Multi-branch LED illumination intelligent control system based on multi-condition decision

Abstract

The invention discloses a multi-branch LED illumination intelligent control system based on multi-condition decision, which relates to the technical field of LED control and comprises a control center, a condition input module, a task construction module, an illumination execution module and an area detection module. By setting the detection period, secondary detection is carried out on the illumination area, whether the illumination time is prolonged or not is determined according to the detection result, the problem that illumination can be carried out only by manual secondary triggering is solved, and meanwhile, by setting the detection period and carrying out human shape recognition on the illumination area, the illumination time can be prolonged. And unnecessary resource waste caused by continuous illumination due to accidental sound can be avoided.

Description

Technical Field

[0001] The invention relates to the technical field of LED control, in particular to a multi-branch LED lighting intelligent control system based on multi-condition decision-making. Background Art

[0002] Currently, each floor of office and residential buildings is equipped with lamps to provide lighting for residents' activities in the common areas of the floor; In existing residential lighting, the lighting is often controlled by setting a time period and then by voice control, and the lighting time is fixed. When the lighting time is reached, it needs to be manually triggered again, that is, a sound is emitted; Therefore, how to make the lighting in residential public areas more reasonable and thus improve lighting efficiency is a problem we need to solve. To this end, a multi-branch LED lighting intelligent control system based on multi-condition decision-making is now provided. Summary of the invention

[0003] The object of the present invention is to provide a multi-branch LED lighting intelligent control system based on multi-condition decision making.

[0004] The object of the present invention can be achieved by the following technical solutions: A multi-branch LED lighting intelligent control system based on multi-condition decision-making, comprising a control center, the control center being communicatively and / or electrically connected to a conditional input module, a task construction module, a lighting execution module, and an area detection module; The condition input module is used to input control condition data and control decision data; The task construction module is used to construct a corresponding lighting execution task according to the input control condition data and control decision data; The lighting execution module is used to execute corresponding lighting control on the LED according to the constructed lighting execution task; The area detection module is used to detect the lighting area of ​​the LED and obtain corresponding area detection information.

[0005] Furthermore, the process of the condition input module inputting control condition data and control decision data includes: Setting up a condition input unit and a decision input unit; Inputting control condition data through the condition input unit, wherein the control condition data includes sound and ambient brightness; Inputting control decision data through a decision input unit, wherein the control decision data includes lighting start, lighting duration, and lighting stop; The input lighting trigger conditions and lighting decision plans are uploaded to the task building module.

[0006] Furthermore, the process of the task construction module constructing the corresponding lighting execution task according to the input control condition data and control decision data includes: Generate a corresponding lighting trigger node according to the input control condition data, wherein the lighting trigger node includes a sound trigger node and an ambient brightness trigger node; Generate a corresponding lighting execution node according to the input lighting decision plan, wherein the lighting execution node includes a start node, a stop node and an information collection node; A priority relationship is set for the environment brightness trigger node and the sound trigger node, wherein the environment brightness trigger node has a higher priority than the sound trigger node; The ambient brightness trigger node and the sound trigger node are connected in parallel to obtain a lighting trigger task node.

[0007] Further, a task list is set based on the lighting task trigger node, a first task node is created in the task list, and the information collection node is assigned to the first task node; Generate an information collection task according to the information collection node, send the information collection task to the area detection module, and the area detection module obtains the area detection information of the lighting area according to the information collection task; Importing the obtained area detection information into the first task node, analyzing the area detection information imported into the first task node, judging whether it is necessary to illuminate the lighting area according to the analysis result, and if it is necessary to illuminate the lighting area, generating a second task node, assigning a start node to the second task node, and establishing a third task node at the same time; Generate a lighting startup task according to the second task node, and send the lighting startup task to the lighting execution module; Generate a periodic information collection task according to the third task node, and send the generated periodic information collection task to the area detection module; The area detection module periodically obtains the area identification information of the lighting area according to the generated periodic information collection task, analyzes the area identification information, and determines whether it is necessary to stop lighting the lighting area according to the analysis result. If necessary, a fourth task node is established, and the stop node is assigned to the fourth task node; Generate a lighting stop task according to the fourth task node, and send the lighting stop task to the lighting execution module; The generated task nodes are aggregated to complete the construction of the lighting execution task.

[0008] Furthermore, the lighting execution module performs corresponding lighting control on the LED according to the constructed lighting execution task, including: When a lighting start-up task is obtained, the LED is started to complete the lighting of the lighting area. At the same time, the lighting brightness of the LED is dynamically adjusted according to the area detection information of the area detection module; When the lighting stop task is obtained, the LED is stopped, thereby stopping the lighting of the lighting area.

[0009] Furthermore, the area detection module includes a sound acquisition unit, an environment brightness acquisition unit, an image acquisition unit and an information analysis unit; The area detection information includes sound information and ambient brightness value; Acquire the sound information of the lighting area through the sound collection unit, and acquire the ambient brightness value of the lighting area through the ambient brightness collection unit; The image acquisition unit is used to acquire image data of the illumination area; The information analysis unit is used to analyze the obtained sound information, environmental brightness value and image data.

[0010] Furthermore, the region detection module detects the lighting region of the LED, and the process of obtaining corresponding region detection information includes: The ambient brightness value HL of the lighting area is collected in real time by the set ambient brightness collection unit; Set the ambient brightness threshold H0; Comparing the obtained ambient brightness value with the ambient brightness threshold H0 in the information analysis unit to obtain a corresponding comparison result; When HL ≥ H0, no operation is performed; When HL<H0, an information collection task is generated; According to the generated information collection task, the sound information of the lighting area is obtained in real time through the set sound collection unit, where the sound information is the decibel value Fb of the lighting area; Set the decibel threshold F0; The decibel value Fb of the illumination area obtained is compared with the decibel threshold F0 in the information analysis unit to obtain a corresponding comparison result; When Fb<F0, no operation is performed; When Fb ≥ F0, it means that the lighting area needs to be illuminated, and a lighting start task is generated; When the lighting startup task is started, a periodic information collection task is generated, and the area identification information is acquired according to the generated periodic information collection task.

[0011] Furthermore, the process of obtaining the region identification information according to the generated periodic information collection task includes: Set the detection period T; At each detection period T, the image acquisition unit is used to obtain image data of the lighting area, wherein the image data is a photograph of the lighting area; The obtained image data is uploaded to the information analysis unit, and the information analysis unit performs human figure recognition on the obtained image data to obtain a corresponding human figure recognition result; When the information analysis unit recognizes that a human figure exists in the obtained image data, the detection cycle is reset. If no human figure is detected in the obtained image data, a lighting stop task is generated.

[0012] Compared with the prior art, the present invention has the following beneficial effects: 1. By setting the detection cycle, the lighting area can be tested twice, and the lighting time can be extended according to the detection results, thus solving the problem of requiring manual secondary triggering for lighting; At the same time, by setting the detection cycle and human recognition in the lighting area, continuous lighting caused by unexpected sounds can be avoided, which would cause unnecessary waste of resources. 2. By operating the sound acquisition unit, the ambient brightness acquisition unit and the image acquisition unit in stages, the sound acquisition unit, the ambient brightness acquisition unit and the image acquisition unit can be used more efficiently, the acquisition of invalid data can be reduced, and the performance loss of the hardware module can be indirectly reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0014] Figure 1 It is the principle diagram of the present invention; Figure 2 It is a schematic diagram of the region detection module of the present invention. DETAILED DESCRIPTION

[0015] like Figure 1 As shown, a multi-branch LED lighting intelligent control system based on multi-condition decision-making includes a control center, the control center is communicated and / or electrically connected to a conditional input module, a task construction module, a lighting execution module and an area detection module; The condition input module is used to input control condition data and control decision data; The task construction module is used to construct a corresponding lighting execution task according to the input control condition data and control decision data; The lighting execution module is used to execute corresponding lighting control on the LED according to the constructed lighting execution task; The area detection module is used to detect the lighting area of ​​the LED and obtain corresponding area detection information.

[0016] It should be further explained that, in the specific implementation process, the process of the condition input module inputting the control condition data and the control decision data includes: Setting up a condition input unit and a decision input unit; Inputting control condition data through the condition input unit, wherein the control condition data includes sound and ambient brightness; Inputting control decision data through a decision input unit, wherein the control decision data includes lighting start, lighting duration, and lighting stop; The input lighting trigger conditions and lighting decision plans are uploaded to the task building module.

[0017] It should be further explained that, in the specific implementation process, the process of the task construction module constructing the corresponding lighting execution task according to the input control condition data and control decision data includes: Generate a corresponding lighting trigger node according to the input control condition data, wherein the lighting trigger node includes a sound trigger node and an ambient brightness trigger node; Generate a corresponding lighting execution node according to the input lighting decision plan, wherein the lighting execution node includes a start node, a stop node and an information collection node; A priority relationship is set for the environment brightness trigger node and the sound trigger node, wherein the environment brightness trigger node has a higher priority than the sound trigger node; The environment brightness trigger node and the sound trigger node are connected in parallel to obtain a lighting trigger task node; Setting a task list based on the lighting task trigger node, creating a first task node in the task list, and assigning the information collection node to the first task node; Generate an information collection task according to the information collection node, send the information collection task to the area detection module, and the area detection module obtains the area detection information of the lighting area according to the information collection task; Importing the obtained area detection information into the first task node, analyzing the area detection information imported into the first task node, judging whether it is necessary to illuminate the lighting area according to the analysis result, and if it is necessary to illuminate the lighting area, generating a second task node, assigning a start node to the second task node, and establishing a third task node at the same time; Generate a lighting startup task according to the second task node, and send the lighting startup task to the lighting execution module; Generate a periodic information collection task according to the third task node, and send the generated periodic information collection task to the area detection module; The area detection module periodically obtains the area identification information of the lighting area according to the generated periodic information collection task, analyzes the area identification information, and determines whether it is necessary to stop lighting the lighting area according to the analysis result. If necessary, a fourth task node is established, and the stop node is assigned to the fourth task node; Generate a lighting stop task according to the fourth task node, and send the lighting stop task to the lighting execution module; Summarize the generated task nodes to complete the construction of the lighting execution task; It should be further explained that, in the specific implementation process, when the lighting execution module completes the execution of the lighting stop task, it indicates the completion of the lighting execution task, and at the same time generates a new first task node, and the above operation is looped, and so on, that is, each lighting execution task is independent of each other.

[0018] It should be further explained that, in the specific implementation process, the lighting execution module performs corresponding lighting control on the LED according to the constructed lighting execution task, including: When a lighting start-up task is obtained, the LED is started to complete the lighting of the lighting area. At the same time, the lighting brightness of the LED is dynamically adjusted according to the area detection information of the area detection module; When the lighting stop task is obtained, the LED is stopped, thereby stopping the lighting of the lighting area.

[0019] like Figure 2 As shown, the area detection module includes a sound acquisition unit, an ambient brightness acquisition unit, an image acquisition unit and an information analysis unit; The area detection information includes sound information and ambient brightness value; Acquire the sound information of the lighting area through the sound collection unit, and acquire the ambient brightness value of the lighting area through the ambient brightness collection unit; The information analysis unit is used to analyze the obtained sound information, environmental brightness value and image data.

[0020] It should be further explained that, in a specific implementation process, the region detection module detects the lighting region of the LED, and the process of obtaining the corresponding region detection information includes: The ambient brightness value of the lighting area is collected in real time by the set ambient brightness collection unit, and the ambient brightness value obtained by the ambient brightness collection unit is recorded as HL; Set the ambient brightness threshold, denoted as H0; Comparing the obtained ambient brightness value with the ambient brightness threshold H0 in the information analysis unit to obtain a corresponding comparison result; When HL ≥ H0, no operation is performed; When HL<H0, an information collection task is generated; According to the generated information collection task, the sound information of the lighting area is obtained in real time through the set sound collection unit, wherein the sound information is the decibel value of the lighting area, and the decibel value of the lighting area obtained by the sound collection unit is recorded as Fb; Set the decibel threshold, denoted as F0; The decibel value Fb of the illumination area obtained is compared with the decibel threshold F0 in the information analysis unit to obtain a corresponding comparison result; When Fb<F0, no operation is performed; When Fb ≥ F0, it means that the lighting area needs to be illuminated, and a lighting start task is generated; It should be further explained that, in the specific implementation process, the sound collection unit and the environment brightness collection unit do not work at the same time, and the environment brightness collection unit has a higher priority than the sound collection unit, that is, when the environment brightness value acquired by the lighting area environment brightness collection unit is lower than the set environment brightness threshold, the sound collection unit will collect the sound data of the lighting area, and at the same time, the environment brightness collection unit will temporarily stop working; When the sound information of the lighting area obtained by the sound collection unit is not lower than the set decibel threshold, a lighting start task will be generated, the lighting area will be illuminated according to the lighting start task, and the sound collection unit will temporarily stop working; When the lighting startup task is started, a periodic information collection task is generated, and the area identification information is obtained according to the generated periodic information collection task, that is, Set the detection period T; At each detection period T, the image acquisition unit is used to obtain image data of the lighting area, wherein the image data is a photograph of the lighting area; The obtained image data is uploaded to the information analysis unit, and the information analysis unit performs human figure recognition on the obtained image data to obtain a corresponding human figure recognition result; When the information analysis unit recognizes that a human figure exists in the acquired image data, the detection cycle is reset; if no human figure is detected in the acquired image data, a lighting stop task is generated, and the image acquisition unit temporarily stops working; By making the sound collection unit, the environment brightness collection unit and the image collection unit work in stages, the sound collection unit, the environment brightness collection unit and the image collection unit can be used more efficiently, the acquisition of invalid data can be reduced, and the performance loss of the hardware module can be indirectly reduced; It should be further explained that, in the specific implementation process, when the detection cycle is reset, the illumination area will continue to be illuminated, and the image data of the illumination area will be acquired again in the next detection cycle, and recognition will be performed again, and so on; By setting detection cycles and human figure recognition in the lighting area, continuous lighting caused by unexpected sounds can be avoided, which would result in unnecessary waste of resources.

[0021] The above is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any modification or equivalent replacement of the above embodiments made according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still falls within the scope of the technical solution of the present invention.

Claims

1. A multi-branch LED lighting intelligent control system based on multi-condition decision-making, including a control center, characterized in that: The control center is in communication and / or electrically connected with the conditional input module, the task construction module, the lighting execution module and the area detection module; The condition input module is used to input control condition data and control decision data; The task construction module is used to construct a corresponding lighting execution task according to the input control condition data and control decision data; The lighting execution module is used to execute corresponding lighting control on the LED according to the constructed lighting execution task; The area detection module is used to detect the lighting area of ​​the LED and obtain corresponding area detection information.

2. According to claim 1, a multi-branch LED lighting intelligent control system based on multi-condition decision-making is characterized in that: The process of inputting control condition data and control decision data by the condition input module includes: Setting up a condition input unit and a decision input unit; Inputting control condition data through the condition input unit, wherein the control condition data includes sound and ambient brightness; Inputting control decision data through a decision input unit, wherein the control decision data includes lighting start, lighting duration, and lighting stop; The input lighting trigger conditions and lighting decision plans are uploaded to the task building module.

3. The multi-branch LED lighting intelligent control system based on multi-condition decision-making according to claim 2 is characterized in that: The process of constructing the corresponding lighting execution task according to the input control condition data and control decision data by the task construction module includes: Generate a corresponding lighting trigger node according to the input control condition data, wherein the lighting trigger node includes a sound trigger node and an ambient brightness trigger node; Generate a corresponding lighting execution node according to the input lighting decision plan, wherein the lighting execution node includes a start node, a stop node and an information collection node; A priority relationship is set for the environment brightness trigger node and the sound trigger node, wherein the environment brightness trigger node has a higher priority than the sound trigger node; The ambient brightness trigger node and the sound trigger node are connected in parallel to obtain a lighting trigger task node.

4. The multi-branch LED lighting intelligent control system based on multi-condition decision-making according to claim 3 is characterized in that: Setting a task list based on the lighting task trigger node, creating a first task node in the task list, and assigning the information collection node to the first task node; Generate an information collection task according to the information collection node, send the information collection task to the area detection module, and the area detection module obtains the area detection information of the lighting area according to the information collection task; Importing the obtained area detection information into the first task node, analyzing the area detection information imported into the first task node, judging whether it is necessary to illuminate the lighting area according to the analysis result, and if it is necessary to illuminate the lighting area, generating a second task node, assigning a start node to the second task node, and establishing a third task node at the same time; Generate a lighting startup task according to the second task node, and send the lighting startup task to the lighting execution module; Generate a periodic information collection task according to the third task node, and send the generated periodic information collection task to the area detection module; The area detection module periodically obtains the area identification information of the lighting area according to the generated periodic information collection task, analyzes the area identification information, and determines whether it is necessary to stop lighting the lighting area according to the analysis result. If necessary, a fourth task node is established, and the stop node is assigned to the fourth task node; Generate a lighting stop task according to the fourth task node, and send the lighting stop task to the lighting execution module; The generated task nodes are aggregated to complete the construction of the lighting execution task.

5. The multi-branch LED lighting intelligent control system based on multi-condition decision-making according to claim 4 is characterized in that: The process in which the lighting execution module performs corresponding lighting control on the LED according to the constructed lighting execution task includes: When a lighting start-up task is obtained, the LED is started to complete the lighting of the lighting area. At the same time, the lighting brightness of the LED is dynamically adjusted according to the area detection information of the area detection module; When the lighting stop task is obtained, the LED is stopped, thereby stopping the lighting of the lighting area.

6. The multi-branch LED lighting intelligent control system based on multi-condition decision-making according to claim 5 is characterized in that: The area detection module includes a sound acquisition unit, an environment brightness acquisition unit, an image acquisition unit and an information analysis unit; The area detection information includes sound information and ambient brightness value; Acquire the sound information of the lighting area through the sound collection unit, and acquire the ambient brightness value of the lighting area through the ambient brightness collection unit; The image acquisition unit is used to acquire image data of the illumination area; The information analysis unit is used to analyze the obtained sound information, environmental brightness value and image data.

7. The multi-branch LED lighting intelligent control system based on multi-condition decision-making according to claim 6 is characterized in that: The region detection module detects the lighting region of the LED, and the process of obtaining corresponding region detection information includes: The ambient brightness value HL of the lighting area is collected in real time by the set ambient brightness collection unit; Set the ambient brightness threshold H0; Comparing the obtained ambient brightness value with the ambient brightness threshold H0 in the information analysis unit to obtain a corresponding comparison result; When HL ≥ H0, no operation is performed; When HL<H0, an information collection task is generated; According to the generated information collection task, the sound information of the lighting area is obtained in real time through the set sound collection unit, where the sound information is the decibel value Fb of the lighting area; Set the decibel threshold F0; The decibel value Fb of the illumination area obtained is compared with the decibel threshold F0 in the information analysis unit to obtain a corresponding comparison result; When Fb<F0, no operation is performed; When Fb ≥ F0, it means that the lighting area needs to be illuminated, and a lighting start task is generated; When the lighting startup task is started, a periodic information collection task is generated, and the area identification information is acquired according to the generated periodic information collection task.

8. The multi-branch LED lighting intelligent control system based on multi-condition decision-making according to claim 7 is characterized in that: The process of obtaining the area identification information according to the generated periodic information collection task includes: Set the detection period T; At each detection period T, the image acquisition unit is used to obtain image data of the lighting area, wherein the image data is a photograph of the lighting area; The obtained image data is uploaded to the information analysis unit, and the information analysis unit performs human figure recognition on the obtained image data to obtain a corresponding human figure recognition result; When the information analysis unit recognizes that a human figure exists in the obtained image data, the detection cycle is reset. If no human figure is detected in the obtained image data, a lighting stop task is generated.

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