware form of DSP, FPGA, and PLA. The processor 1101 may integrate one or several combinations of a CPU, a GPU, and a modem, etc. Among them, the CPU mainly processes the operating system, the user interface, and application programs, etc.; the GPU is responsible for rendering and drawing the content required to be displayed on the display screen; the modem is used to process wireless communication.

[0064] It can be understood that the above-mentioned modem may not be integrated into the processor 1101 and may be implemented separately by a single chip.

[0065] Among them, the memory 1105 may include RAM or ROM. Optionally, the memory 1105 includes a non-transitory computer-readable medium. The memory 1105 can be used to store instructions, programs, codes, code sets, or instruction sets. The memory 1105 may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing the operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above method embodiments, etc.; the data storage area may store data involved in the above method embodiments. Optionally, the memory 1105 may also be at least one storage device located away from the aforementioned processor 1101. As a computer storage medium, the memory 1105 may include an operating system, a network communication module, a user interface module, and application programs. The processor 1101 may be used to call the application programs stored in the memory 1105 and execute the methods in the above embodiments.

[0066] An embodiment of this specification also provides a computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are run on a computer or a processor, the computer or the processor is caused to execute multiple steps in the above embodiments. If each component module of the above electronic device is implemented in the form of a software functional unit and sold or used as an independent product, it may be stored in the computer-readable storage medium.

[0067] An embodiment of this specification also provides a computer program product, including a computer program. When the computer program is executed by a processor, multiple steps in the above embodiments are implemented.

[0068] Without conflict, the technical features in this embodiment and the implementation solutions can be combined arbitrarily.

[0069] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes a plurality of computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of this specification are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server 30, or data center to another website, computer, server 30, or data center by wire (such as coaxial cable, optical fiber, Digital Subscriber Line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server 30, data center, etc. that contains a plurality of integrated available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a Digital Versatile Disc (DVD)), or a semiconductor medium (such as a Solid State Disk (SSD)), etc.

[0070] When implemented by hardware or firmware, the foregoing method flow is programmed into a hardware circuit to obtain a corresponding hardware circuit structure and implement the corresponding function. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. A designer can program on their own to "integrate" a digital system on a single PLD, without having to ask a chip manufacturer to design and fabricate a dedicated integrated circuit chip. Moreover, nowadays, instead of manually fabricating integrated circuit chips, this programming is mostly implemented using "logic compiler" software, which is similar to the software compiler used in program development and writing. The original code before compilation also has to be written in a specific programming language, which is called a Hardware Description Language (HDL), and there are not only one but many kinds of HDLs. Those skilled in the art should also be clear that only by slightly logically programming the method flow with the above-mentioned several hardware description languages and programming it into an integrated circuit can a hardware circuit for implementing the logic method flow be easily obtained.

[0071] The embodiments described above are merely described in terms of the preferred embodiments of this specification, and do not limit the scope of this specification. Without departing from the design spirit of this specification, various deformations and improvements made by those of ordinary skill in the art to the technical solutions of this specification shall fall within the protection scope determined by the claims of this specification.

Claims

1. An intelligent governance method for campus lighting environment based on OEOT, characterized in that, Including the steps: Read the ambient color temperature and ambient light intensity detected by the ambient light color temperature sensor and ambient light intensity sensor set in the classroom; Poll the human proximity status of the human sensors on each study position on the study desks at a preset period, obtain a list of study positions with human proximity, traverse the study positions in the list of study positions, and perform the following steps: Read the video data and sound data obtained by the cameras and microphones on the study positions for a preset time length; Identify the personnel activity status according to the video data and sound data; Generate a supplementary lighting plan according to the personnel activity status, ambient color temperature and ambient light intensity; Control the brightness and color temperature of the dual-color LED lights on the study positions according to the supplementary lighting plan; Correct the color temperature of the dual-color LED lights according to the detection value of the color temperature sensor of the study position.

2. The intelligent governance method for campus light environment based on OEOT according to claim 1, characterized in that The method for identifying the personnel activity status according to the video data and sound data includes: Identify the focus object and tension score of the personnel in each frame of the video data; Obtain the number of focus objects according to the focus objects in all frames of the video data, and obtain the focus rating according to the number of focus objects; Obtain the tension rating according to the tension score and the pre-configured division intervals; Identify the personnel activity status according to the focus rating and tension rating.

3. The intelligent governance method for campus light environment based on OEOT according to claim 2, characterized in that The method for identifying the focus object of the personnel in each frame of the video data includes: Identify the items on the desktop of the study position and the item positions; Identify the face position and face orientation; Obtain the focus object of the personnel according to the face position, face orientation and item position.

4. The intelligent governance method for campus light environment based on OEOT according to claim 2 or 3, characterized in that The method for identifying the tension score of the personnel in each frame of the video data includes: Identify the face in each frame of the image to obtain the facial expression; Obtain the initial tension score corresponding to the facial expression according to the preset reference library; Obtain the number of types of facial expressions in all frames of the video data; Obtain the tension score of the personnel in each frame of the image according to the number of types and the initial tension score; The method for obtaining the focus rating according to the number of focus objects includes: Read the preset focus rating table, and the focus rating table records the association relationship between the focus rating and the focus object number interval; Obtain the focus rating according to the focus rating table.

5. The intelligent governance method for campus light environment based on OEOT according to any one of claims 1 to 3, characterized in that The personnel activity status includes rest, handicraft work, painting, learning, reading and discussion. Associate the focus rating, tension rating and sound status with the personnel activity status. The focus rating includes high focus, medium focus and low focus. The tension rating includes high tension and low tension. The sound status includes having sound and no sound. A method for identifying the activity state of a person based on the concentration rating, stress rating, and voice state includes: When the concentration is high, the stress is low, and there is no sound, identify the person's activity state as reading; When the concentration is low, the stress is low, and there is no sound, identify the person's activity state as resting; When the concentration is low, the stress is high, and there is no sound, identify the person's activity state as manual work; When the concentration is medium, the stress is high, and there is no sound, identify the person's activity state as painting; When the concentration is high, the stress is high, and there is no sound, identify the person's activity state as studying; When there is sound, identify the person's activity state as discussing.

6. The intelligent campus light environment governance method based on OEOT according to claim 5, characterized in that: A method for generating a supplementary lighting scheme based on the person's activity state, ambient color temperature, and ambient light intensity includes: When the person's activity state is reading, generate a supplementary lighting scheme with a low color temperature and high brightness as the goal; When the person's activity state is resting, generate a supplementary lighting scheme with a low color temperature and natural light brightness as the goal; When the person's activity state is manual work, generate a supplementary lighting scheme with a natural color temperature and high brightness as the goal; When the person's activity state is painting, generate a supplementary lighting scheme with a natural color temperature and natural brightness as the goal; When the person's activity state is studying, generate a supplementary lighting scheme with a high color temperature and high brightness as the goal; When the person's activity state is discussing, generate a supplementary lighting scheme with a low color temperature and high brightness as the goal; The natural brightness is the ambient light intensity collected on any sunny day in a preset month, and the natural color temperature is the ambient color temperature collected on any sunny day in a preset month.

7. The intelligent governance system for campus optical environment based on OEOT, characterized in that, It includes: An environment module that reads the ambient color temperature and ambient light intensity detected by the ambient light color temperature sensor and ambient light intensity sensor set in the classroom; A processing module that polls the human proximity status of the human body sensors on each study position on each study desk at a preset period to obtain a list of study positions with human proximity, traverses the study positions in the list of study positions, and triggers the following modules to work: A reading module that reads the video data and sound data obtained by the camera and microphone on the study position for a preset time length; An identification module that identifies the person's activity state based on the video data and sound data; A calculation module that generates a supplementary lighting scheme based on the person's activity state, ambient color temperature, and ambient light intensity; A control module that controls the brightness and color temperature of the dual-color LED lights on the study position according to the supplementary lighting scheme; A correction module that corrects the color temperature of the dual-color LED lights according to the detection value of the color temperature sensor of the study position.

8. An electronic device, characterized in that, It includes a processor and a memory; The processor is connected to the memory; The memory is used to store executable program code; The processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory to execute the method according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, The computer program, when executed by the processor, implements the method according to any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, The computer program, when executed by the processor, implements the method according to any one of claims 1-6.

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