Dimming system for infrared laser lights based on big data analysis

Abstract

The present invention discloses a dimming system for infrared laser lamps based on big data, comprising a power supply module, a camera module, an ambient light module, a controller, a data acquisition and analysis module, and a dimming module. The present invention eliminates the effects of strong light and device failures on the detection of ambient light data collected by uniformly arranging ambient light sensors in a circular pattern indoors and performing discrete judgments on the ambient light sensors. The system also records indoor image data, calculates the contrast corresponding to the grayscale difference between adjacent pixels in the image from the perspective of the image, and calculates the average value of the contrast to eliminate the effects of sudden strong light on the image. The dimming module dims the indoor ambient light using a red laser, and determines whether dimming is needed for a short period of time using a preset light intensity threshold, thereby extending the device lifespan and reducing system power consumption.

Description

Technical Field

[0001] The present invention relates to the field of indoor dimming, and in particular to a dimming system for infrared lasers based on big data analysis. Background Art

[0002] In many indoor environments, cameras need to work around the clock. A good indoor lighting environment makes it easier to capture clear images, especially when low illumination is required to ensure the visibility of surveillance images. Currently, the control of indoor light is relatively simple. For example, the fill light can only be simply turned on and off. Currently, common fill lights (infrared lights or white lights) all have fixed brightness. On the one hand, this method affects the quality of surveillance images, and on the other hand, the power consumption is relatively high, which cannot meet the light control requirements under different brightness conditions. Sudden high brightness light will also affect the control of indoor light. To address this situation, the present invention has developed a dimming system for infrared laser lights based on big data analysis that can automatically adjust the indoor light brightness to an appropriate brightness, extend the service life of infrared laser lights, and reduce power consumption. Summary of the Invention

[0003] The purpose of the present invention is to provide a dimming system for infrared laser lamps based on big data analysis.

[0004] The purpose of the present invention can be achieved through the following technical solutions:

[0005] The dimming system for infrared laser lights based on big data analysis includes:

[0006] A data acquisition and analysis module is used to analyze the indoor ambient light intensity and the image data in the room to obtain the indoor dimming value G1;

[0007] The dimming module includes an infrared laser lamp. The dimming module determines whether the indoor ambient light intensity needs to be dimmed and generates determination data. The dimming module adjusts the indoor light brightness according to the determination data.

[0008] Furthermore, the ambient light module includes an ambient light sensor. Four ambient light sensors are evenly arranged in the middle of the room and distributed in a ring shape. The ambient light module is used to collect indoor ambient light and generate average ambient light intensity data.

[0009] Furthermore, the data acquisition module analyzes and obtains the indoor dimming value G1. The specific steps are as follows:

[0010] Step 1: Select a classroom to be sampled;

[0011] Step 2: Divide the camera shooting time into 48 standard shooting points. The initial standard shooting point is 00:00; and so on to obtain all standard shooting points Tn, where n = 1, 2,... n;

[0012] Step 3: Sequentially obtain the image data of the camera at each standard shooting point and mark it as Mn;

[0013] Step 4: Sequentially obtain the ambient light intensity detected by the indoor ambient light sensor at each standard shooting point and mark it as Gn;

[0014] Step 5: Obtain the total pixel value of M1 at the standard shooting point T1 and mark it as X1;

[0015] Step 6: Divide the coordinates of M1 at the standard shooting point T1. Take the lower left corner of M1 as the coordinate origin, and mark the coordinate positions of each pixel on M1 according to the coordinates and record them as (i, j);

[0016] Step 7: Use the formula to calculate the contrast C1 of the gray difference f between adjacent pixels, where f1(i, j) is the gray difference between adjacent pixels, and gf1(i, j) is the pixel distribution probability of the gray difference f between adjacent pixels;

[0017] Step 8: Sequentially obtain the contrast Cy corresponding to the gray difference between each adjacent pixel of the image M1;

[0018] Step 9: Use the formula to calculate and obtain the standard deviation of the contrast Cy corresponding to the gray difference between each adjacent pixel of the image M1, is the average value of the contrast of the gray difference between each adjacent pixel of the image M1;

[0019] Step 10: Sequentially obtain the standard deviation Qn of the contrast corresponding to the gray difference between each adjacent pixel of the image Mn at 48 standard shooting points according to Steps 5 to 9;

[0020] Step 11: Use the formula to calculate and obtain the standard deviation R of the contrast corresponding to the gray difference between each adjacent pixel of Mn at each standard shooting point, is the average value of the contrast standard deviation of the image Mn at 48 standard shooting points. Compare the calculated standard deviation R with R1. If R > R1, it is considered that the contrast of the gray value between this group of adjacent pixels is affected by strong light factors, then according to the values of Qs are sequentially deleted in descending order and the corresponding standard deviation R of the remaining Qs values is calculated until R < R1, where 1 < s < n, and the R1 is the contrast threshold of the image Mn;

[0021] Step Twelve: Calculate and obtain the brightness factor P1 of the image using the formula P1 = [x1 - 127.5*(1 - B)]*(Cy / y) + 127.5*(1 + B).

[0022] Step Thirteen: Obtain the ambient light intensity of the images of 48 standard camera points participating in the remaining corresponding contrast standard deviation indoor ambient light sensor detection and mark it as Gs.

[0023] Step Fourteen: Use the formula to calculate and obtain the dimming value G1 of the classroom to be sampled.

[0024] Further, the dimming module generates the following specific determination data:

[0025] V1: The dimming module receives the current light intensity value U transmitted by the ambient light module.

[0026] V2: If W = G1 - U > 0, it is determined that the light intensity in the room is insufficient. Here, W is the dimming degree. At this time, the controller generates a dimming instruction and transmits it to the dimming module. The dimming module is used to adjust the light intensity in the room. After receiving the dimming instruction and the dimming degree W transmitted by the controller, the infrared laser lamp adjusts the light intensity in the room according to the dimming degree W.

[0027] V3: If W = G1 - U < 0, at this time the controller determines that the light intensity in the room is sufficient.

[0028] Further, the dimming module determines that the indoor light intensity is sufficient and generates an instruction according to a certain rule. The specific rule is as follows:

[0029] If W < W1, at this time the controller does not generate a pending instruction.

[0030] If W > W1, at this time the controller generates a pending instruction and transmits it to the ambient light module. After receiving the pending instruction transmitted by the controller, the ambient light module generates a timing instruction and re - collects the ambient light intensity half an hour later. Here, W1 is the preset light intensity pending threshold.

[0031] Advantages of the present invention:

[0032] (1) In the present invention, ambient light sensors are evenly arranged in a ring shape indoors, and through discrete judgment of the collected ambient light sensors, the detection influence of strong light and device failures on the ambient light acquisition data is excluded.

[0033] (2) In the present invention, by recording the image data in the room, calculating the contrast corresponding to the gray - scale difference between adjacent pixels in the image from the perspective of the image, and calculating its average value to exclude the influence of suddenly appearing strong light on the image.

[0034] (3) The present invention uses a red laser to dim the ambient light in the room through a dimming module, and determines whether dimming is needed for a short time through a preset light intensity threshold, thereby extending the service life of the device and reducing the power consumption of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The present invention will be further described below with reference to the accompanying drawings.

[0036] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0038] like Figure 1 As shown, the dimming system for infrared laser lights based on big data analysis includes: a power module, a camera module, an ambient light module, a controller, a data acquisition and analysis module, and a dimming module.

[0039] The power supply module includes a first power supply unit and a second power supply unit. The first power supply unit is used to supply the power required for the lighting of the entire classroom, and intermittent power supply is adopted according to the lighting needs. The second power supply unit is used to continuously supply the power required for the entire system.

[0040] The camera module includes a monitoring camera and an image storage library. The camera module is used to collect indoor environmental data and display images thereof. The specific steps are as follows:

[0041] S1: Install the surveillance camera in the top corner of the room near the front door to capture a comprehensive view of the indoor environment.

[0042] S2: Set the surveillance camera's shooting cycle to once every 30 minutes;

[0043] S3: The surveillance camera takes pictures of the indoor environment and records the stone expulsion time;

[0044] The camera module generates image data based on the data captured by the surveillance camera of the environment. The Suosheng camera module transmits the image data and the time when the image data was captured to the image repository. After receiving the image data and the time when the image data was captured, the image repository stores them, and uses the time when the image data was captured as the name for storing the image data for easy sampling and querying, and sets the image expiration time to 30 days, avoiding the situation that the system becomes inconvenient to use due to data redundancy caused by long-term use.

[0045] The ambient light module includes an ambient light sensor and an ambient light recording library. Four ambient light sensors are evenly arranged at the middle position of the room, and the four ambient light sensors are distributed in a ring. The ambient light module is used to collect the indoor ambient light. The specific steps are as follows:

[0046] SS1: Divide the ambient light collection points. Divide the ambient light collection points into 48 standard collection points. The initial standard collection point is 00:00, and all the standard collection points On are obtained by analogy, where n = 1, 2,... 48;

[0047] SS2: Taking the standard collection point 00:00 as an example, obtain the ambient light intensities detected by the four ambient light sensors and mark them as a1, a2, a3, and a4 respectively;

[0048] SS3: Judge the detected ambient light intensity. The specific steps are as follows:

[0049] SSS1: Use the formula a = (a1 + a2 + a3 + a4) / 4 to calculate and obtain the average value a of the ambient light intensity;

[0050] SSS2: Use the formula E = |a1 - a| to calculate and obtain the deviation value E of the ambient light intensity. If E < E1, the ambient light data collected by this ambient light sensor is reliable; if E > E1, the ambient light data collected by this ambient light sensor is unreliable, and this ambient light data is excluded;

[0051] SSS3: Perform exclusion judgment on the ambient light intensities detected by the remaining ambient light sensors in sequence according to step SSS2;

[0052] SS4: Calculate and obtain the average ambient light intensity A1 at the current standard collection point after excluding unreliable data;

[0053] SS4: According to steps SS2 to SS3, obtain the average ambient light intensities An of 48 standard collection points in sequence;

[0054] The ambient light module transmits the average ambient light intensity An of the 48 standard collection points and the time of collecting the ambient light to the ambient light recording library. The ambient light recording library receives the average ambient light intensity transmitted by the ambient light module and stores it in the ambient light recording library, and sets an expiration time of 30 days.

[0055] The data acquisition and analysis module is used to collect required data and analyze it. The data acquisition and analysis module generates a data acquisition instruction and transmits it to the camera module and the ambient light module respectively. After receiving the data acquisition instruction transmitted by the data acquisition and analysis module, the camera module collects the indoor image data and transmits it to the data acquisition and analysis module. After receiving the data acquisition instruction transmitted by the camera module, the ambient light module collects the indoor ambient light intensity and transmits it to the data acquisition and analysis module. After receiving the image data transmitted by the camera module and the ambient light data transmitted by the ambient light module, the data acquisition and analysis module analyzes the data.

[0056] The specific steps are as follows:

[0057] Step 1: Select a classroom to be sampled;

[0058] Step 2: Divide the camera points into 48 standard camera points, with the initial standard camera point being 00:00; and so on to obtain all standard camera points Tn, where n=1, 2, ...n;

[0059] Step 3: Obtain the image data of the camera at each standard camera point in sequence and mark it as Mn;

[0060] Step 4: Obtain the ambient light intensity detected by the indoor ambient light sensor at each standard camera point in turn and mark it as Gn;

[0061] Step 5: Obtain the total pixel value of M1 at the standard camera point T1 and mark it as X1;

[0062] Step 6: Divide the coordinates of M1 under the standard camera point T1, taking the lower left corner of M1 as the coordinate origin, and mark the coordinate position of each pixel on M1 as (i, j);

[0063] Step 7: Use the formula Calculate the contrast C1 when the grayscale difference between adjacent pixels is f, where f1(i, j) is the grayscale difference between adjacent pixels, and gf1(i, j) is the pixel distribution probability when the grayscale difference between adjacent pixels is f;

[0064] Step 8: sequentially obtain the contrast Cy corresponding to the grayscale difference between each adjacent pixel of the image M1;

[0065] Step 9: Exploit Calculate the standard deviation of the contrast Cy corresponding to the gray - level difference between adjacent pixels of image M1 through formula calculation. is the average value of the contrast corresponding to the gray - level difference between adjacent pixels of image M1.

[0066] Step Ten: Sequentially obtain the standard deviation Qn of the contrast corresponding to the gray - level difference between adjacent pixels of each image Mn at 48 standard camera points according to Steps 5 to 9.

[0067] Step Eleven: Use the formula to calculate and obtain the standard deviation R of the contrast corresponding to the gray - level difference between adjacent pixels of Mn at each standard camera point. is the average value of the standard deviation of the contrast of image Mn at 48 standard camera points. Compare the calculated standard deviation R with R1. If R > R1, it is considered that the contrast of the gray - level values between this group of adjacent pixels is affected by strong light factors. Then, delete the corresponding Qs values in descending order according to the value and calculate the standard deviation R corresponding to the remaining Qs values until R < R1, where 1 < s < n, and the R1 is the contrast threshold of image Mn.

[0068] Step Twelve: Use the formula P1 = [x1 - 127.5*(1 - B)]*(Cy / y)+127.5*(1 + B) to calculate and obtain the brightness factor P1 of the image.

[0069] Step Thirteen: Obtain the ambient light intensity of the images at 48 standard camera points participating in the detection of the remaining corresponding contrast standard deviation by the indoor ambient light sensor and mark it as Gs.

[0070] Step Fourteen: Use the formula to calculate and obtain the dimming value G1 of the classroom to be sampled.

[0071] The controller generates the current light intensity instruction and transmits it to the ambient light module. After receiving the current light intensity instruction transmitted by the controller, the ambient light module detects the current indoor light intensity to generate the current light intensity value U and transmits it to the controller. After receiving the current light intensity value U transmitted by the ambient light module, the controller makes a judgment on it. The specific steps are as follows:

[0072] V1: If W = G1 - U > 0, the controller determines that the current indoor light intensity is insufficient. Here, W is the dimming degree. At this time, the controller generates a dimming instruction and transmits it to the dimming module. The dimming module is used to adjust the indoor light intensity. The dimming module includes an infrared laser lamp. After receiving the dimming instruction and the dimming degree W transmitted by the controller, the infrared laser lamp adjusts the indoor light intensity according to the dimming degree W.

[0073] V2: If W = G1 - U < 0, the controller determines that the current indoor light intensity is sufficient. At this time, the controller generates an instruction according to certain rules. The specific rules are as follows:

[0074] If W < W1, the controller does not generate a pending instruction;

[0075] If W > W1, the controller generates a pending instruction and transmits it to the ambient light module. After receiving the pending instruction transmitted by the controller, the ambient light module generates a timing instruction and re-collects the ambient light intensity half an hour later. W1 is a preset threshold for pending light intensity.

[0076] In the description of the specification, the descriptions referring to terms such as "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0077] The above content is only an example and illustration of the present invention. Those skilled in the art of this technology can make various modifications or supplements to the described specific embodiments or use similar methods to replace them. As long as they do not deviate from the invention or exceed the scope defined by the claims of this patent, they should fall within the protection scope of the present invention.

[0078] The above has described a detailed description of an embodiment of the present invention, but the content described is only the preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the application of the present invention should still fall within the scope covered by the patent of the present invention.

Claims

1. The dimming system for infrared laser lamp based on big data analysis is characterized by: Including: A data acquisition and analysis module, which is used to analyze the ambient light intensity in the room and the image data in the shed to obtain the dimming value G1 of the room; The dimming module includes an infrared laser lamp. The dimming module determines whether dimming is required for the ambient light intensity in the room and generates determination data. The dimming module adjusts the indoor light brightness according to the determination data; The data acquisition module analyzes and obtains the dimming value G1 of the room. The specific steps are as follows: Step 1: Select a classroom as the classroom to be sampled; Step 2: Divide the camera shooting points. Divide the shooting time into 48 standard shooting points. The initial standard shooting point is 00:00; and so on to obtain all the standard shooting points Tn, where n = 1, 2,... n; Step 3: Sequentially obtain the image data of the camera at each standard shooting point and mark it as Mn; Step 4: Sequentially obtain the ambient light intensity detected by the indoor ambient light sensor at each standard shooting point and mark it as Gn; Step 5: Obtain the total pixel value of M1 at the standard shooting point T1 and mark it as X1; Step 6: Divide the coordinates of M1 at the standard shooting point T1. Take the lower left corner of M1 as the coordinate origin, and mark the coordinate positions of each pixel on M1 according to the coordinates and record them as (i, j); Step 7: Use the formula Calculate the contrast C1 when the grayscale difference between adjacent pixels is f, where f1(i, j) is the grayscale difference between adjacent pixels, and gf1(i, j) is the pixel distribution probability when the grayscale difference between adjacent pixels is f; Step 8: Sequentially obtain the contrast Cy corresponding to the gray difference between adjacent pixels of the image M1; Step 9: Use the formula Calculate the standard deviation of the contrast Cy corresponding to the grayscale difference between adjacent pixels in the acquired image M1. is the average value of the contrast corresponding to the grayscale difference between adjacent pixels in image M1; Step 10: Sequentially obtain the standard deviation Qn of the contrast corresponding to the gray difference between adjacent pixels of the images Mn at 48 standard shooting points according to steps 5 to 9; Step Eleven: Using the formula calculate the standard deviation R of the contrast corresponding to the gray - level differences between adjacent pixels of Mn under each standard camera point, R1 is the average value of the contrast standard deviations of the images Mn of 48 standard camera points. Compare the calculated standard deviation R with R1. If R > R1, it is considered that the contrast of the gray - level values between this group of adjacent pixels is affected by strong light factors, and then delete the corresponding Qs values in descending order according to the values of and calculate the standard deviation R corresponding to the remaining Qs values until R < R1, where 1 < s < n, and the R1 is the contrast threshold of the image Mn; Step 12: Use the formula P1 = [x1 - 127.5 * (1 - B)] * (Cy / y) + 127.5 * (1 + B) to calculate and obtain the brightness factor P1 of the image; Step 13: Obtain the ambient light intensity detected by the indoor ambient light sensor corresponding to the remaining corresponding contrast standard deviation of the images at 48 standard shooting points and mark it as Gs; Step 14: Using the formula Calculate and obtain the dimming value G1 of the classroom to be sampled; The ambient light module includes ambient light sensors. 4 ambient light sensors are evenly arranged at the middle position of the room. The 4 ambient light sensors are distributed in a ring shape, and the ambient light module is used to collect the indoor ambient light and generate average ambient light intensity data; The dimming module generates the following specific determination data: V1: The dimming module receives the current light intensity value U transmitted by the ambient light module; V2: If W = G1 - U > 0, it is determined that the current indoor light intensity is insufficient. W is the dimming degree. At this time, the controller generates a dimming instruction and transmits it to the dimming module. The dimming module is used to adjust the indoor light intensity. After the dimming module receives the dimming instruction and the dimming degree W transmitted by the controller, the infrared laser lamp adjusts the indoor light intensity according to the dimming degree W; V3: If W = G1 - U < 0, at this time the controller determines that the current indoor light intensity is sufficient; The dimming module determines that the indoor light intensity is sufficient and generates an instruction according to a certain rule. The specific rule is as follows: If W < W1, at this time the controller does not generate a pending instruction; If W>W1, the controller generates a pending instruction and transmits it to the ambient light module. The ambient light module generates a timing instruction after receiving the pending instruction transmitted by the controller and collects the ambient light intensity again after half an hour. W1 is the preset light intensity pending threshold.

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