MCU mode control circuit and method

Abstract

The present application discloses an MCU mode control circuit and method, which relates to the field of intelligent lighting control technology. The present application divides the target lighting area into multiple sub-areas through a segmentation module, and each sub-area is equipped with an independent MCU, sensor and lighting equipment. The detection module includes a first mode, a second mode and a third mode, which are respectively used to predict the user's entry into the sub-area, detect the user's activities in the sub-area in real time, and judge the need to merge or split multiple sub-areas. The control module performs preloading, real-time adjustment and area merging / splitting operations of lighting parameters based on the information generated by each mode. The present application uses multiple sensors to collaboratively perceive user activities and environmental changes, combined with a distributed decision-making algorithm, to achieve collaborative control between sub-areas, thereby improving the flexibility, energy efficiency and user experience of the system. Through the above method, the present application can provide personalized, energy-saving and efficient lighting solutions.

Description

Technical Field

[0001] The present application relates to the field of intelligent lighting control technology, and in particular to an MCU mode control circuit and method. Background Art

[0002] With the development of intelligent lighting technology, more and more solutions have been proposed to improve the energy efficiency of lighting systems and user experience. For example, Chinese patent publication number CN111757569B discloses an intelligent lighting control method that simulates the daylight spectrum pattern. This method is mainly used in long-term workplaces. Through zoning control and daylight coordination strategies, it achieves energy savings and provides a lighting environment that conforms to physiological rhythms. The patent proposes a method for dividing areas based on their distance from windows. Using light sensors in different areas, it automatically adjusts the brightness and color temperature of the lighting in each area to simulate the changes in natural daylight.

[0003] However, these approaches have some shortcomings. For example, they primarily focus on leveraging the coordinated control of natural and artificial lighting, but in practice, their ability to respond to user activity in real time is limited. Furthermore, these approaches primarily rely on fixed adjustment strategies, failing to fully consider users' real-time activity and personalized needs. This leads to limited flexibility and adaptability in complex and changing usage scenarios. These limitations leave significant room for improvement in existing lighting systems in terms of user experience and energy efficiency optimization. Summary of the Invention

[0004] In response to the deficiencies in the prior art, the present application discloses an MCU mode control circuit and method.

[0005] In a first aspect, the present application provides an MCU mode control circuit, comprising:

[0006] A segmentation module, configured to divide the target lighting area into a plurality of sub-areas; wherein each sub-area is provided with at least one lighting device, a sensor, and an MCU;

[0007] The detection module includes: a first mode, a second mode, and a third mode; wherein the first mode includes: generating first mode information in response to a sub-area having no users within it and detecting that a user is about to enter the sub-area; the second mode includes: generating second mode information in response to a user being present in a sub-area by detecting the user's location, activity type, and scene information in real time; and the third mode includes: generating third mode information in response to a user being present in at least two sub-areas within the target lighting area by detecting the user activity density and activity type within the sub-areas containing the users;

[0008] The control module controls the lighting device, the sensor, and the MCU in the target lighting area to execute a preset lighting strategy based on at least one of the first mode information, the second mode information, and the third mode information.

[0009] As an optional implementation, the first mode further includes: detecting the acceleration and direction of the user through a motion sensor, determining the user's movement path based on historical data and real-time data, and determining whether the user is about to enter a sub-area; wherein the historical data includes historical movement data and historical preference data;

[0010] The lighting strategy includes: based on the first mode information, controlling the MCU of the sub-area to preload the lighting parameter data preset for the sub-area; wherein the lighting parameter data includes: brightness, color temperature, scene mode and user preference.

[0011] As an optional implementation manner, the second mode further includes:

[0012] Real-time detection of user location, activity type, and scene information through sensors in sub-areas;

[0013] The lighting strategy includes: determining scene requirement information of the sub-area based on the second mode information, and adjusting the lighting equipment of the sub-area based on the scene requirement information.

[0014] As an optional implementation manner, the third mode further includes:

[0015] Detecting user activity density and activity type through sensors within the target lighting area;

[0016] The lighting strategy includes: determining, based on the third mode information, multi-sub-area merging requirement information; and merging multiple adjacent sub-areas into a large area based on the multi-sub-area merging requirement information; wherein the lighting devices, sensors, and MCU in the large area are uniformly adjusted;

[0017] Based on the third mode information, determine the splitting requirement information of the large area merged by multiple sub-areas; and based on the splitting requirement information, restore the large area to multiple independent sub-areas before the merger, and restore the independent control status of the lighting equipment, sensors, and MCU within each sub-area.

[0018] As an optional implementation manner, determining the multi-sub-region merging requirement information includes:

[0019] The user activity state detected by the motion sensor and the sound sensor is identified to determine the current activity type; in response to the user activity density in the adjacent sub-area being greater than or equal to a preset value and the current activity type in the adjacent sub-area being a first preset activity, the adjacent multiple sub-areas are merged into a large area.

[0020] As an optional implementation manner, determining the splitting requirement information of a large area merged from multiple sub-areas includes:

[0021] In response to the user activity density in the large area being lower than a preset value and the current activity type in the large area being a second preset activity, the large area is restored to the multiple independent sub-areas before the merger.

[0022] As an optional implementation, the sensor includes: a motion sensor, a sound sensor, a light sensor, and a temperature sensor; wherein:

[0023] The motion sensor is used to detect the user's acceleration, direction and activity frequency;

[0024] The sound sensor is used to capture volume and spectrum changes in the environment;

[0025] The light sensor is used to monitor changes in ambient light intensity;

[0026] The temperature sensor is used to monitor changes in ambient temperature to assist in adjusting the color temperature of the lighting device.

[0027] As an optional implementation, a communication network is provided between the MCUs of each sub-area; the communication network is used to enable the MCUs of each sub-area to share the first mode information, the second mode information, and the third mode information of each sub-area.

[0028] As an optional implementation manner, the MCUs of each sub-area adopt a distributed decision algorithm based on the shared first mode information, the second mode information, and the third mode information to jointly determine the merging requirement information and the splitting requirement information;

[0029] The distributed decision-making algorithm includes: the MCU in each sub-area receives and analyzes the shared pattern information, and independently calculates local merge or split suggestions based on a preset user activity density threshold and activity type;

[0030] The MCU of each sub-area sends the locally calculated merge or split suggestion to the MCU of the adjacent sub-area via the communication network;

[0031] The MCU of each sub-region adopts a distributed consensus algorithm to vote on the collected merger or split suggestions; when the preset consensus conditions are reached, the final merger requirement information or the split requirement information is determined.

[0032] In a second aspect, the present application further provides an MCU mode control method, comprising:

[0033] Divide the target lighting area into multiple sub-areas; each sub-area is provided with at least one lighting device, a sensor, and an MCU;

[0034] In response to there being no user in a sub-area and detecting that a user is about to enter the sub-area, generating first mode information;

[0035] In response to a user being present in a certain sub-area, detecting the user's location, activity type, and scene information in real time, and generating second mode information;

[0036] In response to the presence of users in at least two sub-areas in the target lighting area, detecting user activity density and activity type within the sub-areas where the users are present, and generating third pattern information;

[0037] Based on at least one of the first mode information, the second mode information, and the third mode information, the lighting device, the sensor, and the MCU within the target lighting area are controlled to execute a preset lighting strategy.

[0038] Compared with the existing technology, the beneficial effects of the present invention are: flexible lighting control is achieved by dynamically managing the merging and splitting of sub-areas, and the lighting range is automatically adjusted according to the density and type of user activities; lighting parameters are preloaded in advance based on user historical behavior and real-time data to ensure that users can enjoy a personalized lighting experience when entering the sub-area; user activities and environmental changes are perceived through multi-sensor collaboration to accurately adjust the lighting; a distributed decision-making algorithm is used to achieve collaborative control of the MCUs in each sub-area, thereby improving the robustness and response speed of the system; at the same time, through real-time adjustment strategies and efficient energy consumption management, the energy efficiency of the lighting system and user experience are significantly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A schematic diagram of the system structure of the MCU mode control circuit provided in an embodiment of the present disclosure;

[0040] Figure 2 This is a flowchart of the MCU mode control method provided in an embodiment of the present disclosure.

[0041] Reference numerals: 10, segmentation module; 20, detection module; 30, control module. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0043] See Figure 1 , Figure 1 A schematic diagram of the system structure of the MCU mode control circuit provided in an embodiment of the present disclosure includes:

[0044] A segmentation module 10 is used to divide the target lighting area into multiple sub-areas; wherein each sub-area is provided with at least one lighting device, a sensor, and an MCU;

[0045] The detection module 20 includes a first mode, a second mode, and a third mode. The first mode includes generating first mode information in response to detecting that a user is about to enter a sub-area and that there is no user in the sub-area. The second mode includes generating second mode information by detecting the user's location, activity type, and scene information in real time in response to the presence of a user in the sub-area. The third mode includes generating third mode information by detecting the user activity density and activity type in the sub-area containing the user in response to the presence of a user in at least two sub-areas within the target lighting area.

[0046] The control module 30 controls the lighting device, the sensor, and the MCU in the target lighting area to execute a preset lighting strategy based on at least one of the first mode information, the second mode information, and the third mode information.

[0047] The detection module 20 and the control module 30 can be built into the MCU of each sub-area. The entire target lighting area can be equipped with a central controller for deploying the segmentation modules 10 and the control module 30 for controlling the entire target lighting area.

[0048] In a specific implementation, the segmentation module 10 is used to divide the target lighting area into multiple sub-areas. Each sub-area is equipped with at least one lighting device, a sensor, and an MCU to enable independent control of that sub-area. The principle of segmentation is to divide a large area into multiple independently controllable sub-areas based on the functionality of the space and the characteristics of user activities. For example, an open office can be divided into several workstation areas, each equipped with corresponding lighting devices and sensors to collect data such as ambient light and user activities.

[0049] The detection module 20 is responsible for collecting and analyzing data in different working modes to achieve precise lighting control. The detection module 20 includes three modes:

[0050] The first mode is activated when a user is detected about to enter a sub-area and no users are present. In this mode, the system generates first mode information, which is used to preload the sub-area's lighting parameters, ensuring that the lighting equipment is in its default state before the user enters. For example, by using motion sensors to detect the user's movement path and speed, the system determines whether the user is about to enter the sub-area and sends a preload instruction to the MCU.

[0051] Second Mode: Second Mode activates when a user is present within a sub-area. In this mode, the system detects the user's location, activity type, and scene information in real time, generating second-mode information to appropriately adjust lighting parameters such as brightness and color temperature. For example, if a user is reading within a sub-area, the system uses sensors to collect activity data and automatically adjusts the lighting brightness to a suitable level for reading.

[0052] Third Mode: This mode activates when users are present in at least two sub-areas within the target lighting area. In this mode, the system detects user activity density and activity type, generating third mode information to determine whether to merge adjacent sub-areas into a larger area or restore them to independent sub-areas. For example, during an office meeting, where user activity density is high across multiple adjacent sub-areas, the system uses third mode to merge the sub-areas, centrally managing lighting equipment and providing a suitable lighting environment for the meeting.

[0053] The control module 30 controls the lighting devices, sensors, and MCU within the target lighting area to execute a preset lighting strategy based on the first mode information, second mode information, and third mode information generated by the detection module 20. The main functions of this module include:

[0054] Based on the first mode information: when a user is about to enter a sub-area, the lighting parameter data of the sub-area, such as brightness, color temperature and scene mode, is preloaded to ensure that the lighting is ready before the user enters.

[0055] Based on the second mode information: adjust the lighting equipment in the sub-area in real time, optimize the lighting effect according to the user's activity type and scene requirements, such as automatically adjusting the brightness and color temperature.

[0056] Based on the third mode information: sub-areas are dynamically merged or split. When user activity density is high or specific activity types occur, adjacent sub-areas are merged into a large area and lighting equipment is adjusted uniformly. When user activity density decreases, the independent control state of the sub-areas is restored to ensure the rational allocation of lighting resources and energy efficiency optimization.

[0057] In a specific implementation, the system is initialized: when the system starts, the segmentation module 10 divides the target lighting area into multiple sub-areas, and the MCU in each sub-area is initialized and connected to the communication network. When a user enters the range of a certain sub-area, the detection module 20 enters the first mode, predicts that the user is about to enter the sub-area, and triggers the MCU to preload the corresponding lighting parameters. After the user enters the sub-area, the detection module 20 switches to the second mode, collects user data in real time and adjusts the lighting equipment to ensure that the lighting environment meets user needs. If it is detected that the user activity density in adjacent sub-areas is high, the system merges the sub-areas through the third mode for unified lighting control; when the user activity density decreases, the system automatically splits the sub-areas and restores independent control of each sub-area.

[0058] For example, in an open office space, the segmentation module 10 divides the space into several sub-areas, each of which is equipped with an MCU, lighting equipment, and sensors. When an employee enters the office space, the first mode of the detection module 20 is activated, and the lighting parameters of the area are preloaded in advance. When the employee is active at the workstation, the system switches to the second mode and adjusts the lighting in real time to meet work needs. If the user activity density in multiple adjacent areas is high within a certain time period, such as during team collaboration, the system merges these sub-areas through the third mode and uniformly adjusts the lighting to provide the lighting environment required for collaboration. After the activity ends, the system automatically splits the sub-areas according to the actual situation and resumes independent control.

[0059] In this way, the MCU mode control circuit of the present invention can efficiently manage and optimize the intelligent control of the lighting area, thereby improving the flexibility, energy efficiency and user experience of the lighting system.

[0060] As an optional implementation, the sensor includes: a motion sensor, a sound sensor, a light sensor, and a temperature sensor; wherein:

[0061] The motion sensor is used to detect the user's acceleration, direction and activity frequency;

[0062] The sound sensor is used to capture volume and spectrum changes in the environment;

[0063] The light sensor is used to monitor changes in ambient light intensity;

[0064] The temperature sensor is used to monitor changes in ambient temperature to assist in adjusting the color temperature of the lighting device.

[0065] Motion sensors (such as accelerometers and infrared sensors) are used to detect a user's acceleration, movement direction, and activity frequency. This data allows real-time tracking of the user's movement trajectory, determining whether the user is stationary, walking, or engaging in high-frequency activity. For example, if a user is detected moving frequently within a subarea, the detection module 20 can identify the user as engaging in high-activity activities such as exercise or a stand-up meeting.

[0066] The sound sensor captures changes in ambient sound, including volume and spectral characteristics. By analyzing this sound data, it identifies the user's activity type, such as conversation, music playback, or quiet rest. For meetings, the control module 30 can automatically adjust the lighting to a moderate brightness and cool color temperature by identifying persistent conversation and high volume, enhancing focus in meetings.

[0067] The light sensor monitors changes in ambient light intensity in real time. When the external light level changes significantly, such as when daylight gradually decreases or the weather outside suddenly gets dark, the control module 30 automatically adjusts the indoor lighting brightness to maintain a stable light level, ensuring that the user is always in an appropriate lighting environment.

[0068] Temperature sensors monitor temperature changes within sub-areas and assist in adjusting the color temperature of lighting. Control module 30 adjusts the color temperature of the lighting based on ambient temperature to provide a more comfortable lighting experience. For example, in warmer environments, the system might adjust to a cooler color temperature to reduce visual fatigue and provide a refreshing sensation; while in cooler environments, it might adjust to a warmer color temperature to enhance comfort and warmth.

[0069] In a specific implementation, the data from each sensor is integrated and analyzed by the control module 30, and the lighting parameters are dynamically adjusted based on the integrated sensor data.

[0070] In this way, through the collaborative work of multiple sensors, the control module 30 can accurately perceive the user's multi-dimensional activities and environmental changes, thereby making more precise lighting adjustments.

[0071] As an optional implementation, the first mode further includes: detecting the acceleration and direction of the user through a motion sensor, determining the user's movement path based on historical data and real-time data, and determining whether the user is about to enter a sub-area; wherein the historical data includes historical movement data and historical preference data;

[0072] The lighting strategy includes: based on the first mode information, controlling the MCU of the sub-area to preload the lighting parameter data preset for the sub-area; wherein the lighting parameter data includes: brightness, color temperature, scene mode and user preference.

[0073] In practice, motion sensors deployed within the sub-areas, such as accelerometers, passive infrared sensors, and ultrasonic sensors, can be used to collect user acceleration and directional change data. For example, when a user walks from an office area to a conference room, the sensors can detect the user's movement acceleration and directional change.

[0074] Furthermore, by analyzing historical and real-time user movement data, path prediction algorithms (such as Kalman filtering or Bayesian prediction) can be used to predict a user's movement path. For example, by combining a user's past movement patterns within an office space with their current movement data, it is possible to predict whether the user will enter a specific sub-area (such as a conference room).

[0075] When it is predicted that a user is about to enter a sub-area (such as a conference room), the MCU in that area automatically triggers the preloading of lighting parameters.

[0076] Among them, the preloaded lighting parameters can include brightness, color temperature, scene mode and user preference settings. For example, the preset lighting parameters for a conference room can be high-brightness, cool-toned light to promote concentration. At the same time, based on user preferences, specific scene modes such as "meeting mode" or "discussion mode" may be enabled in that area. The above preloaded lighting parameters are stored in the local storage of the MCU so that they can be quickly loaded and applied when the user enters. For example, when a user approaches a conference room, the system loads the lighting settings of the conference room in advance to ensure that the light is adjusted to the optimal state when the user enters.

[0077] It is understandable that the above-mentioned analysis of user preference settings and user historical movement data (movement habits) is performed based on user identity identification, that is, the preference settings and movement habits of different users may be different.

[0078] For example, an employee walks from their office to a conference room, preparing to attend a meeting. The detection module 20 uses a motion sensor to detect the employee's acceleration and direction, predicting that they are about to enter the conference room. Based on this prediction, the conference room's lighting parameters, such as brightness and color temperature, are pre-loaded. This way, when the employee enters the conference room, the lighting is already adjusted to a suitable setting, improving the user experience.

[0079] For example, a user walks from the living room to the bedroom to rest. Detection module 20 uses motion sensors to capture the user's movement path and speed, predicting that the user is about to enter the bedroom. It then preloads bedroom lighting parameters, such as low brightness and warm tones, to create a comfortable resting environment. This way, when the user enters the bedroom, the lighting environment is already adjusted to the desired setting, without manual adjustment.

[0080] As an optional implementation, a personalized learning module can be used to continuously accumulate historical user behavior data and analyze it in combination with real-time sensor data to achieve personalized lighting adjustments.

[0081] In a specific implementation, the detection module 20 can record each user's lighting parameter settings (e.g., brightness, color temperature, scene mode) and the corresponding activity type (e.g., work, rest, party) each time they use a sub-area. This data is stored in the system's local database or in the cloud, forming a personalized user behavior profile. Machine learning algorithms (e.g., collaborative filtering-based recommendation algorithms or decision tree models) analyze historical preference data to build a user lighting preference model. For example, it can be determined that a user prefers higher brightness and cooler color temperatures when working, but prefers lower brightness and warmer color temperatures when resting.

[0082] When a user re-enters a sub-area, the system combines real-time information such as user activity type, ambient light, and time of day to match the user's preference model. Lighting parameters are dynamically adjusted based on the matching results. For example, if the system detects that the user is working at night, it can automatically adjust the lighting to the user's preferred working mode parameters instead of the default nighttime rest mode.

[0083] By predicting the user's movement path and preloading lighting parameters in advance, the system can provide the optimal lighting environment when the user enters a sub-area, eliminating the need for users to wait or manually adjust the lighting after entering. Preloading is triggered only when the user is about to enter a specific area, avoiding unnecessary energy consumption and improving the overall energy efficiency of the system. By analyzing historical user behavior and real-time data, the system can flexibly adjust lighting parameters to meet the personalized needs and preferences of different users.

[0084] As an optional implementation manner, the second mode further includes:

[0085] Real-time detection of user location, activity type, and scene information through sensors in sub-areas;

[0086] The lighting strategy includes: determining scene requirement information of the sub-area based on the second mode information, and adjusting the lighting equipment of the sub-area based on the scene requirement information.

[0087] In practice, the second mode aims to dynamically adjust lighting device parameters by real-time monitoring of user behavior and environmental changes. This, combined with pre-loaded lighting parameters, enables efficient and flexible lighting control. When a user enters a sub-area, the detection module 20 switches from the first mode to the second mode, activating real-time monitoring. Motion sensors within the sub-area (such as infrared or ultrasonic sensors) capture the user's location information. By tracking the user's movement path, the control module 30 can accurately determine the user's current activity area.

[0088] Before a user enters a sub-area, the control module 30 preloads the initial lighting parameters for that area, including brightness, color temperature, and scene mode, using the first mode. These preloaded parameters are based on the user's historical behavior and preferences. For example, if a user enters the office during work hours, the system will preload high brightness and cool color temperature settings suitable for work environments. Once the user enters, the second mode's real-time monitoring function takes effect immediately. Motion and sound sensors further capture the user's real-time activity, such as whether they are sitting down to work or standing to talk.

[0089] Based on this real-time data, the control module 30 adjusts pre-loaded lighting parameters to better suit the current user's specific needs. For example, if the pre-loaded parameters are set to high brightness for work mode, but the control module 30 detects in real time that the user is relaxing, it will gradually reduce the brightness to a softer, warmer color temperature to suit the user's restful state. This dynamic adjustment mechanism ensures that the lighting environment adapts to the user's activities, thereby improving the user experience.

[0090] Furthermore, environmental data provided by light and temperature sensors also contribute to the real-time adjustment process. When external light intensity changes significantly, such as during a sudden cloudy day or sunset, the control module 30 automatically adjusts the indoor lighting brightness to maintain a consistent light level. The temperature sensor also assists in adjusting the color temperature, ensuring a comfortable lighting environment regardless of temperature.

[0091] This combination of pre-loaded lighting and real-time adjustment not only allows for a quick response to initial user needs, but also optimizes lighting parameters as user activity changes. This continuous intelligent control delivers a consistent, comfortable lighting experience across different scenarios while effectively reducing energy consumption and avoiding over-lighting or unnecessary parameter adjustments.

[0092] As an optional implementation manner, the third mode further includes:

[0093] Detecting user activity density and activity type through sensors within the target lighting area;

[0094] The lighting strategy includes: determining, based on the third mode information, multi-sub-area merging requirement information; and merging multiple adjacent sub-areas into a large area based on the multi-sub-area merging requirement information; wherein the lighting devices, sensors, and MCU in the large area are uniformly adjusted;

[0095] Based on the third mode information, determine the splitting requirement information of the large area merged by multiple sub-areas; and based on the splitting requirement information, restore the large area to multiple independent sub-areas before the merger, and restore the independent control status of the lighting equipment, sensors, and MCU within each sub-area.

[0096] In a specific implementation, the MCU mode control circuit of the present invention, in the third mode, dynamically decides whether to merge multiple sub-areas into a large area or split the large area back into multiple independent sub-areas by real-time detection of user activity density and activity type, so as to optimize lighting control and resource allocation.

[0097] When user activity is detected in multiple sub-areas within the target lighting area, the detection module 20 enters the third mode. Motion and sound sensors within each sub-area collect real-time user activity data, including activity frequency, dwell time, and ambient noise level. This data can be used to determine the user activity density within each sub-area. For example, within an open office space, the detection module 20 may detect frequent user activity within multiple adjacent workstations through sensors. This density is particularly high during team collaboration or discussions.

[0098] After determining that user activity density has reached a preset threshold, the activity types within these sub-areas are analyzed. If the user activity types within multiple adjacent sub-areas are consistent, such as meetings or gatherings, the control module 30 determines that these sub-areas need to be merged and issues a merge instruction, merging them into a larger area. After merging, the lighting devices, sensors, and MCUs within all merged areas are managed according to a unified lighting strategy, such as adjusting the brightness and color temperature to suit meetings or gatherings, providing a consistent lighting environment and improving the user experience.

[0099] After the merger is complete, user activity within the larger area continues to be monitored. If the density of user activity drops below a preset threshold and the activity type changes, such as from a high-density meeting to a low-density individual work session, the system triggers a split mechanism. Based on real-time data and activity type, the control module 30 issues a split command, splitting the original large area back into independent sub-areas. After the split, the lighting devices, sensors, and MCUs in each sub-area resume independent control and resume operation according to their respective lighting strategies, avoiding unnecessary energy waste.

[0100] For example, in a large open office space, a team concludes a meeting and members disperse to their respective workstations. At this point, the detection module 20 detects a decrease in activity density within the meeting area, and the control module 30 automatically reverts the meeting area to multiple independent workstation areas. Each area adjusts lighting brightness and color temperature based on individual work needs, achieving precise and energy-efficient lighting management.

[0101] Thus, through the dynamic merging and splitting functions of the third mode, the present invention can flexibly respond to the different needs of users' activities and provide efficient and personalized lighting control in multiple users and multiple scenarios. At the same time, this dynamic management mechanism can effectively improve energy efficiency, optimize resource allocation, and meet the diverse needs of complex environments.

[0102] As an optional implementation manner, determining the multi-sub-region merging requirement information includes:

[0103] The user activity state detected by the motion sensor and the sound sensor is identified to determine the current activity type; in response to the user activity density in the adjacent sub-area being greater than or equal to a preset value and the current activity type in the adjacent sub-area being a first preset activity, the adjacent multiple sub-areas are merged into a large area.

[0104] In practice, to dynamically merge multiple sub-areas, the system detects user activity and environmental changes in real time to identify the need for merging adjacent sub-areas. Specifically, the system uses motion and sound sensors to analyze the density and type of user activity within each sub-area, determining whether these sub-areas should be merged into a larger area.

[0105] In practice, motion sensors within each sub-area continuously collect user motion data, including acceleration, movement direction, and activity frequency. Sound sensors capture ambient sound signals, analyzing volume changes and spectral characteristics. For example, in an office, if multiple users are detected to be active in adjacent sub-areas, and the sound sensors detect continuous conversation and the audio characteristics typical of a meeting, the system can determine the current activity type as a "meeting."

[0106] Once the system identifies that the user activity density within adjacent sub-areas reaches or exceeds a preset value, and the activity type matches a preset high-density activity type such as "meeting" or "party," it generates a merge request message. Based on this information, the control module 30 performs a region merge operation, integrating the lighting equipment, sensors, and MCUs of the relevant sub-areas into the management scope of the larger area.

[0107] For example, in an open office space, detection module 20 detects that employees at three adjacent workstations are engaged in a team discussion. Motion sensors register frequent movement and brief periods of inactivity, while sound sensors capture the loud volume of discussion. Control module 30 identifies the current activity type as "team collaboration" and determines that the three sub-areas need to be merged into a larger area. Control module 30 then adjusts the lighting strategy to provide a uniform lighting environment across the entire area, such as moderate brightness and cool color temperature, to promote collaboration and communication.

[0108] This method can dynamically identify and respond to users' real-time needs, automatically adjusting zoning and lighting strategies to ensure the lighting environment in different activity scenarios always meets user expectations. Furthermore, this flexible zoning management approach effectively improves the system's energy efficiency, avoiding energy waste caused by excessive or insufficient lighting.

[0109] As an optional implementation manner, determining the splitting requirement information of a large area merged from multiple sub-areas includes:

[0110] In response to the user activity density in the large area being lower than a preset value and the current activity type in the large area being a second preset activity, the large area is restored to the multiple independent sub-areas before the merger.

[0111] In practice, to flexibly respond to changing user needs, a large region formed by merging multiple sub-regions needs to be split at appropriate times, restoring it to multiple independent sub-regions. Specifically, by continuously monitoring the density and type of user activity within the large region, the splitting conditions are determined and the corresponding actions are taken.

[0112] In practice, when multiple sub-areas are merged into a larger area, the sensor network continues to collect real-time user activity data. Motion sensors monitor user acceleration, movement frequency, and position changes, while sound sensors capture ambient volume and spectral characteristics. Based on this data, the system calculates the user activity density within the current large area.

[0113] When the user activity density falls below a preset threshold, for example, when most users have left or user activity within the area becomes sparse, the control module 30 further analyzes the activity type. If the detection module 20 detects that the activity type within the current large area has shifted to a lower density, for example, from "meeting" or "gathering" to "personal work" or "rest," the control module 30 determines that the large area no longer needs to be merged.

[0114] Based on this determination, the control module 30 generates splitting requirements and executes the zone splitting operation, breaking the large zone back into its original sub-zones and restoring independent control of each sub-zone. The lighting devices, sensors, and MCUs within each sub-zone operate according to their own independent lighting strategies. For example, after a meeting in a large zone concludes, it is detected that users have dispersed to their respective workstations and gradually reduced their activity. The control module 30 automatically splits the meeting area into independent workstation zones, adjusting the lighting brightness and color temperature for each sub-zone to suit the user's individual work needs.

[0115] This split mechanism ensures that the system can flexibly adjust as user activity changes, meeting the lighting needs of high-intensity events while quickly resuming efficient, personalized lighting management after the event to avoid energy waste. Furthermore, this real-time adjustment capability enhances the system's intelligence, enabling it to consistently provide users with the appropriate lighting environment in different scenarios.

[0116] As an optional implementation, a communication network is provided between the MCUs of each sub-area; the communication network is used to enable the MCUs of each sub-area to share the first mode information, the second mode information, and the third mode information of each sub-area.

[0117] In a specific implementation, the MCUs of each sub-area can be connected via a wired or wireless communication network, such as using a communication protocol such as Wi-Fi, Zigbee, Bluetooth Mesh, or Ethernet. The communication network ensures that each MCU can send and receive mode information from other sub-areas in real time.

[0118] When the MCU of each sub-area is running, the detection module 20 collects information about the area and generates corresponding pattern information, where:

[0119] First mode information: predicts the sub-area that the user is about to enter and sends the preloaded lighting parameter information to the MCU of the sub-area.

[0120] Second mode information: Real-time detection of user location, activity type, and scene information within a sub-area, and sharing with other MCUs to assist in dynamic adjustments between areas.

[0121] Third mode information: when it is detected that the user activity density and activity type meet the merging or splitting conditions, the merging requirement information and the splitting requirement information are shared with the relevant MCU.

[0122] As an optional implementation manner, the MCUs of each sub-area adopt a distributed decision algorithm based on the shared first mode information, the second mode information, and the third mode information to jointly determine the merging requirement information and the splitting requirement information;

[0123] The distributed decision-making algorithm includes: the MCU in each sub-area receives and analyzes the shared pattern information, and independently calculates local merge or split suggestions based on a preset user activity density threshold and activity type;

[0124] The MCU of each sub-area sends the locally calculated merge or split suggestion to the MCU of the adjacent sub-area via the communication network;

[0125] The MCU of each sub-region adopts a distributed consensus algorithm to vote on the collected merger or split suggestions; when the preset consensus conditions are reached, the final merger requirement information or the split requirement information is determined.

[0126] In practice, the MCUs in each sub-area can collaboratively determine when to merge or split areas based on shared pattern information through a distributed decision-making algorithm. This mechanism ensures that the entire lighting system can quickly adapt to changes in user activity, while maintaining efficient and consistent overall lighting control.

[0127] Each sub-region's MCU shares real-time first-mode, second-mode, and third-mode information via a communication network, forming a decentralized information network. Within this network, each MCU independently analyzes the shared information and makes preliminary recommendations for mergers or splits based on its own and neighboring sub-regions' situations.

[0128] Exemplarily, after each MCU receives the shared pattern information, it combines it with local sensor data to calculate the user activity density and activity type. For example, the MCU in a certain sub-area detects that the user activity density in its own area is high, and at the same time receives similar information sent by the MCU in an adjacent sub-area, it determines that regional merging may be required. Based on the preset user activity density threshold and activity type, the MCU independently generates local merge or split suggestions. For example, when the activity density of two adjacent sub-areas exceeds the preset threshold and the activity type is a meeting, the MCU generates a merge suggestion.

[0129] Each sub-region's MCU sends locally generated merge or split proposals to neighboring sub-regions via the communication network. The MCUs that receive these proposals vote and, based on a pre-defined consensus algorithm (such as a Byzantine fault-tolerant algorithm or a majority voting consensus algorithm), decide on the final merge or split operation.

[0130] When consensus conditions are reached (e.g., more than a set percentage of MCUs agree to merge or split), the corresponding area merge or split operation is immediately executed. For example, if more than two-thirds of the relevant MCUs agree to merge, adjacent sub-areas are automatically merged into a large area, and the lighting strategy is adjusted.

[0131] For example, during an exhibition at a multi-functional exhibition hall, the density of visitors within different exhibition areas was detected to be gradually increasing. The MCUs in each sub-area used a distributed decision-making algorithm to analyze visitor traffic and activity types in the local and neighboring areas. Ultimately, they reached a consensus to merge the multiple exhibition areas into a single large area, providing a unified lighting environment for the entire exhibition. After the exhibition, the distributed decision-making algorithm again determined that visitor traffic had returned to normal. The MCUs in each sub-area reached a consensus to split the large area into independent exhibition areas and restore their respective lighting control strategies.

[0132] This decentralized control approach improves the system's robustness and scalability, avoids single points of failure, and enables more efficient response to user needs and environmental changes. At the same time, the distributed consensus mechanism ensures the accuracy and consistency of merge and split operations, improving the user experience and overall system efficiency.

[0133] Based on the same inventive concept, an MCU mode control method corresponding to the MCU mode control circuit is also provided in the embodiment of the present disclosure. Since the principle of solving the problem by the MCU mode control method in the embodiment of the present disclosure is similar to that of the above-mentioned MCU mode control circuit in the embodiment of the present disclosure, the implementation of the method can refer to the implementation of the control circuit, and the repeated parts will not be repeated.

[0134] See Figure 2 , Figure 2 The flowchart of the MCU mode control method provided in the embodiment of the present disclosure includes steps S101 to S105, wherein:

[0135] S101: Divide the target lighting area into multiple sub-areas; each sub-area is provided with at least one lighting device, a sensor, and an MCU;

[0136] S102: In response to there being no user in a sub-area and detecting that a user is about to enter the sub-area, generating first mode information;

[0137] S103: In response to a user existing in a certain sub-area, detecting the user's location, activity type, and scene information in real time, and generating second mode information;

[0138] S104: In response to the presence of users in at least two sub-areas in the target lighting area, detecting user activity density and activity type within the sub-areas where the users are located, and generating third pattern information;

[0139] S105: Based on at least one of the first mode information, the second mode information, and the third mode information, control the lighting device, the sensor, and the MCU in the target lighting area to execute a preset lighting strategy.

[0140] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present application. The preferred embodiments do not describe all details in detail, nor do they limit the present application to specific embodiments. Obviously, many modifications and variations can be made based on the contents of this specification. This specification selects and describes these embodiments in detail to better explain the principles and practical applications of the present application, so that those skilled in the art can better understand and utilize the present application. The present application is limited only by the claims and their full scope and equivalents.

Claims

1. MCU mode control circuit, characterized in that, include: A segmentation module, configured to divide the target lighting area into a plurality of sub-areas; wherein each sub-area is provided with at least one lighting device, a sensor, and an MCU; The detection module includes: a first mode, a second mode, and a third mode; wherein the first mode includes: generating first mode information in response to a sub-area having no users within it and detecting that a user is about to enter the sub-area; the second mode includes: generating second mode information in response to a user being present in a sub-area by detecting the user's location, activity type, and scene information in real time; and the third mode includes: generating third mode information in response to a user being present in at least two sub-areas within the target lighting area by detecting the user activity density and activity type within the sub-areas containing the users; a control module, configured to control the lighting device, the sensor, and the MCU within the target lighting area to execute a preset lighting strategy based on at least one of the first mode information, the second mode information, and the third mode information; The first mode further includes: detecting the acceleration and direction of the user through a motion sensor, determining the user's movement path based on historical data and real-time data, and determining whether the user is about to enter a sub-area; wherein the historical data includes historical movement data and historical preference data; the historical movement data and historical preference data of different users are independent; The lighting strategy includes: based on the first mode information, controlling the MCU of the sub-area to preload the lighting parameter data preset for the sub-area; wherein the lighting parameter data includes: brightness, color temperature, scene mode and user preference; The lighting strategy includes: determining, based on the third mode information, multi-sub-area merging requirement information; and merging multiple adjacent sub-areas into a large area based on the multi-sub-area merging requirement information; wherein the lighting devices, sensors, and MCU in the large area are uniformly adjusted; Determining, based on the third mode information, splitting requirement information for a large area formed by merging multiple sub-areas; and restoring, based on the splitting requirement information, the large area back to multiple independent sub-areas before the merger, and restoring the independent control states of the lighting devices, sensors, and MCUs within each sub-area; The second mode also includes: Real-time detection of user location, activity type, and scene information through sensors in sub-areas; The lighting strategy includes: determining scene requirement information of a sub-area based on the second pattern information, and adjusting lighting equipment of the sub-area based on the scene requirement information; The third mode also includes: The density and type of user activities are detected by sensors within the target lighting area.

2. The MCU mode control circuit according to claim 1, wherein: Determining the multi-sub-region merging requirement information includes: The user activity state detected by the motion sensor and the sound sensor is identified to determine the current activity type; in response to the user activity density in the adjacent sub-area being greater than or equal to a preset value and the current activity type in the adjacent sub-area being a first preset activity, the adjacent multiple sub-areas are merged into a large area.

3. The MCU mode control circuit according to claim 2, characterized in that: The determining of splitting requirement information of a large area formed by merging multiple sub-areas includes: In response to the user activity density in the large area being lower than a preset value and the current activity type in the large area being a second preset activity, the large area is restored to the multiple independent sub-areas before the merger.

4. The MCU mode control circuit according to claim 3, characterized in that: The sensors include: a motion sensor, a sound sensor, a light sensor, and a temperature sensor; wherein: The motion sensor is used to detect the user's acceleration, direction and activity frequency; The sound sensor is used to capture volume and spectrum changes in the environment; The light sensor is used to monitor changes in ambient light intensity; The temperature sensor is used to monitor changes in ambient temperature to assist in adjusting the color temperature of the lighting device.

5. The MCU mode control circuit according to claim 4, wherein: A communication network is provided between the MCUs of each sub-area; the communication network is used to enable the MCUs of each sub-area to share the first mode information, the second mode information, and the third mode information of each sub-area.

6. The MCU mode control circuit according to claim 5, characterized in that: The MCU of each sub-area adopts a distributed decision algorithm based on the shared first mode information, the second mode information, and the third mode information to jointly determine the merging requirement information and the splitting requirement information; The distributed decision-making algorithm includes: the MCU in each sub-area receives and analyzes the shared pattern information, and independently calculates local merge or split suggestions based on a preset user activity density threshold and activity type; The MCU of each sub-area sends the locally calculated merge or split suggestion to the MCU of the adjacent sub-area via the communication network; The MCU of each sub-region adopts a distributed consensus algorithm to vote on the collected merger or split suggestions; when the preset consensus conditions are reached, the final merger requirement information or the split requirement information is determined.

7. MCU mode control method, characterized in that, include: Divide the target lighting area into multiple sub-areas; each sub-area is provided with at least one lighting device, a sensor, and an MCU; In response to there being no user in a sub-area and detecting that a user is about to enter the sub-area, generating first mode information; In response to a user being present in a certain sub-area, detecting the user's location, activity type, and scene information in real time, and generating second mode information; In response to the presence of users in at least two sub-areas in the target lighting area, detecting user activity density and activity type within the sub-areas where the users are present, and generating third pattern information; Based on at least one of the first mode information, the second mode information, and the third mode information, controlling the lighting device, the sensor, and the MCU within the target lighting area to execute a preset lighting strategy; The first mode further includes: detecting the acceleration and direction of the user through a motion sensor, determining the user's movement path based on historical data and real-time data, and determining whether the user is about to enter a sub-area; wherein the historical data includes historical movement data and historical preference data; the historical movement data and historical preference data of different users are independent; The lighting strategy includes: based on the first mode information, controlling the MCU of the sub-area to preload the lighting parameter data preset for the sub-area; wherein the lighting parameter data includes: brightness, color temperature, scene mode and user preference; The second mode further includes: detecting user location, activity type, and scene information in real time through sensors within the sub-area; the lighting strategy includes: determining scene requirement information of the sub-area based on the second mode information, and adjusting lighting equipment in the sub-area based on the scene requirement information; The third mode also includes: The density and type of user activities are detected by sensors within the target lighting area.

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