A multi-scenario adaptive lighting control device

Abstract

The application discloses a kind of multi-scene adaptive lighting control device, including control component, user terminal and lighting lamp, the control component includes installation box, the inside of the installation box is provided with control panel, energy-saving optimization module, communication coordination module and intelligent control module;The equipment realizes the real-time response of environment and user demand, solves the problem of poor adaptability of traditional equipment: device is through illumination perception module Real-time acquisition of ambient light intensity, temperature and humidity, natural light spectrum and other data, automatically identify day, night, rainy day and other different light scenes, without manual setting or relying on fixed schedule, can dynamically adjust lighting parameters according to environmental changes;At the same time, combined with activity identification module, accurately identify different activity types such as user reading, office work, movie watching, match corresponding light mode (such as reading with 4000K neutral white light, movie watching with 3000K warm tone), avoid the uncomfortable experience caused by the scene change that traditional equipment cannot adapt.

Description

Technical Field

[0001] This invention relates to the field of smart home technology, specifically to a multi-scene adaptive lighting control device. Background Technology

[0002] With the popularization of smart homes, the intelligentization of lighting systems has become a research hotspot in homes, offices, and commercial spaces. Currently, smart lighting devices can only adjust the brightness and color temperature of the light source manually or on a fixed schedule, lacking real-time adaptability to environmental changes and user needs, resulting in energy waste and uncomfortable experiences. For example, in a home environment, lighting needs differ significantly between day and night, and traditional lighting systems struggle to automatically adjust lighting conditions to achieve optimal visual and energy-saving effects. Furthermore, different activities (such as reading, dining, and resting) require different lighting conditions, and existing devices cannot make real-time adjustments based on changes in the scenario. Summary of the Invention

[0003] The purpose of this invention is to provide a multi-scene adaptive lighting control device to solve the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a multi-scene adaptive lighting control device, comprising a control component, a user terminal, and a lighting lamp. The control component includes a mounting box, the interior of which is provided a control panel, an energy-saving optimization module, a communication and collaboration module, and an intelligent control module. The mounting box has ventilation holes on both sides, a door on one side wall, a keyhole on the side wall of the door, a key in the keyhole, and a viewing window on the side wall of the door. The lighting lamp has a light sensing module and an activity recognition module on its outer wall. The user terminal includes a user setting interface.

[0005] Preferably, the light sensing module is used to collect ambient light intensity, personnel presence status, ambient temperature and humidity, and natural light spectrum data in real time; the activity recognition module is used to identify the user's current activity type based on vision and multi-sensor fusion technology; the intelligent control module is used to automatically adjust the brightness, color temperature, color rendering index, and zoned lighting status of the lighting system according to environmental data and user activity type; the user setting interface is used to provide users with manual control and personalized lighting scene customization functions; the energy-saving optimization module is used to execute lighting energy-saving control strategies according to personnel activity status and ambient natural light intensity; and the communication and collaboration module is used to realize data transmission between various modules within the device and linkage control with external intelligent devices.

[0006] Preferably, the light sensing module includes a light intensity sensor, a human infrared sensor, a millimeter-wave radar sensor, a temperature and humidity sensor, and a natural light spectrum sensor, which can identify light environments such as daytime, nighttime, cloudy / rainy days, and dusk, and detect the location, movement trajectory, and duration of stay of people indoors.

[0007] Preferably, the activity recognition module is equipped with a low-power camera and an edge computing unit, and adopts human posture recognition and deep learning algorithms to recognize reading, working, watching movies, dining, resting and unattended states, and the image data is processed locally and not transmitted to the cloud.

[0008] Preferably, the intelligent control module has a built-in scene database and user habit learning model, which can realize stepless brightness adjustment, precise switching of color temperature from 2700K to 6500K, and smooth transition of lighting parameters; it outputs 4000K neutral white light in reading mode, reduces brightness and switches to 3000K warm color tone in movie mode, and outputs 5000K–6000K cool white light in office mode.

[0009] Preferably, the user settings interface includes a mobile APP, a smart voice assistant, a local touch screen, and a physical remote control, supporting user-defined lighting scenes, multi-user permission management, and linkage with smart home devices such as curtains, air conditioners, and speakers.

[0010] Preferably, the energy-saving strategies executed by the energy-saving optimization module include: dimming or turning off the lighting when no one is detected, reducing indoor lighting power when there is sufficient outdoor natural light, optimizing lighting operation according to peak and off-peak electricity consumption periods, and the device itself operating in low-power standby mode.

[0011] Preferably, the communication and collaboration module supports Wi-Fi, Bluetooth 5.0, Zigbee, LoRa wireless communication protocols as well as RS485 and Ethernet wired connections, enabling multi-device networking, cloud algorithm upgrades, and unified lighting control across multiple areas.

[0012] Preferably, the intelligent control module employs machine learning and deep learning algorithms, enabling it to learn user habits and continuously optimize activity recognition accuracy and lighting control strategies.

[0013] The control method for the aforementioned multi-scene adaptive lighting control device includes the following steps: S1. The light sensing module collects environmental parameters and personnel status data in real time. S2. The activity recognition module performs image and behavior analysis locally to identify the user's current activity type. S3, the intelligent control module integrates environmental and activity data to match the optimal lighting control strategy; S4. Drive the lighting equipment to perform smooth adjustment of brightness, color temperature, and zoned illumination; S5, the energy-saving optimization module simultaneously executes energy-saving control that combines unmanned energy saving with natural light complementary energy saving control; S6. Users can adjust parameters or edit custom scenes through the user settings interface; S7 The device continuously collects user behavior data, optimizes control logic through self-learning algorithms, and supports cloud-based algorithm upgrades.

[0014] Compared with existing technologies, the beneficial effects of this invention are: the device achieves real-time response to environmental and user needs, solving the problem of poor adaptability of traditional devices: the device collects data such as ambient light intensity, temperature and humidity, and natural light spectrum in real time through a light sensing module, automatically identifying different lighting scenarios such as daytime, nighttime, and rainy days, without the need for manual setting or reliance on a fixed schedule, and can dynamically adjust lighting parameters according to environmental changes; at the same time, combined with an activity recognition module, it accurately identifies different activity types of users such as reading, working, and watching movies, and matches corresponding lighting modes (such as 4000K neutral white light for reading and 3000K warm light for watching movies), avoiding the uncomfortable experience caused by the inability of traditional devices to adapt to scene changes; This device is more intelligent and caters to users' personalized needs: the intelligent control module has a built-in user habit learning model that can learn user preferences and continuously optimize lighting control strategies to achieve "the more you use it, the smarter it becomes"; at the same time, it provides multiple control methods such as mobile APP and voice assistant, supports user-defined scenes and multi-permission management, and builds an integrated control system, which is superior to the single manual or timed control mode of traditional devices. Attached Figure Description

[0015] Figure 1 This is a three-dimensional structural diagram of the control component of the present invention.

[0016] Figure 2 This is a three-dimensional structural schematic diagram of the control component of the present invention from another perspective.

[0017] Figure 3 This is a structural schematic diagram of the module flowchart of the present invention.

[0018] Figure 4 This is a schematic diagram of the process flow of the device of the present invention.

[0019] In the diagram: 1. Installation box; 2. Box door; 3. Keyhole; 4. Key; 5. Ventilation vent; 6. Control panel; 7. Viewing window. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Please see Figures 1-4, the present invention provides a technical solution: a multi-scenario adaptive lighting control device, including a control component, a user terminal and a lighting lamp. The control component includes an installation box 1. Inside the installation box 1, there are a control panel 6, an energy-saving optimization module, a communication collaboration module and an intelligent control module. There are heat dissipation holes 5 on both sides of the installation box 1. A box door 2 is provided on the side wall of the installation box 1. There is a keyhole 3 on the side wall of the box door 2, and a key 4 is arranged in the keyhole 3. There is a viewing window 7 on the side wall of the box door 2. The outer wall of the lighting lamp is provided with a light perception module and an activity recognition module. The user terminal includes a user setting interface. The light perception module is used to collect environmental light intensity, personnel presence status, environmental temperature and humidity, and natural light spectrum data in real time; the activity recognition module is used to identify the current activity type of the user based on vision and multi-sensor fusion technology; the intelligent control module is used to automatically adjust the brightness, color temperature, color rendering index and zonal lighting status of the lighting system according to environmental data and the user's activity type; the user setting interface is used to provide users with manual control and personalized lighting scene customization functions; the energy-saving optimization module is used to execute a lighting energy-saving control strategy according to the personnel activity status and environmental natural light intensity; the communication collaboration module is used to realize data transmission between internal modules of the device and linkage control with external intelligent devices. The light perception module includes a light intensity sensor, a human body infrared sensor, a millimeter wave radar sensor, a temperature and humidity sensor and a natural light spectrum sensor, which can identify lighting environments such as day, night, rainy day, dusk, etc., and detect the indoor personnel position, movement trajectory and stay duration. The activity recognition module is configured with a low-power camera and an edge computing unit, and uses human body pose recognition and deep learning algorithms to identify reading, office work, movie watching, dining, resting and no-person states, and the image data is only processed locally without cloud transmission. The intelligent control module has a built-in scene database and a user habit learning model, which can realize stepless brightness adjustment, accurate switching of color temperature from 2700K to 6500K and smooth transition of lighting parameters; in the reading mode, it outputs 4000K neutral white light, in the movie watching mode, it reduces the brightness and switches to 3000K warm color tone, and in the office mode, it outputs 5000K - 6000K cold white light. The user setting interface includes a mobile APP, an intelligent voice assistant, a local touch screen and a physical remote control, and supports users to customize lighting scenes, multi-user permission management and linkage with smart home devices such as curtains, air conditioners, speakers, etc. The energy-saving strategy executed by the energy-saving optimization module includes: dimming or turning off the lighting with a time delay when no one is detected, reducing the indoor lighting power when the outdoor natural light is sufficient, optimizing the lighting operation according to the peak and valley periods of electricity consumption, and the device itself being in a low-power standby state. The communication collaboration module supports Wi-Fi and Bluetooth 5.The system utilizes Zigbee and LoRa wireless communication protocols, as well as RS485 and Ethernet wired connections, enabling multi-device networking, cloud-based algorithm upgrades, and unified lighting control across multiple areas. The intelligent control module employs machine learning and deep learning algorithms, allowing it to learn user habits and continuously optimize activity recognition accuracy and lighting control strategies.

[0022] The working principle of the above technical solution is as follows: This multi-scene adaptive lighting control device uses "perception-analysis-decision-execution-optimization" as its core logic. Through the coordinated linkage of control components, user terminals, and lighting lamps, it achieves intelligent, personalized, and energy-saving control of the lighting system, adapting to different environments and user activity needs. Its entire workflow forms a closed loop, with each module working collaboratively and closely to complete adaptive lighting control. The device's perception layer consists of a light sensing module and an activity recognition module on the outer wall of the lighting lamp. As a prerequisite for adaptive control, it is responsible for collecting various key data, providing a solid foundation for subsequent control decisions. Among them, the light sensing module integrates a light intensity sensor, a human infrared sensor, a millimeter-wave radar sensor, a temperature and humidity sensor, and a natural light spectrum sensor. It can capture environmental and personnel-related data in all aspects. On the one hand, it can collect environmental parameters such as ambient light intensity, natural light spectrum, ambient temperature and humidity in real time, and accurately identify different lighting scenarios such as daytime, nighttime, cloudy and rainy days, and dusk. On the other hand, it can detect the location, movement trajectory and stay duration of indoor personnel, clarify the presence status of personnel, and provide a reliable basis for energy-saving control and scenario adaptation. The activity recognition module is equipped with a low-power camera and edge computing unit. It adopts human posture recognition and deep learning algorithms to accurately identify the user's current activity type. It can clearly distinguish between various states such as reading, working, watching movies, dining, resting and no one is present. At the same time, in order to protect data privacy, all image data is processed only locally and is not transmitted to the cloud, which ensures recognition efficiency and effectively avoids privacy leakage. The communication and coordination module in the control components plays a core role in data transmission and device linkage, building a communication bridge between the internal devices and between the devices and external equipment to ensure efficient data flow and accurate command transmission. Internally, the communication and coordination module enables smooth data interaction between the light sensing module, activity recognition module, intelligent control module, and energy-saving optimization module, transmitting environmental data, personnel status, and activity type data collected by the sensing layer to the control layer for analysis and processing in real time. For external linkage, this module supports wireless communication protocols such as Wi-Fi, Bluetooth 5.0, Zigbee, and LoRa, as well as wired connections such as RS485 and Ethernet. It not only enables networking of multiple lighting control devices and cloud algorithm upgrades, but also allows linkage with external smart devices such as curtains, air conditioners, and speakers, constructing an integrated smart home control system that allows lighting control to work collaboratively with other smart devices, enhancing the overall user experience. As the "core brain" of the device, the intelligent control module in the control component combines sensor data, user habits and preset strategies to make precise decisions and adjustments to lighting parameters, while supporting personalized operation by users to meet the dual needs of adaptability and personalization. This module incorporates a scene database and a user habit learning model, employing machine learning and deep learning algorithms. On one hand, it can automatically adjust various parameters of the lighting system based on environmental data (such as light intensity and spectrum) from the light sensing module and the user activity type identified by the activity recognition module. For example, in reading mode, it outputs 4000K neutral white light to ensure visual comfort; in movie mode, it reduces brightness and switches to 3000K warm color tone to create an immersive atmosphere; and in office mode, it outputs 5000K–6000K cool white light to improve work focus. It also achieves stepless brightness adjustment, precise color temperature switching from 2700K to 6500K, and smooth transitions in lighting parameters, avoiding discomfort caused by sudden changes in lighting. On the other hand, the intelligent control module receives manual control commands and personalized customization requests from users through the user settings interface on the user terminal. Users can customize lighting scene parameters, set multiple user permissions, and link other smart home devices through various convenient methods such as mobile APP, intelligent voice assistant, local touchscreen, and physical remote control to achieve lighting control modes that suit their own habits. Customized scenes are also stored synchronously in the scene database for quick subsequent retrieval, meeting the personalized needs of different users. The energy-saving optimization module works in collaboration with the intelligent control module and the light sensing module to execute a full-process energy-saving control strategy based on real-time data. This minimizes energy consumption while ensuring a good lighting experience, achieving a balance between energy saving and practicality. The specific energy-saving strategies cover four aspects: first, personnel detection energy saving—when the light sensing module detects no one in the room, it automatically dims or turns off the lights after a delay to avoid unnecessary energy consumption; second, natural light utilization energy saving—when there is sufficient outdoor natural light, it automatically reduces indoor lighting power to fully utilize natural light resources and reduce artificial lighting energy consumption; third, time-of-use optimization energy saving—it optimizes the lighting system's operating parameters based on the differences in peak and off-peak electricity consumption, reducing energy consumption during peak hours and rationally controlling electricity costs; and fourth, low-power standby—when the device is not started or idle, it automatically switches to a low-power standby mode to reduce its own energy loss and further improve energy-saving effects. The self-learning function of the intelligent control module is the core advantage of the device's "adaptive" capability. By continuously learning user habits, it constantly optimizes control strategies and recognition accuracy, improving the adaptability and intelligence level of lighting control. This module uses machine learning and deep learning algorithms to record user data such as lighting parameter adjustment habits and usage patterns in different scenarios, gradually building a personalized control model tailored to user needs. Simultaneously, based on long-term collected environmental and activity recognition data, it continuously optimizes the accuracy of the activity recognition algorithm, reducing recognition errors and ensuring more precise lighting adjustment that better meets actual user needs, achieving an adaptive effect that becomes "smarter with use." In summary, the entire device forms a complete closed-loop workflow through data collection by the sensing module, data transmission by the communication module, decision-making and adjustment by the intelligent control module, and energy-saving optimization by the energy-saving module. This achieves automatic adaptive lighting control in multiple scenarios, supports user customization, and balances energy efficiency and practicality, making it suitable for various indoor and outdoor lighting scenarios.

[0023] The control method of the above-mentioned multi-scene adaptive lighting control device is characterized by including the following steps: S1. The light sensing module collects environmental parameters and personnel status data in real time. S2. The activity recognition module performs image and behavior analysis locally to identify the user's current activity type. S3, the intelligent control module integrates environmental and activity data to match the optimal lighting control strategy; S4. Drive the lighting equipment to perform smooth adjustment of brightness, color temperature, and zoned illumination; S5, the energy-saving optimization module simultaneously executes energy-saving control that combines unmanned energy saving with natural light complementary energy saving control; S6. Users can adjust parameters or edit custom scenes through the user settings interface; S7 The device continuously collects user behavior data, optimizes control logic through self-learning algorithms, and supports cloud-based algorithm upgrades.

[0024] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A multi-scene adaptive lighting control device, comprising a control component, a user terminal, and a lighting lamp, characterized in that: The control components include an installation box (1), which contains a control panel (6), an energy-saving optimization module, a communication collaboration module, and an intelligent control module. The installation box (1) has heat dissipation holes (5) on both sides. The side wall of the installation box (1) has a door (2), and the side wall of the door (2) has a keyhole (3). A key (4) is placed in the keyhole (3). The side wall of the door (2) has a viewing window (7). The outer wall of the lighting lamp has a light sensing module and an activity recognition module. The user terminal includes a user setting interface.

2. The multi-scene adaptive lighting control device according to claim 1, characterized in that: The illumination sensing module is used to collect ambient light intensity, personnel presence status, ambient temperature and humidity, and natural light spectrum data in real time; the activity recognition module is used to identify the user's current activity type based on vision and multi-sensor fusion technology. The intelligent control module is used to automatically adjust the brightness, color temperature, color rendering index, and zoned illumination status of the lighting system based on environmental data and user activity types; the user setting interface is used to provide users with manual control and personalized lighting scene customization functions; the energy-saving optimization module is used to execute lighting energy-saving control strategies based on personnel activity status and ambient natural light intensity; the communication and coordination module is used to realize data transmission between various modules within the device and linkage control with external intelligent devices.

3. The multi-scene adaptive lighting control device according to claim 2, characterized in that: The light sensing module includes a light intensity sensor, a human infrared sensor, a millimeter-wave radar sensor, a temperature and humidity sensor, and a natural light spectrum sensor. It can identify light environments such as daytime, nighttime, cloudy / rainy days, and dusk, and detect the location, movement trajectory, and duration of stay of people indoors.

4. The multi-scene adaptive lighting control device according to claim 3, characterized in that: The activity recognition module is equipped with a low-power camera and an edge computing unit. It uses human posture recognition and deep learning algorithms to recognize reading, working, watching movies, dining, resting, and unattended states. The image data is processed locally and is not transmitted to the cloud.

5. A multi-scene adaptive lighting control device according to claim 4, characterized in that: The intelligent control module has a built-in scene database and user habit learning model, which can realize stepless brightness adjustment, precise switching of color temperature from 2700K to 6500K and smooth transition of lighting parameters; it outputs 4000K neutral white light in reading mode, reduces brightness and switches to 3000K warm color tone in movie mode, and outputs 5000K–6000K cool white light in office mode.

6. The multi-scene adaptive lighting control device according to claim 5, characterized in that: The user settings interface includes a mobile app, a smart voice assistant, a local touchscreen, and a physical remote control, supporting user-defined lighting scenes, multi-user permission management, and integration with smart home devices such as curtains, air conditioners, and speakers.

7. A multi-scene adaptive lighting control device according to claim 6, characterized in that: The energy-saving strategies implemented by the energy-saving optimization module include: dimming or turning off the lighting when no one is detected, reducing indoor lighting power when there is sufficient outdoor natural light, optimizing lighting operation according to peak and off-peak electricity consumption periods, and enabling the device to operate in low-power standby mode.

8. A multi-scene adaptive lighting control device according to claim 7, characterized in that: The communication and collaboration module supports Wi-Fi, Bluetooth 5.0, Zigbee, LoRa wireless communication protocols as well as RS485 and Ethernet wired connections, enabling multi-device networking, cloud algorithm upgrades, and unified lighting control across multiple areas.

9. A multi-scene adaptive lighting control device according to claim 8, characterized in that: The intelligent control module employs machine learning and deep learning algorithms, enabling it to learn user habits and continuously optimize activity recognition accuracy and lighting control strategies.

10. The control method of the multi-scene adaptive lighting control device according to claims 1-9, characterized in that: Includes the following steps: S1. The light sensing module collects environmental parameters and personnel status data in real time. S2. The activity recognition module performs image and behavior analysis locally to identify the user's current activity type. S3, the intelligent control module integrates environmental and activity data to match the optimal lighting control strategy; S4. Drive the lighting equipment to perform smooth adjustment of brightness, color temperature, and zoned illumination; S5, the energy-saving optimization module simultaneously executes energy-saving control that combines unmanned energy saving with natural light complementary energy saving control; S6. Users can adjust parameters or edit custom scenes through the user settings interface; S7 The device continuously collects user behavior data, optimizes control logic through self-learning algorithms, and supports cloud-based algorithm upgrades.

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