Intelligent management method and system of campus light environment based on OEOT

Abstract

Multiple embodiments of this specification relate to the field of information technology, and more specifically, to an OEOT-based intelligent management method and system for campus light environments. The method includes the following steps: reading the ambient color temperature and ambient light intensity detected by an ambient light color temperature sensor and an ambient light intensity sensor installed in a classroom; polling the human proximity status of a human body sensor at each learning station on a preset cycle to obtain a list of learning stations with human proximity; traversing the learning stations in the learning station list, and performing the following steps: reading video data and audio data obtained by a camera and microphone at the learning station for a preset time length; identifying the activity status of a person based on the video data and audio data; generating a fill light scheme based on the activity status of the person, the ambient color temperature, and the ambient light intensity; controlling the brightness and color temperature of a dual-color LED light based on the fill light scheme; and correcting the color temperature of the dual-color LED light based on the detection value of the color temperature sensor at the learning station.

Description

Technical Field

[0001] Multiple embodiments of this specification relate to the field of information technology, and specifically to an OEOT-based campus light environment intelligent management method and system. Background Art

[0002] With the development of information technology and rising demands for a better learning and working environment, optimizing campus lighting environments has become a key research topic. Traditional lighting systems often use fixtures with fixed brightness and color temperature, which cannot be flexibly adjusted to meet actual needs. This, to a certain extent, affects student learning efficiency and teacher teaching effectiveness. In particular, changes in natural light during different time periods or weather conditions can significantly affect indoor lighting, making it difficult for fixed lighting settings to provide an optimal visual experience all day long. Therefore, research is needed on intelligent campus light environment management technologies. Summary of the Invention

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

[0004] In a first aspect, the embodiments of this specification provide a method for intelligently managing campus light environment based on OEOT, including the following steps:

[0005] Read the ambient color temperature and ambient light intensity detected by the ambient light color temperature sensor and ambient light intensity sensor installed in the classroom;

[0006] Poll the human proximity status of the human body sensors on the learning positions on each learning table at a preset period, obtain a list of learning positions with human bodies approaching, traverse the learning positions in the learning position list, and perform the following steps:

[0007] Read the video and sound data obtained by the camera and microphone at the learning position for a preset time length;

[0008] identifying the activity status of a person based on the video data and the sound data;

[0009] Generate a fill light solution based on the activity status of the personnel, the ambient color temperature and the ambient light intensity;

[0010] Controlling the brightness and color temperature of the dual-color LED lamp according to the fill light scheme;

[0011] The color temperature of the dual-color LED lamp is corrected according to the detection value of the color temperature sensor of the learning position.

[0012] In a second aspect, the embodiments of this specification provide a campus light environment intelligent management system based on OEOT, including:

[0013] The environment module reads the ambient color temperature and ambient light intensity detected by the ambient light color temperature sensor and ambient light intensity sensor installed in the classroom;

[0014] The processing module polls the human proximity status of the human body sensors at each learning position on the learning table at a preset period, obtains a list of learning positions with human proximity, traverses the learning positions in the learning position list, and triggers the following modules to work:

[0015] A reading module reads the video data and sound data obtained by the camera and microphone at the learning position for a preset time length;

[0016] an identification module for identifying the activity status of a person based on the video data and the sound data;

[0017] A calculation module generates a fill light solution according to the activity status of the personnel, the ambient color temperature and the ambient light intensity;

[0018] A control module, controlling the brightness and color temperature of the dual-color LED lamp according to the fill light scheme;

[0019] 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 learning position.

[0020] In a third aspect, embodiments of this specification provide an electronic device, including a processor and a memory;

[0021] The processor is connected to the memory;

[0022] The memory is used to store executable program code;

[0023] The processor reads the executable program code stored in the memory to run a program corresponding to the executable program code, so as to execute the method described in any one of the above aspects.

[0024] In a fourth aspect, an embodiment of this specification provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method described in any one of the above aspects is implemented.

[0025] In a fifth aspect, embodiments of this specification provide a computer program product, including a computer program, which implements the method described in any of the above aspects when executed by a processor.

[0026] The beneficial effects of the technical solutions provided by some embodiments of this specification include at least:

[0027] In multiple embodiments of this specification, the provided intelligent management solution for campus light environment can provide lighting conditions that are more suitable for learning and rest by monitoring the ambient color temperature and light intensity in the classroom in real time, and dynamically adjusting the color temperature and brightness of the lights according to the different activity states of students. It can adapt the lighting changes according to the specific activity states of people at different learning positions, achieving a more personalized lighting experience. Choosing the right color temperature and light intensity can not only protect eyesight, but also affect the atmosphere of the space and people's psychological state, helping to improve work efficiency and quality of life. By using Internet of Things technology and sensor networks, intelligent management and control of the lighting system in the classroom can be achieved, reducing the need for manual intervention and improving efficiency.

[0028] Other features and advantages of the various embodiments of this specification will be further disclosed in the following detailed description and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of this specification, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0030] Figure 1 This is a flow chart of the method for intelligent management of campus light environment provided in the embodiments of this specification.

[0031] Figure 2 A schematic diagram of a classroom provided in an embodiment of this specification.

[0032] Figure 3 This is a schematic diagram of the campus light environment intelligent management system architecture provided in the embodiments of this specification.

[0033] Figure 4 This is a schematic diagram of the study table structure provided in the embodiment of this specification.

[0034] Figure 5 This is a schematic diagram of the beam structure provided in the embodiments of this specification.

[0035] Figure 6 This is a schematic diagram of the partition structure provided in the embodiments of this specification.

[0036] Figure 7 This is a flow chart of a method for identifying the activity status of a person provided in an embodiment of this specification.

[0037] Figure 8 This is a flow chart of the stress scoring method provided in the embodiments of this specification.

[0038] Figure 9Schematic diagram of the campus light environment intelligent management system provided in the embodiments of this specification.

[0039] Figure 10 This is a schematic diagram of an electronic device provided in an embodiment of this specification. DETAILED DESCRIPTION

[0040] The following is an explanation and description of the technical solutions of the embodiments of this specification in conjunction with the drawings of the embodiments of this specification. However, the following embodiments are only preferred embodiments of this specification and are not exhaustive. Based on the embodiments in the implementation mode, other embodiments obtained by those skilled in the art without making any creative work are all within the scope of protection of this specification.

[0041] Throughout this specification, the claims, and the accompanying drawings, the terms "first," "second," "third," and the like are used to distinguish between different items, not to describe a particular order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may include other steps or elements inherent to the process, method, product, or apparatus.

[0042] In the following description, terms such as "inside", "outside", "up", "down", "left", "right", etc. that indicate directions or positional relationships are only used to facilitate the description of the embodiments and simplify the description. They do not indicate or imply that the devices or elements referred to must have a specific direction, be constructed and operate in a specific direction. Therefore, they should not be understood as limitations on this specification.

[0043] The data involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection of relevant data complies with the relevant laws, regulations and standards of relevant countries and regions.

[0044] Before introducing the technical solution in this specification, the application scenarios and related technologies of the technical solution are introduced.

[0045] OEOT (Optimized Environmental Optical Technology) is a cutting-edge technology suitable for managing the lighting environment in campus settings. It utilizes a sensor network to monitor the ambient color temperature and light intensity in real time. Combined with a cellular sensor 41, it determines whether a study space is occupied and its specific activity status, enabling precise supplemental lighting control. For example, if the system detects a student is reading, it automatically adjusts the lighting to a low color temperature, high brightness setting to reduce eye strain. During breaks, it switches to a low color temperature, natural light setting to create a relaxing atmosphere. While OEOT technology can improve the quality of campus lighting and provide a more suitable environment for students, its application relies on identifying occupant status. Currently, this identification is based on teaching plans. It cannot respond to real-time changes in occupant status or adapt lighting to individual occupants.

[0046] Since this application involves some professional terms, these professional terms will be introduced below.

[0047] Color temperature

[0048] Color temperature, measured in Kelvin (K), is a method for characterizing the color characteristics of a light source. It is based on the color of light emitted by an idealized blackbody radiator when heated to different temperatures. Low color temperatures (e.g., 2000K-3000K) typically exhibit warm tones, such as yellow or orange, creating a warm and comfortable feeling; while high color temperatures (e.g., above 5000K) exhibit cool tones, such as blue, creating a fresh and bright impression. In lighting design, choosing the right color temperature can influence the atmosphere of a space and people's psychological state.

[0049] Dual-color LED light 54

[0050] A bi-color LED lamp 54 is an LED lamp that emits light at two different color temperatures. These lamps typically incorporate two types of LED chips: one for producing warm white light (lower color temperature) and the other for producing cool white light (higher color temperature). By adjusting the brightness ratio of these two LEDs, the bi-color LED lamp 54 can adjust the color temperature of its output light over a wide range, adapting to varying usage needs and environmental conditions. For example, a higher color temperature setting might be preferred in a work environment requiring concentration, while a lower color temperature setting might be chosen to create a relaxing atmosphere in a rest area.

[0051] Light intensity

[0052] Light intensity refers to the luminous intensity of a light source in a specific direction. Its international unit is the candela (cd). It is a physical quantity that measures a light source's ability to emit light in a specific direction. Simply put, higher light intensity means stronger light emitted from that source. For indoor lighting, light intensity directly impacts the brightness and visual comfort of a space. Appropriate light intensity not only helps protect eyesight but also improves work efficiency and quality of life. In practical applications, in addition to considering light intensity, factors such as uniformity and contrast must also be considered to ensure the overall lighting effect.

[0053] This manual provides a method for intelligent management of campus light environment based on OEOT. Figure 1 , including the steps of:

[0054] Step S101) reading the ambient color temperature and ambient light intensity detected by the ambient light color temperature sensor 21 and the ambient light intensity sensor 22 installed in the classroom;

[0055] Step S102) Poll the human proximity status of the human body sensor 41 on each learning position on the learning table 10 at a preset period, obtain a list of learning positions with human proximity, traverse the learning positions in the learning position list, and perform the following steps:

[0056] Step S103) reading the video data and sound data obtained by the camera 43 and the microphone 42 at the learning position for a preset time length;

[0057] Step S104) identifying the activity status of the person based on the video data and the sound data;

[0058] Step S105) generating a fill light solution according to the activity status of the personnel, the ambient color temperature and the ambient light intensity;

[0059] Step S106) controlling the brightness and color temperature of the dual-color LED lamp 54 according to the fill light solution;

[0060] Step S107 ) Correcting the color temperature of the bi-color LED lamp 54 according to the detection value of the color temperature sensor 45 at the learning position.

[0061] Please see the attached Figure 2 , is the classroom study table 10 and its example placement method used in the technical solution recorded in this specification. There are multiple study tables 10 placed in a classroom, and each study table 10 has an independent sensor and a controllable light source. Please refer to the attached Figure 3, the technical solution recorded in this specification uses the Internet of Things technology, and each classroom is equipped with an ambient light color temperature sensor 21 and an ambient light intensity sensor 22. The ambient light color temperature sensor 21 and the ambient light intensity sensor 22 are both connected to a server 30. Each study table 10 is provided with a human body sensor 41, a microphone 42, a camera 43, a lighting controller 44 and a color temperature sensor 45, and the human body sensor 41, microphone 42, camera 43, lighting controller 44 and color temperature sensor 45 are all connected to the server 30. As the control center of the OEOT technology, the server 30 can not only read the data of all sensors, but also independently control the lighting on each learning position of each study table 10 through each lighting controller 44.

[0062] Please see the attached Figure 4 and attached Figure 5 In one embodiment, the study table 10 includes four study positions. The study table 10 includes a desktop and columns 51 and a beam 53 arranged on the desktop, and the beam 53 is supported by the column 51. The beam 53 is provided with four two-color LED lights 54, a manual switch 52, two partitions 55, four groups of sensors corresponding to each study position and a light controller 44. 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 two-color LED lights 54, the light controller 44 and the sensors. After the manual switch 52 is turned on, the light controller 44 and the sensor 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 two-color LED lights 54 according to the control instructions.

[0063] Please see the attached Figure 6 The partition 55 is located between the two bi-color LED lamps 54 to prevent interference between them. The partition 55 includes a base 551, a reflective layer 552, and an inclined plate 553. The base 551 is fixed to the crossbeam 53 and located between the two bi-color LED lamps 54. The inclined plate 553 is mounted on the base 551. The inclined plate 553 has two inclined surfaces. The reflective layer 552 is attached to both surfaces of the inclined plate 553.

[0064] In another embodiment, the study table 10 includes only two study stations on one side. In this embodiment, all study stations can be oriented in the same direction. This is suitable for situations where all students are participating in the same activity. Alternatively, the study table 10 may include only one study station. This can be achieved by adapting the number of dual-color LED lights 54 and sensor groups.

[0065] The human body sensor 41 is implemented in a manner disclosed in the art. For example, an infrared sensor is used as the human body sensor 41 .

[0066] Please see the attached Figure 7 The method for identifying the activity status of a person based on the video data and the sound data includes:

[0067] Step S201) Identify the focus object and tension score of the person in each frame of the video data.

[0068] Step S202) Obtaining the number of focused objects based on the focused objects in all frames of the video data, and obtaining a focus rating based on the number of focused objects.

[0069] Step S203) Obtain a stress rating based on the stress score and the pre-configured division intervals.

[0070] Step S204) Identify the activity status of the person based on the concentration rating and the tension rating.

[0071] The method of identifying the object of focus of a person in each frame of the video data includes:

[0072] Identify items and their locations on the desk of the learning station;

[0073] Identify face position and face orientation;

[0074] The object of the person's focus is obtained according to the face position, face orientation and object position.

[0075] There is a notebook, a pen, and an open book on the table. The student's face is facing the book, so the object of his or her focus is determined to be "the book."

[0076] When studying, the only object of focus is the book. When reading, the focus also includes the book, an empty space on the desk, and items outside the desk. This is because when reading, people often briefly look away from the book when they experience emotional resonance. This means they focus on the empty space on the desk or items outside the desk.

[0077] When people perform manual work, they use a lot of tools, such as utility knives, scissors, glue, wooden sticks, paper, etc. Therefore, when performing manual work, the number of items to focus on is relatively large, and it is necessary to constantly shift focus. Since the focus is divided among multiple items, the concentration level will be lower at this time.

[0078] On the other hand, please see the attached Figure 8 The method for identifying the stress score of a person in each frame of the video data includes:

[0079] Step S301) Identify faces in each image frame and obtain facial expressions. Extract faces from each image frame and analyze facial expressions. Different expressions may reflect varying degrees of emotional states, such as anxiety or relaxation.

[0080] Step S302) Obtain an initial stress score corresponding to the facial expression based on a preset reference library. Based on the preset reference library (which contains stress scores corresponding to different facial expressions), a preliminary stress score is assigned to each facial expression in each frame. For example, in the video data, the person's expression is mostly calm, resulting in an initial stress score of 0.2. However, at certain moments, they may exhibit a slight frown, resulting in an initial stress score of 0.6.

[0081] Step S303) Obtain the number of facial expression types for all frames in the video data. If only calmness and frowning appear, the number of facial expression types is 2. Even if calmness and frowning appear alternately multiple times, the number of facial expression types remains 2.

[0082] Step S304) A stress score is obtained for the person in each frame based on the number of facial expression types and the initial stress score. If the number of facial expression types is large, i.e., greater than a set reference value, the initial stress score is multiplied by a coefficient less than 1 to obtain a final stress score. If the number of facial expression types is small, i.e., less than a set reference value, the initial stress score is multiplied by a coefficient greater than 1 to obtain a final stress score. For example, a score of 0-3 indicates low stress, and a score of 3 or higher indicates high stress.

[0083] The method for obtaining a concentration rating according to the number of the focus objects includes:

[0084] Reading a preset concentration rating table, wherein the concentration rating table records the correlation between the concentration rating and the number interval of the concentration objects;

[0085] Obtain a concentration rating according to the concentration rating table.

[0086] For example, if the number of focus objects is 1, it is rated as high focus; if the number of focus objects is between 2 and 5, it is rated as medium focus; if there are more than 5 different focus objects, it is rated as low focus.

[0087] In this embodiment, the personnel activity status includes resting, manual work, painting, studying, reading and discussing, and the personnel activity status is associated with a concentration rating, a tension rating and a sound status. The concentration rating includes high concentration, medium concentration and low concentration. The tension rating includes high tension and low tension. The sound status includes sound and no sound.

[0088] The method for identifying the activity status of a person based on the concentration rating, the tension rating, and the voice status includes:

[0089] When concentration is high, tension is low, and there is no sound, the activity state of the identifier is reading;

[0090] When concentration is low, tension is low, and there is no sound, the person's activity state is identified as resting;

[0091] When the concentration is low, the tension is high, and there is no sound, the activity state of the person is identified as manual work;

[0092] When the concentration is medium, the tension is high, and there is no sound, the activity state of the person is identified as drawing;

[0093] When the concentration is high, the tension is high, and there is no sound, the activity state of the person is identified as learning;

[0094] When there is sound, the activity status of the identified person is discussion.

[0095] On this basis, the method for generating a fill light solution according to the activity status of the personnel, the ambient color temperature, and the ambient light intensity includes:

[0096] When the person's activity state is reading, a fill light solution is generated with low color temperature and high brightness as the goal;

[0097] When the person's activity state is resting, a fill light solution is generated with low color temperature and natural light brightness as the target;

[0098] When the personnel activity state is manual work, a fill light solution is generated with natural color temperature and high brightness as the goal;

[0099] When the activity state of the person is painting, a fill light solution is generated with natural color temperature and natural brightness as the target;

[0100] When the activity state of the person is learning, a fill light solution is generated with high color temperature and high brightness as the goal;

[0101] When the activity status of the personnel is discussion, a fill light solution is generated with low color temperature and high brightness as the goal;

[0102] 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.

[0103] For example, when a person is reading, the target color temperature is low, approximately 3000K, and the brightness is high, such as 500 lux. The dual-color LED light 54 is adjusted to produce a warm but bright light, reducing eye fatigue while providing adequate illumination. When a person is resting, the target color temperature is low, approximately 3000K, and the brightness is natural light, such as 300 lux. Lowering the brightness and maintaining a warm tone creates a relaxing and comfortable atmosphere, helping to relieve stress and restore energy.

[0104] When manual labor is involved, the target is a natural color temperature of approximately 5000K and a high brightness of, for example, 700 lux. Using a color temperature close to daylight and a higher brightness ensures clear visibility of details, improving work efficiency and accuracy.

[0105] When a person is painting, the target color temperature is approximately 5000K, and the brightness is 500 lux. This simulates natural lighting conditions, making color representation more realistic and accurate, facilitating artistic creation.

[0106] When studying, the goal is a high color temperature of approximately 6500K and a high brightness of 800 lux. This cool white light enhances concentration and is suitable for extended study sessions.

[0107] When people are discussing something, aim for a low color temperature of around 3000K and high brightness, such as 600 lux. This creates a warm and bright space that encourages open communication while avoiding harsh lighting that can affect the quality of communication.

[0108] Natural brightness refers to the ambient light intensity measured on a sunny day during a preset month. For example, the average outdoor illuminance value measured on a sunny day in May. Natural color temperature refers to the ambient color temperature measured on a sunny day during a preset month. For example, the color temperature of natural light at noon on a sunny day in May is approximately 5000K to 6000K.

[0109] On the other hand, this manual provides a campus light environment intelligent management system based on OEOT, please refer to the attached Figure 9 ,include:

[0110] 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 installed in the classroom;

[0111] The processing module 200 polls the human proximity status of the human body sensor 41 at each learning position on the learning table 10 at a preset period, obtains a list of learning positions with human proximity, traverses the learning positions in the learning position list, and triggers the following modules to work:

[0112] The reading module 300 reads the video data and sound data obtained by the camera 43 and the microphone 42 at the learning position for a preset time length;

[0113] Identification module 400, identifying the activity status of a person based on the video data and the sound data;

[0114] The calculation module 500 generates a fill light solution according to the activity status of the personnel, the ambient color temperature and the ambient light intensity;

[0115] The control module 600 controls the brightness and color temperature of the dual-color LED lamp 54 according to the fill light solution;

[0116] The 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 at the learning position.

[0117] See also Figure 10 The figure shows a schematic diagram of the structure of an electronic device provided by an embodiment of this specification.

[0118] like Figure 10 As 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. The communication bus 1102 may be used to implement communication between the aforementioned components. The user interface 1103 may include buttons, and optionally may also include a standard wired interface or a wireless interface. The network interface 1104 may include, but is not limited to, a Bluetooth module, an NFC module, a Wi-Fi module, etc. The processor 1101 may include one or more processing cores. The processor 1101 utilizes various interfaces and circuits to connect the various components within the entire electronic device 1100. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 1105 and accessing data stored in the memory 1105, it performs various functions of the routing device 1100 and processes data. Optionally, the processor 1101 may be implemented in hardware using at least one of a DSP, an FPGA, and a PLA. The processor 1101 may integrate one or a combination of a CPU, a GPU, and a modem. The CPU primarily processes the operating system, user interface, and applications; the GPU is responsible for rendering and drawing content displayed on the display; and the modem handles wireless communications.

[0119] It is understandable that the above-mentioned modem may not be integrated into the processor 1101, but may be implemented separately through a chip.

[0120] Memory 1105 may include either RAM or ROM. Optionally, memory 1105 may include non-transitory computer-readable media. Memory 1105 may be used to store instructions, programs, codes, code sets, or instruction sets. Memory 1105 may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, sound playback function, image playback function, etc.), instructions for implementing the aforementioned method embodiments, etc.; the data storage area may store data related to the aforementioned method embodiments, etc. Memory 1105 may also optionally be at least one storage device located remotely from the aforementioned processor 1101. Memory 1105, as a computer storage medium, may include an operating system, a network communication module, a user interface module, and application programs. Processor 1101 may be configured to invoke the application programs stored in memory 1105 and execute the methods described in the aforementioned embodiments.

[0121] The embodiments of this specification also provide a computer-readable storage medium having instructions stored therein that, when executed on a computer or processor, cause the computer or processor to perform the steps of the aforementioned embodiments. If the components of the aforementioned electronic device are implemented as software functional units and sold or used as independent products, they may be stored in the computer-readable storage medium.

[0122] The embodiments of this specification also provide a computer program product, including a computer program, which implements multiple steps in the above embodiments when executed by a processor.

[0123] In the absence of conflict, the technical features in this embodiment and implementation scheme can be combined arbitrarily.

[0124] In the above embodiments, all or part of the embodiments can be implemented using software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes multiple computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this specification are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted via 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 via wired (e.g., coaxial cable, optical fiber, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. 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 or data center that integrates multiple available media. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital versatile disc (DVD)), or a semiconductor medium (eg, a solid state drive (SSD)).

[0125] When implemented via hardware or firmware, the aforementioned method flow is programmed into the hardware circuit to obtain the corresponding hardware circuit structure and realize the corresponding function. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit, whose logical function is determined by the user's device programming. Designers can "integrate" a digital system on a PLD through self-programming, eliminating the need for chip manufacturers to design and manufacture dedicated integrated circuit chips. Moreover, today, instead of manually manufacturing integrated circuit chips, this programming is often performed using "logic compiler" software. This is similar to the software compiler used in program development. Before compilation, the original code must also be written in a specific programming language, called a hardware description language (HDL). There are not just one HDL, but many. Those skilled in the art will also understand that simply by programming the method flow in one of the aforementioned hardware description languages ​​and programming it into the integrated circuit, a hardware circuit that implements the logical method flow can be easily obtained.

[0126] The embodiments described above are merely preferred embodiments of this specification and are not intended to limit the scope of this specification. Without departing from the design spirit of this specification, various modifications and improvements made to the technical solutions of this specification by ordinary technicians in this field should fall within the scope of protection determined by the claims of this specification.

Claims

1. The intelligent management method of campus light environment based on OEOT is characterized by: Including steps: Read the ambient color temperature and ambient light intensity detected by the ambient light color temperature sensor and ambient light intensity sensor installed in the classroom; Poll the human proximity status of the human body sensors on the learning positions on each learning table at a preset period, obtain a list of learning positions with human bodies approaching, traverse the learning positions in the learning position list, and perform the following steps: Read the video and sound data obtained by the camera and microphone at the learning position for a preset time length; identifying the activity status of a person based on the video data and the sound data; Generate a fill light solution based on the activity status of the personnel, the ambient color temperature and the ambient light intensity; Control the brightness and color temperature of the dual-color LED lamp according to the fill light solution; Correcting the color temperature of the dual-color LED lamp according to the detection value of the color temperature sensor of the learning position; The method for identifying the activity status of a person based on the video data and the sound data includes: Identifying the focus object and the tension score of the person in each frame of the video data; Obtaining the number of focused objects according to the focused objects of all frames of the video data, and obtaining a focus rating according to the number of focused objects; Get a stress rating based on the stress score and pre-configured division intervals; Identifying the activity status of the personnel based on the concentration rating and the tension rating; The method for identifying the stress score of a person in each frame of the video data includes: Identify faces in each frame and obtain facial expressions; Obtain an initial score of tension corresponding to facial expressions based on a preset reference library; Obtaining the number of types of facial expressions in all frame images in the video data; Obtaining a stress score of the person in each frame of the image according to the number of types and the initial stress score; Methods for obtaining a focus rating based on the number of said focus objects include: Reading a preset concentration rating table, wherein the concentration rating table records the correlation between the concentration rating and the number interval of the concentration objects; Obtain a focus rating according to the focus rating form; The personnel activity status includes resting, manual work, painting, studying, reading and discussing.

2. The method for intelligent management of campus light environment based on OEOT according to claim 1 is characterized in that: The method for identifying the object of focus of a person in each frame of the video data includes: Identify items and their locations on the desk of the learning station; Identify face position and face orientation; The object of the person's focus is obtained according to the face position, face orientation and object position.

3. The OEOT-based campus light environment intelligent management method according to claim 1 or 2, characterized in that: The activity status of the personnel is associated with a concentration rating, a tension rating, and a sound status, wherein the concentration rating includes high concentration, medium concentration, and low concentration, the tension rating includes high tension and low tension, and the sound status includes sound and no sound. The method for identifying the activity status of a person based on the concentration rating, the tension rating, and the voice status includes: When concentration is high, tension is low, and there is no sound, the activity state of the identifier is reading; When concentration is low, tension is low, and there is no sound, the person's activity state is identified as resting; When the concentration is low, the tension is high, and there is no sound, the activity state of the person is identified as manual work; When the concentration is medium, the tension is high, and there is no sound, the activity state of the person is identified as drawing; When the concentration is high, the tension is high, and there is no sound, the activity state of the person is identified as learning; When there is sound, the activity status of the identified person is discussion.

4. The method for intelligent management of campus light environment based on OEOT according to claim 3 is characterized in that: The method for generating a fill light solution according to the activity status of the personnel, the ambient color temperature, and the ambient light intensity includes: When the person's activity state is reading, a fill light solution is generated with low color temperature and high brightness as the goal; When the person's activity state is resting, a fill light solution is generated with low color temperature and natural light brightness as the target; When the personnel activity state is manual work, a fill light solution is generated with natural color temperature and high brightness as the goal; When the activity state of the person is painting, a fill light solution is generated with natural color temperature and natural brightness as the target; When the activity state of the person is learning, a fill light solution is generated with high color temperature and high brightness as the goal; When the activity status of the personnel is discussion, a fill light solution is generated with 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.

5. The campus light environment intelligent management system based on OEOT is characterized by: include: The environment module reads the ambient color temperature and ambient light intensity detected by the ambient light color temperature sensor and ambient light intensity sensor installed in the classroom; The processing module polls the human proximity status of the human body sensors at each learning position on the learning table at a preset period, obtains a list of learning positions with human proximity, traverses the learning positions in the learning position list, and triggers the following modules to work: A reading module reads the video data and sound data obtained by the camera and microphone at the learning position for a preset time length; an identification module for identifying the activity status of a person based on the video data and the sound data; A calculation module generates a fill light solution according to the activity status of the personnel, the ambient color temperature and the ambient light intensity; A control module controls the brightness and color temperature of the dual-color LED lamp according to the fill light solution; a correction module, which corrects the color temperature of the dual-color LED lamp according to the detection value of the color temperature sensor of the learning position; The method for identifying the activity status of a person based on the video data and the sound data includes: Identifying the focus object and the tension score of the person in each frame of the video data; Obtaining the number of focused objects according to the focused objects of all frames of the video data, and obtaining a focus rating according to the number of focused objects; Get a stress rating based on the stress score and pre-configured division intervals; Identifying the activity status of the personnel based on the concentration rating and the tension rating; The method for identifying the stress score of a person in each frame of the video data includes: Identify faces in each frame and obtain facial expressions; Obtain an initial score of tension corresponding to facial expressions based on a preset reference library; Obtaining the number of types of facial expressions in all frame images in the video data; Obtaining a stress score of the person in each frame of the image according to the number of types and the initial stress score; Methods for obtaining a focus rating based on the number of said focus objects include: Reading a preset concentration rating table, wherein the concentration rating table records the correlation between the concentration rating and the number interval of the concentration objects; Obtain a focus rating according to the focus rating form; The personnel activity status includes resting, manual work, painting, studying, reading and discussing.

6. An electronic device, characterized in that: including 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, so as to execute the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

8. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

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