A method for intelligently adjusting light power and color change of light luring fishing boat LED fish gathering lamp according to fish finder data

Abstract

The application discloses a method for intelligently adjusting light power and color change of LED fish gathering lamps of a light fishing boat according to fish finder data, and comprises the following steps: designing a side-scan fish finder data division scheme, dividing data of the side-scan fish finder into six areas A-F, which respectively correspond to six different areas under the light fishing boat; collecting fish finder data of the light fishing boat; performing background noise erasing, fish quantity analysis and other processing on the collected data, and dividing fish conditions of each area into four categories of no fish, few fish, medium fish and many fish; converting a light adjustment scheme of the light fishing boat into light adjustment instructions, and sending the light adjustment instructions to a fish gathering lamp ballast end through a local area network; and the fish gathering lamp ballast end adjusts power to realize brightness of two color lights of the LED fish gathering lamp, and realizes a fish gathering function. The application can significantly improve the precision of light control of the light fishing boat, reduce the artificial workload in the fishing link, and greatly improve fishing yield and fishing efficiency.

Description

Technical Field

[0001] This invention relates to the application of intelligent LED lighting and acoustic data processing technology in fisheries, and in particular to a method for intelligently adjusting the light power and color changes of LED fish-attracting lights on light-attracting fishing boats based on data from a fish finder. Background Technology

[0002] Phototaxis in animals is related to vision, and its manifestation varies among different species and at different developmental stages of the same species. Many fish exhibit phototaxis, and fishing vessels using light traps or light-attracting techniques operate at night, taking advantage of this phototaxis. Due to the unique environment, the characteristics of the light field created by fish-attracting lights in the water have been extensively studied. The light emitted by fish-attracting lights is absorbed and scattered by seawater, forming a light field of varying intensity, which is used by fishing vessels catching various phototactic fish. Research shows that light fishing in the South China Sea has developed rapidly, with the number of fishing vessels during the spring fishing season increasing from around 400 in 2012 to over 2,000 in 2020. Light fishing has become an important part of the current fisheries industry.

[0003] However, current light fishing still faces many industry challenges. For example, when fishing for mid-to-upper-level fish such as squid, saury, and mackerel, experienced captains often need to assess the fishing conditions based on the sea surface and then adjust the color and brightness of the lights accordingly. This approach demands a high level of experience from the captain, resulting in significant differences in catches among different captains. Furthermore, the light adjustment process for light-fishing vessels typically requires zone-by-zone adjustments. Captains must assess different areas separately, which is time-consuming. For some mid-to-lower-level fish, where surface conditions are not readily apparent, fish finders and other equipment are needed to determine the fishing conditions in that area. This approach also suffers from inconsistent captain experience and time-consuming processes. Therefore, light fishing urgently needs an intelligent light adjustment method. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method for intelligently adjusting the power and color change of LED fish-attracting lights on fishing boats based on fish finder data. This method can determine the fishing conditions in a corresponding area through fish finder data, intelligently formulate brightness strategies for red and white light, and complete the automatic adjustment of brightness.

[0005] This application is achieved through the following technical solution:

[0006] A method for intelligently adjusting the power and color change of LED fish-attracting lights on a light-attracting fishing boat based on data from a fish finder includes the following steps:

[0007] (1) Design a regional division scheme for the side-scan fish finder data of the fishing boat with light. Divide the side-scan fish finder data of the fishing boat with light into six fields AF, corresponding to six different areas under the fishing boat with light. Combine intelligent LED lights, routers, host and other equipment to form an intelligent lighting adjustment system for the fishing boat with light.

[0008] (2) Collect data from the fish finder on the fishing boat and determine the target intensity range of the fish species to be caught based on empirical formulas;

[0009] (3) Based on the echo intensity range determined in step (2), the background noise of the data in the fish finder is removed; and the fish quantity in the area is calculated and divided into four categories of fishing conditions: no fish, few fish, medium fish, and many fish.

[0010] (4) Based on the fishing conditions calculated in step (3), design an intelligent lighting adjustment scheme for fishing boats in each area using the scheduling system.

[0011] (5) Convert the lighting adjustment scheme of the fishing boat into a lighting adjustment command, and convert the command into a data frame and send it to the fish-attracting lamp ballast via the local area network;

[0012] (6) The ballast controls the white and red light current of the intelligent LED lights on the fishing boat to achieve the effect of brightness control.

[0013] As a preferred embodiment, the six-area division scheme of the side-scan fish finder in step (1) follows the following principles: each side of the fishing boat contains three areas. The sponge area corresponding to the fish finder data is determined according to the side-scan angle. Areas A, B, and C respectively represent the three areas from front to back on the left side of the fishing boat with lights. Areas D, E, and F are located on the right side of the fishing boat with lights and correspond to areas A, B, and C respectively.

[0014] As a preferred embodiment, the empirical formula in step (2) varies according to the different dynamic changes of fish species. Taking a squid fishing boat as an example, the empirical formula for the target intensity of a squid fishing boat is generally related to its body length. The empirical formula for the target intensity at a frequency of 70kHz in the fish finder of a squid fishing boat is as follows:

[0015] TS = 20 log10(DML)-67.4 (1).

[0016] In a preferred embodiment, DML represents mantle length. This empirical formula is obtained by referring to the experience of captains and other relevant literature. According to this empirical formula, the target intensity range of squid at a frequency of 70kHz is determined to be between -30dB and -40dB.

[0017] In a preferred embodiment, the data processing method in step (3) includes the following sub-steps:

[0018] (31) Adjust the echo intensity range to remove background noise;

[0019] (32) After removing background noise, the number of target fish species is identified from the visualization of the fish finder data using the OpenCV findContours() method;

[0020] (33) Determine the fishing condition level based on the number of target fish species, and divide the fishing condition into four levels: no fish, few fish, medium fish, and many fish.

[0021] In a preferred embodiment, the intelligent lighting adjustment scheme in step (4) is implemented in six areas, with each area containing four brightness intensities ranging from 0 to 3, where 0-3 represent light intensity from weak to strong. The formulas for the changes in white light and red light are as follows:

[0022]

[0023]

[0024] In the formulas (2) and (3), s represents the fishing conditions judged by the system, and the function values ​​0-3 represent the four levels of light intensity.

[0025] In a preferred embodiment, the intelligent lighting adjustment scheme in step (4) includes the following steps:

[0026] (41) When the fish finder detects that there are no fish on the sea surface, adjust the white light intensity to 3 and turn off the red light (adjust the white light intensity to 0);

[0027] (42) When the fish finder detects that the fishing conditions on the sea surface are "few fish", adjust the white light intensity to 2 and the red light intensity to 1;

[0028] (43) When the fish finder detects that the fishing conditions on the sea surface are "fish in the water", adjust the white light intensity to 2 and the red light intensity to 3.

[0029] (44) When the fish finder detects that the fishing conditions on the sea surface are "many fish", adjust the white light intensity to 1 and the red light intensity to 2.

[0030] In a preferred embodiment, step (5) includes the following sub-steps:

[0031] (51) Connect the control host and the smart lamp to the same local area network, configure the IP addresses of the control host (command sending end) and the smart lamp (command receiving end) to ensure that the two IP addresses can communicate normally;

[0032] (52) The transmitted data frames are constructed according to the Ethernet data frame standard, and the real-time performance and reliability of data transmission are guaranteed by the signal transmission mechanism in the TCP / IP protocol communication protocol.

[0033] (53) The constructed data packet satisfies the IP data packet format;

[0034] (54) The first two bytes of the data field are valid data, the first byte is the control command for white light, and the second byte is the control command for red light;

[0035] (55) The first four bits and the last four bits of each valid byte are completely consistent, which is used to further verify the accuracy of the data;

[0036] (56) In each valid four bits, the high 1 bit represents the light indicator, 0 represents white light, 1 represents red light, the middle 2 bits represent the intensity code 0-3, and the low 1 bit is the XOR check value of the high 3 bits.

[0037] (57) The light adjustment instruction occupies only one byte of data bits. The high four bits and low four bits of the byte represent the adjustment intensity of two colors of light respectively. That is, each brightness adjustment unit includes 4 bits. The high bit is the light identifier. 0 and 1 of this bit represent white light and red light respectively. The logical values ​​of the middle two bits represent the brightness level of the corresponding color light. The low bit is the check bit, which should be the XOR check value of the first three bits.

[0038] In a preferred embodiment, in step (51), the control host is configured as the instruction sending end and the smart lamp end is configured as the instruction receiving end.

[0039] In a preferred embodiment, the adjustment of light color and brightness in step (6) is carried out separately for each area. That is, the fishing conditions on the sea surface are judged for each of the six areas divided in step (1), and light adjustment instructions are sent to the corresponding lights.

[0040] The underlying principle of this invention is as follows: First, a regional division scheme is designed for the fish finder on the fishing boat, dividing the data from the fish finder into six regions, corresponding to the sea surface area where the fishing boat is located. Second, the fish finder data is collected, and noise in the raw data is removed using empirical formulas and intelligent algorithms to determine the echo intensity range of the target fish species. Then, the number of target fish species is calculated based on the visualized display of the acoustic data, and the number is divided into four fishing conditions: no fish, few fish, medium fish, and many fish. A fishing boat lighting adjustment scheme is designed based on the fishing conditions. Finally, the lighting adjustment scheme is converted into lighting adjustment commands, which are sent to the intelligent lighting unit via a local area network using the IP protocol. The intelligent lighting unit's ballast adjusts the current to achieve the brightness of the two colors of LED fish-attracting lights, thereby realizing the fish-attracting function.

[0041] Beneficial Effects: Due to the adoption of the above-mentioned technical solution, this invention has the following advantages and positive effects compared with the prior art: This invention uses fish finder data as the main factor in adjusting the lighting of light-attracting fishing boats, which has significant advantages such as strong objectivity and low error rate compared with traditional manual judgment. Compared with video data solutions, it can detect the density of fish species at deeper depths. The method proposed in this invention for intelligently adjusting the power and color changes of LED fish-attracting lights on light-attracting fishing boats based on fish finder data significantly improves the fishing efficiency of light-attracting fishing boats, saving a lot of labor costs and bringing higher yields to the light-attracting fishing boat industry. Attached Figure Description

[0042] Figure 1 This is a flowchart illustrating the present invention;

[0043] Figure 2 This is a schematic diagram of the squid fishing boat area division method corresponding to the fish finder of the present invention;

[0044] Figure 3 This is a schematic diagram of the hardware system structure of the present invention;

[0045] Figure 4 This is a schematic diagram of the data collection location in an example of the present invention;

[0046] Figure 5 This is a schematic diagram of acoustic data visualization in the example of this invention;

[0047] Figure 6 This is a visual illustration of noise removal in an example of the present invention;

[0048] Figure 7 This is a schematic diagram of the data packet structure of the present invention;

[0049] Figure 8 This is a histogram showing the length distribution of 100 squid carcasses in an embodiment of the present invention;

[0050] Figure 9 This is a schematic diagram illustrating the relationship between the length of the fish carcass and the target acoustic intensity in an embodiment of the present invention. Detailed Implementation

[0051] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings: These embodiments are implemented based on the technical solution of the present invention, and provide detailed implementation methods and specific operation processes, but the protection scope of the present invention is not limited to the following embodiments.

[0052] like Figure 1 As shown, a method for intelligently adjusting the power and color change of LED fish-attracting lights on a light-attracting fishing boat based on data from a fish finder specifically includes the following steps:

[0053] (1) Design a regional division scheme for the side-scan fish finder data of the fishing boat with light. Divide the side-scan fish finder data of the fishing boat with light into six fields AF, corresponding to six different areas under the fishing boat with light. Combine intelligent LED lights, routers, host and other equipment to form an intelligent lighting adjustment system for the fishing boat with light.

[0054] (2) Collect data from the fish finder on the fishing boat and determine the target intensity range of the fish species to be caught based on empirical formulas;

[0055] (3) Based on the echo intensity range determined in step (2), the background noise of the data in the fish finder is removed; and the fish quantity in the area is calculated and divided into four categories of fishing conditions: no fish, few fish, medium fish, and many fish.

[0056] (4) Based on the fishing conditions calculated in step (3), design an intelligent lighting adjustment scheme for fishing boats in each area using the scheduling system.

[0057] (5) Convert the lighting adjustment scheme of the fishing boat into a lighting adjustment command, and convert the command into a data frame and send it to the fish-attracting lamp ballast via the local area network;

[0058] (6) The ballast controls the white and red light current of the intelligent LED lights on the fishing boat to achieve the effect of brightness control.

[0059] The six-area division scheme of the side-scan fish finder in step (1) follows the following principles: each side of the fishing boat contains three areas. The sponge area corresponding to the fish finder data is determined according to the side-scan angle. Areas A, B, and C represent the three areas from front to back on the left side of the fishing boat with lights. Areas D, E, and F are located on the right side of the fishing boat with lights and correspond to areas A, B, and C respectively.

[0060] The empirical formula in step (2) varies according to the dynamic changes of different fish species. Taking squid fishing boats as an example, the empirical formula for target intensity on squid fishing boats is generally related to their body length. The empirical formula for target intensity at 70kHz frequency in the fish finder on squid fishing boats is as follows:

[0061] TS = 20 log10(DML)-67.4 (1).

[0062] DML represents mantle length. This empirical formula was obtained by referring to the experience of captains and other relevant literature. According to this empirical formula, the target intensity range of squid at a frequency of 70kHz is determined to be between -30dB and -40dB.

[0063] The data processing method in step (3) includes the following sub-steps:

[0064] (31) Adjust the echo intensity range to remove background noise;

[0065] (32) After removing background noise, the number of target fish species is identified from the visualization of the fish finder data using the OpenCV findContours() method;

[0066] (33) Determine the fishing condition level based on the number of target fish species, and divide the fishing condition into four levels: no fish, few fish, medium fish, and many fish.

[0067] The intelligent lighting adjustment scheme in step (4) is implemented in six areas. The lighting in each area includes four brightness intensities from 0 to 3, where 0-3 represent light intensity from weak to strong. The formulas for the changes in white light and red light are as follows:

[0068]

[0069]

[0070] In the formulas (2) and (3), s represents the fishing conditions judged by the system, and the function values ​​0-3 represent the four levels of light intensity.

[0071] The intelligent lighting adjustment scheme in step (4) includes the following steps:

[0072] (41) When the fish finder detects that there are no fish on the sea surface, adjust the white light intensity to 3 and turn off the red light (adjust the white light intensity to 0);

[0073] (42) When the fish finder detects that the fishing conditions on the sea surface are "few fish", adjust the white light intensity to 2 and the red light intensity to 1;

[0074] (43) When the fish finder detects that the fishing conditions on the sea surface are "fish in the water", adjust the white light intensity to 2 and the red light intensity to 3.

[0075] (44) When the fish finder detects that the fishing conditions on the sea surface are "many fish", adjust the white light intensity to 1 and the red light intensity to 2.

[0076] Step (5) includes the following sub-steps:

[0077] (51) Connect the control host and the smart lamp to the same local area network, configure the IP addresses of the control host (command sending end) and the smart lamp (command receiving end) to ensure that the two IP addresses can communicate normally;

[0078] (52) The transmitted data frames are constructed according to the Ethernet data frame standard, and the real-time performance and reliability of data transmission are guaranteed by the signal transmission mechanism in the TCP / IP protocol communication protocol.

[0079] (53) The constructed data packet satisfies the IP data packet format;

[0080] (54) The first two bytes of the data field are valid data, the first byte is the control command for white light, and the second byte is the control command for red light;

[0081] (55) The first four bits and the last four bits of each valid byte are completely consistent, which is used to further verify the accuracy of the data;

[0082] (56) In each valid four bits, the high 1 bit represents the light indicator, 0 represents white light, 1 represents red light, the middle 2 bits represent the intensity code 0-3, and the low 1 bit is the XOR check value of the high 3 bits.

[0083] (57) The light adjustment instruction occupies only one byte of data bits. The high four bits and low four bits of the byte represent the adjustment intensity of two colors of light respectively. That is, each brightness adjustment unit includes 4 bits. The high bit is the light identifier. 0 and 1 of this bit represent white light and red light respectively. The logical values ​​of the middle two bits represent the brightness level of the corresponding color light. The low bit is the check bit, which should be the XOR check value of the first three bits.

[0084] In step (51), the control host is configured as the command sending end and the smart lamp end is configured as the command receiving end.

[0085] In step (6), the color and brightness of the lights are adjusted separately for each area. That is, the fishing conditions on the sea surface are judged for each of the six areas divided in step (1), and the light adjustment command is sent to the corresponding lights.

[0086] The present invention will be further illustrated by a specific embodiment below:

[0087] 1. Data Collection

[0088] The data in this embodiment was collected from the coast of Mauritania (around 22°47.9'N, 16°43.6'W). The fishing vessel used for data collection was a light-dash squid fishing vessel.

[0089] 2. Determine the zoning of fishing vessels

[0090] The fish finder data was divided into six regions: A, B, C, D, E, and F, corresponding to the six areas of the sea surface where the squid fishing boat was located. Figure 2 As shown. Areas A, B, and C represent the three areas on the left side of the fishing boat from front to back, respectively; areas D, E, and F are located on the right side of the fishing boat and correspond to areas A, B, and C, respectively.

[0091] 3. Data Processing

[0092] The empirical formula for target intensity at 70kHz frequency in a squid fishing vessel's fish finder is TS = 20log10(DML) - 67.4 (where DML represents mantle length). To determine the target intensity range for squid in the target sea area, a statistical analysis of the mantle lengths of 100 caught squid was performed. The results are as follows: Figure 8 As shown. Figure 8 Of the 100 squid samples obtained through random sampling, 93 had a mantle length of 20-70 cm. Figure 9 Analysis of the function graph shows that within the range of 20-70cm in body length, the target intensity value monotonically increases. Specifically, when the body length is 20cm, the target intensity value calculated by the empirical formula is -41.379; when the body length is 70cm, the target intensity value calculated by the empirical formula is -30.498. Therefore, according to... Figure 8 , Figure 9 The target intensity range of squid at 70kHz was determined to be between -30dB and -40dB.

[0093] Noisy data (below -60 dB and above 0 dB) was extracted from the dataset, and data cleaning was performed. Visualizations of the data before and after noise removal are shown below. Figure 5 , Figure 6 As shown in Table 1, after noise removal, the `findContours()` method of OpenCV is used to extract contours with higher information content. Contours with no more than 5 points are considered noise values. Each remaining contour represents a squid. The criteria for determining the fishing conditions are shown in Table 1.

[0094] For example, Figure 6 The analysis results indicate that there are 9 squid in the area. The fishing conditions in this area are classified as "medium-sized fish".

[0095] Table 1 Criteria for Determining Fishing Conditions

[0096]

[0097] When a fishing boat enters a new fishing area and the fishing condition is assessed as having no fish, the intelligent control system decides to adjust the white light to its strongest intensity (intensity 3) and turn off the red light. The strong white light is used to attract squid. As the squid gradually approach and the fishing condition is assessed as "few fish," the intelligent control system decides to adjust the white light intensity to 2 and the red light intensity to 1. As the number of squid gradually increases and the fishing condition is assessed as "medium-sized fish," the intelligent control system decides to maintain the white light intensity at 2 and adjust the red light intensity to 3. Increased red light is mainly used to stabilize the fish population. When the squid population gradually reaches saturation and the fishing condition is assessed as "abundant fish," the intelligent control system decides to adjust the white light intensity to 1 and the red light intensity to 2. These decisions are sent to the execution mechanism via data packets.

[0098] 4. Data packet generation and transmission

[0099] After obtaining the fishing condition levels for each region, according to Figure 7 The IP protocol data packet is constructed using the data packet format. For example, when the last digit detected in area A is 9, the fishing condition is determined to be "fish in progress". At this time, the white light intensity is adjusted to 2 and the red light intensity to 3. Then, the two bytes of valid information in the IP protocol data packet are 01010101 and 11111111. 01010101 indicates that the white light intensity is adjusted to 2, and 11111111 indicates that the red light intensity is adjusted to 3. The source address in the data packet is set to the host IP address, and the destination address is set to the IP address corresponding to area A.

[0100] After receiving the data packet, the smart lights in area A parse the information within it and begin adjusting the ballast's output current to achieve a white light intensity of 2 and a red light intensity of 3, completing the intelligent adjustment for area A at that moment. This adjustment process is dynamic and continuous, making real-time adjustments to the lighting based on data detected by the fish finder, achieving the goal of intelligent real-time control.

[0101] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for intelligently adjusting the power and color change of LED fish-attracting lights on a light-attracting fishing boat based on data from a fish finder, characterized in that... Specifically, the following steps are included: (1) Design a regional division scheme for the side-scan fish finder data of the fishing boat with light. Divide the side-scan fish finder data of the fishing boat with light into six fields AF, corresponding to six different areas under the fishing boat with light. Combine intelligent LED lights, routers and host to form an intelligent lighting adjustment system for the fishing boat with light. (2) Collect data from the fish finder on the fishing boat and determine the target echo intensity range of the fish species to be caught based on empirical formulas. (3) According to the echo intensity range determined in step (2), the background noise of the data in the fish finder is removed; and the number of fish in the area is calculated. Based on the number of fish, the fish conditions are divided into four categories: no fish, few fish, medium fish, and many fish. The number of fish detected for few fish is 0-5, the number of fish detected for medium fish is 6-10, and the number of fish detected for many fish is greater than 10. (4) Based on the fishing conditions calculated in step (3), design an intelligent lighting adjustment scheme for fishing boats in each area using the scheduling system; (5) Convert the lighting adjustment scheme of the fishing boat into a lighting adjustment command, and convert the command into a data frame and send it to the fish-attracting lamp ballast via the local area network; (6) The ballast end controls the white and red light current of the intelligent LED lights on the fishing boat to achieve the effect of brightness control; The intelligent lighting adjustment scheme in step (4) is implemented in six areas. The lighting in each area includes four brightness intensities from 0 to 3, where 0-3 represent light intensity from weak to strong. The formulas for the changes in white light and red light are as follows: （2） （3） In formulas (2) and (3), s represents the fishing conditions judged by the system, and the function values ​​0-3 represent the four levels of light intensity.

2. The method for intelligently adjusting the power and color change of the LED fish-attracting lamp on a light-attracting fishing boat based on data from a fish finder, as described in claim 1, is characterized in that... The six-area division scheme of the side-scan fish finder in step (1) follows the following principles: each side of the fishing boat contains three areas. The sea surface area corresponding to the fish finder data is determined according to the side-scan angle. Areas A, B, and C represent the three areas from front to back on the left side of the fishing boat with lights. Areas D, E, and F are located on the right side of the fishing boat with lights and correspond to areas A, B, and C respectively.

3. The method for intelligently adjusting the power and color change of the LED fish-attracting lamp on a light-attracting fishing boat based on data from a fish finder, as described in claim 1, is characterized in that... The empirical formula in step (2) varies dynamically depending on the fish species. The empirical formula for the target echo intensity of a squid fishing boat is generally related to its body length. The empirical formula for the target intensity at 70kHz in the squid fishing boat fish finder is as follows: TS = 20 log10(DML)−67.4 (1), TS represents the target echo intensity, and DML represents the body length.

4. The method for intelligently adjusting the power and color change of the LED fish-attracting lamp on a light-attracting fishing boat based on data from a fish finder, as described in claim 3, is characterized in that... In the formula (1), DML represents the length of the squid. Based on this empirical formula, the target intensity range of squid at a frequency of 70kHz is determined to be between -30dB and -40dB.

5. The method for intelligently adjusting the power and color change of the LED fish-attracting lamp on a light-attracting fishing boat based on data from a fish finder, as described in claim 1, is characterized in that... Step (3) includes the following sub-steps: (31) Adjust the echo intensity range to remove background noise; (32) After removing background noise, the number of target fish species is identified from the visualization of the fish finder data using the OpenCV findContours() method; (33) Determine the fishing condition level based on the number of target fish species, and divide the fishing condition into four levels: no fish, few fish, medium fish, and many fish.

6. The method for intelligently adjusting the power and color change of the LED fish-attracting lamp on a light-attracting fishing boat based on data from a fish finder, as described in claim 1, is characterized in that... The intelligent lighting adjustment scheme in step (4) includes the following steps: (41) When the fish finder detects that there are no fish on the sea surface, adjust the white light intensity to 3 and turn off the red light; (42) When the fish finder detects that the fishing conditions on the sea surface are "few fish", adjust the white light intensity to 2 and the red light intensity to 1; (43) When the fish finder detects that the fishing conditions on the sea surface are "fish in the water", adjust the white light intensity to 2 and the red light intensity to 3. (44) When the fish finder detects that the fishing conditions on the sea surface are "many fish", adjust the white light intensity to 1 and the red light intensity to 2.

7. The method for intelligently adjusting the power and color change of the LED fish-attracting lamp on a light-attracting fishing boat based on data from a fish finder, as described in claim 1, is characterized in that... Step (5) includes the following sub-steps: (51) Connect the control host and the smart lamp to the same local area network, configure the IP addresses of the control host and the smart lamp, and ensure that the two IP addresses can communicate normally; (52) The transmitted data frames are constructed according to the Ethernet data frame standard, and the real-time performance and reliability of data transmission are guaranteed by the signal transmission mechanism in the TCP / IP protocol communication protocol; (53) The constructed data packet satisfies the IP data packet format; (54) The first two bytes of the data field are valid data, the first byte is the control instruction for white light, and the second byte is the control instruction for red light; (55) The first four bits and the last four bits of each valid byte are completely consistent, which is used to further verify the accuracy of the data; (56) In each valid four bits, the high 1 bit represents the light indicator, 0 represents white light, 1 represents red light, the middle 2 bits represent the intensity code 0-3, and the low 1 bit is the XOR check value of the high 3 bits; (57) The light adjustment instruction occupies only one byte of data bits. The high four bits and low four bits of the byte represent the adjustment intensity of the two colors of light respectively. That is, each brightness adjustment unit includes 4 bits. The high bit is the light identifier. 0 and 1 of this bit represent white light and red light respectively. The logical values ​​of the middle two bits represent the brightness level of the corresponding color light. The low bit is the check bit, which should be the XOR check value of the first three bits.

8. The method for intelligently adjusting the power and color change of the LED fish-attracting lamp on a light-attracting fishing boat based on data from a fish finder, as described in claim 7, is characterized in that... In step (51), the control host is configured as the command sending end and the smart lamp end is configured as the command receiving end.

9. A method for intelligently adjusting the power and color change of LED fish-attracting lights on a light-attracting fishing boat based on data from a fish finder, as described in claim 1, is characterized in that... In step (6), the color and brightness of the lights are adjusted separately for each area. That is, the fishing conditions on the sea surface are judged for each of the six areas divided in step (1), and the light adjustment command is sent to the corresponding lights.

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