Blue-green algae inhibitor accurate spraying method and system based on unmanned ship

Abstract

The invention provides a blue-green algae inhibitor accurate spraying method and system based on an unmanned ship, and belongs to the technical field of blue-green algae treatment. The technical problem that the dosage of the blue-green algae inhibitor cannot be accurately controlled in the blue-green algae killing process is solved. According to the technical scheme, the spraying method comprises the following steps of collecting target water area environment data and blue-green algae concentration data, drawing a target water area route planning map, dividing the target water area route planning map into a plurality of sub-areas, judging target sub-areas needing to be sprayed with inhibitors, planning a spraying path of an unmanned ship, and determining a spraying scheme of each target sub-area. And setting a spraying path of the unmanned ship and a spraying scheme of each target sub-area, and accurately spraying the blue-green algae inhibitor to the target water area. The system comprises an unmanned ship, a planning and drawing module, a route planning module and a spraying control module. According to the method, the blue-green algae inhibitor is automatically and accurately sprayed to the target water area through the unmanned ship, the spraying path is planned, and automatic treatment of blue-green algae is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of cyanobacteria control, and in particular to a method and system for precisely spraying cyanobacteria inhibitors based on an unmanned vessel. Background Art

[0002] Cyanobacteria are large single-cell prokaryotes that can perform oxygen-producing photosynthesis. In some nutrient-rich water bodies, cyanobacteria often reproduce in large numbers in summer and form water blooms on the water surface. Large-scale cyanobacteria outbreaks are called "green tides". Green tides can cause water quality deterioration. In severe cases, they deplete oxygen in the water and cause fish deaths. What's more serious is that some species of cyanobacteria also produce microcystins. About 50% of green tides contain a large amount of microcystins. In addition to being directly toxic to fish, humans and livestock, microcystins are also an important cause of liver cancer. Therefore, it is very important to control cyanobacteria. Existing cyanobacteria control methods are divided into biological methods, chemical methods and physical methods. The biological method uses beneficial microorganisms to decompose organic matter and inhibit the growth and reproduction of cyanobacteria (for example, invention patent CN201610101517.9), but this method is difficult to apply to severely polluted waters. At the same time, manual detection and the placement of microbial preparations are labor-intensive and costly. The chemical method removes cyanobacteria by adding chemical agents (for example, invention patent CN200910304291.2), but it is easy to cause secondary pollution; the physical method uses manual salvage (for example, invention patent CN200910304291.2), but the manual method has high labor costs and low efficiency, and can only be used in large-scale outbreaks. Therefore, how to provide a method and system for accurately spraying cyanobacteria inhibitors based on unmanned boats is a problem that technicians in this field need to solve urgently. Summary of the invention

[0003] The purpose of the present invention is to provide a method and system for accurately spraying cyanobacteria inhibitors based on an unmanned boat, plan the spraying path of the unmanned boat using a path planning algorithm, and accurately spray cyanobacteria inhibitors based on the cyanobacteria concentration in the target waters and path planning to achieve automated control of cyanobacteria in the target waters.

[0004] In order to achieve the above-mentioned invention object, the technical solution adopted by the present invention is specifically: a method for precise spraying of cyanobacteria inhibitors based on an unmanned boat, comprising the following steps:

[0005] S1. Collect environmental data and blue algae concentration data of the target waters and draw a route planning map of the target waters;

[0006] S2, dividing the route planning map of the target water area into multiple sub-areas, and determining the target sub-areas where the inhibitor needs to be sprayed based on the cyanobacteria concentration data in the sub-areas;

[0007] S3, planning the spraying path of the unmanned boat based on the target sub-area where the inhibitor needs to be sprayed and the environmental data of the target waters;

[0008] S4, determining a spraying scheme for each target sub-area based on the cyanobacteria concentration data in the target sub-area;

[0009] S5. Set the spraying path of the unmanned boat and the spraying plan for each target sub-area to accurately spray the cyanobacteria inhibitor in the target waters.

[0010] Furthermore, step S1 is specifically as follows: obtaining contour data of the target waters, setting a plurality of cyanobacteria concentration sampling points in the target waters, setting a cyanobacteria concentration detection instrument and a laser sensor on the unmanned boat, so that the unmanned boat starts from the starting sampling point and traverses all sampling points, and collecting cyanobacteria concentration data and surrounding obstacle data of all sampling points during the navigation of the unmanned boat, and drawing a route planning map of the target waters in combination with the contour data of the target waters, the cyanobacteria concentration data of all sampling points and the surrounding obstacle data.

[0011] Furthermore, step S2 is specifically as follows: dividing the route planning map of the target water area into a plurality of grid sub-areas of equal size, marking the sub-areas with obstacles as inaccessible sub-areas, marking the cyanobacteria concentration data for each sub-area, and when the cyanobacteria concentration in a sub-area is greater than 5×106cell / L, dividing it into a target sub-area requiring spraying of inhibitors.

[0012] Furthermore, the step S3 is specifically as follows:

[0013] S31, planning the spraying order of the inhibitors in all target sub-areas to obtain a spraying sequence;

[0014] S32, planning the shortest spraying path for every two adjacent target sub-areas in the spraying sequence;

[0015] S33, combining the spraying sequence and the shortest spraying path of every two adjacent target sub-areas in the spraying sequence to obtain the spraying path of the unmanned boat.

[0016] Further, the step S31 is specifically as follows: setting the maximum number of iterations and the number of planning schemes for spraying sequence planning, constructing a spraying sequence matrix composed of all planning schemes, constructing a distance matrix between target sub-areas, calculating the fitness of all planning schemes based on the spraying sequence matrix and the distance matrix, sorting the planning schemes from low to high according to the fitness, updating all planning schemes and recalculating the fitness of all planning schemes, sorting the planning schemes from low to high according to the new fitness, repeating the process of updating all planning schemes, calculating fitness and sorting until the maximum number of iterations is reached, and taking the planning scheme with the lowest fitness as the final spraying sequence;

[0017] The spray sequence matrix is:

[0018]

[0019] In the formula, is the position of the unmanned ship in the jth sub-area in the i-th planning scheme, i∈[1,n], j∈[1,m], n is the number of planning schemes, and m is the number of target sub-areas; each row in the spraying sequence matrix P represents a planning scheme;

[0020] The distance matrix is:

[0021]

[0022] In the formula, S jk is the distance between the jth target sub-region and the kth target sub-region;

[0023] The fitness calculation is as follows:

[0024] f=minP i (∑S i(mm) )

[0025] Where P i is the spraying sequence represented by the i-th planning scheme, S i(mm) is the distance of the spraying sequence represented by the i-th planning scheme.

[0026] Further, the step S32 is specifically as follows: taking the target sub-region with the front order in the two adjacent target sub-regions as the starting point and the other target sub-region as the end point, setting the maximum number of iterations of the shortest spraying path and the number of spraying paths, for each spraying path, calculating its transition probability and selecting its next sub-region according to the transition probability, adding the selected sub-region to the spraying path and updating the position of the unmanned ship in the current spraying path, calculating the distances of all spraying paths, if the shortest path distance of this round is less than the global shortest path distance, then updating the shortest path distance of this round to the new global shortest path distance, updating the pheromone and all spraying paths, repeatedly calculating the distances of all spraying paths, updating the global shortest path distance, updating the pheromone and all spraying paths until the maximum number of iterations is reached, and taking the spraying path corresponding to the global shortest path distance as the shortest spraying path between the two adjacent target sub-regions;

[0027] The calculation of transition probability is:

[0028]

[0029] In the formula, is the probability of the unmanned ship transferring from sub-area i to sub-area j in the kth spraying path, G is the set of all transferable sub-areas when the unmanned ship is in a sub-area in the current spraying path, a, b, c are constants, R is the set of sub-areas that have not been visited, τ ij is the pheromone from sub-region i to sub-region j, d ij is the distance from sub-region i to sub-region j, r is the sub-region that has not been visited, τ ir is the pheromone from sub-region i to sub-region r, d ir is the distance from sub-region i to sub-region r, L k is the length of the kth spraying path;

[0030] The updates for pheromones are:

[0031]

[0032] In the formula, is the updated pheromone, ρ is the pheromone retention rate, is the pheromone of the global shortest path.

[0033] Furthermore, step S4 is specifically as follows: the unmanned ship determines the dosage of the cyanobacteria inhibitor based on the cyanobacteria concentration data in the target sub-area, the speed data of the unmanned ship, and the real-time detected water depth data, and the unmanned ship achieves precise control of the dosage of the cyanobacteria inhibitor by controlling the spraying rate of the cyanobacteria inhibitor.

[0034] Furthermore, after step S5, the following steps are further included:

[0035] S6, setting a data collection time interval and a spraying time interval, and within a data collection time interval, for a sub-area not sprayed with the inhibitor, determining a new target sub-area based on the growth curve of the cyanobacteria and the spraying time interval;

[0036] S7. Plan a new spraying path based on the environmental data of the new target sub-area and the target water area.

[0037] Furthermore, after step S7, the following steps are further included:

[0038] S8. Repeat S6-S7 within a data collection time interval until the next data collection time node.

[0039] In order to better achieve the above-mentioned purpose of the invention, the present invention also provides a precise spraying system of cyanobacteria inhibitors based on an unmanned boat, comprising: an unmanned boat, a planning and mapping module, a route planning module and a spraying control module, wherein the unmanned boat is provided with a cyanobacteria concentration detection instrument, a laser sensor and a cyanobacteria inhibitor spraying device, the unmanned boat is used to collect environmental data and cyanobacteria concentration data of the target water area and perform the precise spraying task of the cyanobacteria inhibitor, the planning and mapping module is used to draw a route planning map of the target water area and determine the target sub-area where the inhibitor needs to be sprayed, the route planning module is used to plan the spraying path of the unmanned boat, and the spraying control module is used to determine the spraying plan for each target sub-area.

[0040] Furthermore, the unmanned boat is also provided with a GPS module and a depth sounder. The GPS module is used to obtain the real-time speed of the unmanned boat, and the depth sounder is used to obtain the depth of the water body. When the unmanned boat performs the spraying task, the system automatically controls the opening of the spraying system according to parameters such as the cyanobacteria concentration, the water body depth, and the speed of the unmanned boat, and accurately controls the dosage of the cyanobacteria inhibitor.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] 1. The present invention uses unmanned boats to spray inhibitors to control blue algae, which can save a lot of manpower. By detecting the concentration of blue algae in the target waters and planning the spraying route and confirming the spraying plan, the concentration of blue algae can be controlled, the outbreak of blue algae can be prevented, and water pollution can be avoided;

[0043] 2. The present invention only needs to collect environmental data and cyanobacteria concentration data once to plan the path of each spraying within a certain period of time, thereby realizing automated cyanobacteria inhibitor spraying and cyanobacteria control;

[0044] 3. The present invention can accurately control the dosage of cyanobacteria inhibitor in real time according to the changes in cyanobacteria concentration data detected in real time, which can effectively kill cyanobacteria and reduce the dosage and cost of cyanobacteria inhibitor;

[0045] 4. The present invention can monitor the concentration change of cyanobacteria in the water body before the cyanobacteria outbreak, and spray cyanobacteria inhibitors in advance, so as to kill the cyanobacteria in the water body in advance and avoid large-scale cyanobacteria outbreak. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0047] Figure 1 The present invention is a flow chart of the precise spraying method of the cyanobacteria inhibitor.

[0048] Figure 2 It is a flow chart of spraying path planning of the present invention.

[0049] Figure 3 This is a schematic diagram of the distribution of blue algae concentration in the water area on the third day after spraying in Example 2 of the present invention.

[0050] Figure 4 This is a schematic diagram of the distribution of cyanobacteria concentration in the area three days after spraying in Example 2 of the present invention.

[0051] Figure 5 In Example 3 of the present invention, it is a distribution map of cyanobacteria concentration before spraying in a certain area on June 7, 2024.

[0052] Figure 6 In Example 3 of the present invention, Figure 5 In the same area, the distribution map of cyanobacteria concentration after the unmanned boat completed the automatic spraying of cyanobacteria inhibitors on June 8, 2024. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. Of course, the specific embodiments described here are only used to explain the present invention and are not used to limit the present invention.

[0054] Example 1

[0055] See also Figure 1 and Figure 2 This embodiment discloses a method for accurately spraying cyanobacteria inhibitors based on an unmanned boat, such as Figure 1 As shown, the following steps are included:

[0056] S1. Collect environmental data and blue algae concentration data of the target waters and draw a route planning map of the target waters;

[0057] S2, dividing the route planning map of the target water area into multiple sub-areas, and determining the target sub-areas where the inhibitor needs to be sprayed based on the cyanobacteria concentration data in the sub-areas;

[0058] S3, planning the spraying path of the unmanned boat based on the target sub-area where the inhibitor needs to be sprayed and the environmental data of the target waters;

[0059] S4, determining a spraying scheme for each target sub-area based on the cyanobacteria concentration data in the target sub-area;

[0060] S5. Set the spraying path of the unmanned boat and the spraying plan for each target sub-area to accurately spray the cyanobacteria inhibitor in the target waters.

[0061] Preferably, S1 specifically includes: obtaining contour data of the target waters, setting a plurality of cyanobacteria concentration sampling points in the target waters, setting a cyanobacteria concentration detection instrument and a laser sensor on an unmanned boat, so that the unmanned boat starts from a starting sampling point and traverses all sampling points, and collects cyanobacteria concentration data and surrounding obstacle data of all sampling points during the navigation of the unmanned boat, and draws a route planning map of the target waters in combination with the contour data of the target waters, the cyanobacteria concentration data of all sampling points and the surrounding obstacle data.

[0062] Preferably, S2 is specifically as follows: dividing the route planning map of the target water area into a plurality of grid sub-areas of equal size, marking the sub-areas with obstacles as inaccessible sub-areas, marking the cyanobacteria concentration data for each sub-area, and when the cyanobacteria concentration in a sub-area is greater than 5×10 6 cell / L, it is divided into target sub-areas that need to be sprayed with inhibitors.

[0063] Preferably, S3 is specifically:

[0064] S31, planning the spraying order of the inhibitors in all target sub-areas to obtain a spraying sequence;

[0065] S32, planning the shortest spraying path for every two adjacent target sub-areas in the spraying sequence;

[0066] S33, combining the spraying sequence and the shortest spraying path of every two adjacent target sub-areas in the spraying sequence to obtain the spraying path of the unmanned boat.

[0067] Preferably, S31 is specifically as follows: setting the maximum number of iterations and the number of planning schemes for spraying sequence planning, constructing a spraying sequence matrix composed of all planning schemes, constructing a distance matrix between target sub-areas, calculating the fitness of all planning schemes based on the spraying sequence matrix and the distance matrix, sorting the planning schemes from low to high according to their fitness, updating all planning schemes and recalculating the fitness of all planning schemes, sorting the planning schemes from low to high according to the new fitness, repeating the process of updating all planning schemes, calculating fitness and sorting until the maximum number of iterations is reached, and taking the planning scheme with the lowest fitness as the final spraying sequence.

[0068] In the embodiment of the present invention, the spraying sequence matrix is:

[0069]

[0070] In the formula, is the position of the unmanned ship in the jth sub-area in the i-th planning scheme, i∈[1,n], j∈[1,m], n is the number of planning schemes, and m is the number of target sub-areas; each row in the spraying sequence matrix P represents a planning scheme;

[0071] The distance matrix is:

[0072]

[0073] In the formula, S jk is the distance between the jth target sub-region and the kth target sub-region;

[0074] The fitness calculation is as follows:

[0075] f=minP i (∑S i(mm) )

[0076] Where P i is the spraying sequence represented by the i-th planning scheme, S i(mm) is the distance of the spraying sequence represented by the i-th planning scheme.

[0077] Preferably, if Figure 2 As shown, S32 is specifically: taking the target sub-region with the front order in the two adjacent target sub-regions as the starting point and the other target sub-region as the end point, setting the maximum number of iterations of the shortest spraying path and the number of spraying paths, for each spraying path, calculating its transfer probability and selecting its next sub-region according to the transfer probability, adding the selected sub-region to the spraying path and updating the position of the unmanned ship in the current spraying path, calculating the distances of all spraying paths, if the shortest path distance of this round is less than the global shortest path distance, then updating the shortest path distance of this round to the new global shortest path distance, updating the pheromone and all spraying paths, repeatedly calculating the distances of all spraying paths, updating the global shortest path distance, updating the pheromone and all spraying paths until the maximum number of iterations is reached, and taking the spraying path corresponding to the global shortest path distance as the shortest spraying path between the two adjacent target sub-regions.

[0078] In the embodiment of the present invention, the calculation of the transition probability is:

[0079]

[0080] In the formula, is the probability of the unmanned ship transferring from sub-area i to sub-area j in the kth spraying path, G is the set of all transferable sub-areas when the unmanned ship is in a sub-area in the current spraying path, a, b, c are constants, R is the set of sub-areas that have not been visited, τ ij is the pheromone from sub-region i to sub-region j, d ij is the distance from sub-region i to sub-region j, r is the sub-region that has not been visited, τ ir is the pheromone from sub-region i to sub-region r, d ir is the distance from sub-region i to sub-region r, L kis the length of the kth spray path.

[0081] The updates for pheromones are:

[0082]

[0083] In the formula, is the updated pheromone, ρ is the pheromone retention rate, is the pheromone of the global shortest path. In the embodiment of the present invention, only the pheromone of the global shortest path is updated.

[0084] Preferably, S4 is specifically: the unmanned ship determines the dosage of the cyanobacteria inhibitor based on the cyanobacteria concentration data in the target sub-area, the speed data of the unmanned ship and the real-time detected water depth data, and the unmanned ship achieves precise control of the dosage of the cyanobacteria inhibitor by controlling the spraying rate of the cyanobacteria inhibitor.

[0085] In an embodiment of the present invention, the unmanned ship is equipped with a cyanobacteria inhibitor in the middle warehouse, and a spiral structure is provided at the bottom of the middle warehouse. The screw speed is controlled by a motor, and the cyanobacteria inhibitor falls into the lowered silo by its own gravity. The left side of the silo is a water inlet, and the right side is a water outlet. The water inlet is connected to a water pump, and the right water outlet is connected to the propeller position of the unmanned ship. When the screw rotates, the water pump automatically starts, mixes the cyanobacteria inhibitor in the silo with water, and then flows out from the right water outlet. The thrust and stirring ability of the propeller when the unmanned ship is sailing are used to evenly diffuse the outflowing powder-liquid mixture into the water body. The screw rotation speed is automatically controlled by real-time monitoring of algae protein concentration, the speed of the unmanned ship obtained by GPS, and the water depth data, so as to accurately control the dosage of the cyanobacteria inhibitor. When reaching an area where the cyanobacteria concentration exceeds a threshold, the screw rotation is started to push the cyanobacteria inhibitor. When leaving the area, the screw rotation is turned off. The higher the cyanobacteria concentration, the greater the screw rotation speed, and the greater the dosage of the cyanobacteria inhibitor.

[0086] In the embodiment of the present invention, the spray flow rate of the inhibitor is in the range of 0.5-3 g / m 3 When the concentration of cyanobacteria is 5×10 6 cell / L, the spraying flow rate is 0.5g / m 3 When the concentration of cyanobacteria is greater than or equal to 10 7 cell / L, the spraying flow rate is 3g / m 3 , based on the spraying flow rate, the speed of the unmanned boat and the depth of the water body, the current rotation speed of the screw is obtained.

[0087] Preferably, after S5, the step further includes:

[0088] S6, setting a data collection time interval and a spraying time interval, and within a data collection time interval, for a sub-area not sprayed with the inhibitor, determining a new target sub-area based on the growth curve of the cyanobacteria and the spraying time interval;

[0089] S7. Plan a new spraying path based on the environmental data of the new target sub-area and the target water area.

[0090] In an embodiment of the present invention, the concentration of cyanobacteria in the sub-area at the next spraying time node can be calculated based on the growth curve of cyanobacteria and the spraying time interval, and based on this concentration, it is determined whether the sub-area needs to be sprayed with inhibitors and the inhibitor spraying plan is determined.

[0091] Preferably, after S7, the method further includes:

[0092] S8. Repeat S6-S7 within a data collection time interval until the next data collection time node.

[0093] In the embodiment of the present invention, one data collection time interval includes a plurality of spraying time intervals. When one data collection time interval ends, the environmental data and the blue algae concentration data of the target water area are collected again.

[0094] and Figure 1 Corresponding to the method, an embodiment of the present invention further discloses a precise spraying system of cyanobacteria inhibitors based on an unmanned boat, which executes the above-mentioned precise spraying method of cyanobacteria inhibitors based on an unmanned boat, including: an unmanned boat, a planning and mapping module, a route planning module and a spraying control module, wherein the unmanned boat is provided with a cyanobacteria concentration detection instrument, a laser sensor and a cyanobacteria inhibitor spraying device, the unmanned boat is used to collect environmental data and cyanobacteria concentration data of the target water area and perform the precise spraying task of the cyanobacteria inhibitor, the planning and mapping module is used to draw a route planning map of the target water area and determine the target sub-area where the inhibitor needs to be sprayed, the route planning module is used to plan the spraying path of the unmanned boat, and the spraying control module is used to determine the spraying plan for each target sub-area.

[0095] Preferably, in an embodiment of the present invention, the unmanned boat is also provided with a GPS module and a depth sounder, the GPS module is used to obtain the real-time speed of the unmanned boat, and the depth sounder is used to obtain the depth of the water body. When the unmanned boat performs a spraying task, the system automatically controls the opening of the spraying system according to parameters such as the cyanobacteria concentration, the water body depth, and the speed of the unmanned boat, and accurately controls the dosage of the cyanobacteria inhibitor.

[0096] Example 2

[0097] The cyanobacteria inhibitor was sprayed in a certain water area. The concentration and distribution of cyanobacteria before the spraying of cyanobacteria inhibitor were as follows: Figure 3As shown. The red area indicates the blue algae outbreak area, and the red degree indicates the concentration of blue algae. It can be seen that the concentration of blue algae in this area has dropped significantly after three days of spraying. Figure 4 .

[0098] Example 3

[0099] See also Figure 5 This is a map of the concentration distribution of cyanobacteria in a certain area before spraying on June 7, 2024.

[0100] See also Figure 6 This is the distribution map of cyanobacteria concentration in the same area after the unmanned boat completed the automatic spraying of cyanobacteria inhibitors on June 8, 2024.

[0101] It can be seen that after 24 hours, the concentration of cyanobacteria in most locations in the area has been greatly reduced.

[0102] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for precise spraying of cyanobacteria inhibitors based on an unmanned boat, characterized in that: The following steps are involved: S1. Collect environmental data and blue algae concentration data of the target waters and draw a route planning map of the target waters; S2, dividing the route planning map of the target water area into multiple sub-areas, and determining the target sub-areas where the inhibitor needs to be sprayed based on the cyanobacteria concentration data in the sub-areas; S3, planning the spraying path of the unmanned boat based on the target sub-area where the inhibitor needs to be sprayed and the environmental data of the target waters; S4, determining a spraying scheme for each target sub-area based on the cyanobacteria concentration data in the target sub-area; S5, setting the spraying path of the unmanned boat and the spraying plan for each target sub-area, and accurately spraying the cyanobacteria inhibitor in the target waters; S6, setting a data collection time interval and a spraying time interval, and within a data collection time interval, for a sub-area not sprayed with the inhibitor, determining a new target sub-area based on the growth curve of the cyanobacteria and the spraying time interval; S7, planning a new spraying path based on the environmental data of the new target sub-area and the target water area; S8. Repeat steps S6 to S7 within a data collection time interval until the next data collection time node.

2. The method for precise spraying of cyanobacteria inhibitors based on an unmanned boat according to claim 1, characterized in that: The step S1 specifically includes: obtaining contour data of the target water area, setting a plurality of cyanobacteria concentration sampling points in the target water area, setting a cyanobacteria concentration detection instrument and a laser sensor on the unmanned boat, so that the unmanned boat starts from the starting sampling point and traverses all sampling points, collecting cyanobacteria concentration data and surrounding obstacle data of all sampling points during the navigation of the unmanned boat, and drawing a route planning map of the target water area in combination with the contour data of the target water area, the cyanobacteria concentration data of all sampling points and the surrounding obstacle data.

3. The method for precise spraying of cyanobacteria inhibitors based on an unmanned boat according to claim 1, characterized in that: The step S2 specifically includes: dividing the route planning map of the target water area into a plurality of grid sub-areas of equal size, marking the sub-areas with obstacles as inaccessible sub-areas, marking the cyanobacteria concentration data for each sub-area, and when the cyanobacteria concentration in a sub-area is greater than 5×106cell / L, dividing it into a target sub-area requiring spraying of inhibitors.

4. The method for precise spraying of cyanobacteria inhibitors based on an unmanned boat according to claim 1, characterized in that: The step S3 specifically comprises the following steps: S31, planning the spraying order of the inhibitors in all target sub-areas to obtain a spraying sequence; S32, planning the shortest spraying path for every two adjacent target sub-areas in the spraying sequence; S33, combining the spraying sequence and the shortest spraying path of every two adjacent target sub-areas in the spraying sequence to obtain the spraying path of the unmanned boat.

5. The method for precise spraying of cyanobacteria inhibitors based on an unmanned boat according to claim 4, characterized in that: The step S31 specifically includes: setting the maximum number of iterations and the number of planning schemes for spraying sequence planning, constructing a spraying sequence matrix composed of all planning schemes, constructing a distance matrix between target sub-areas, calculating the fitness of all planning schemes based on the spraying sequence matrix and the distance matrix, sorting the planning schemes from low to high according to the fitness, updating all planning schemes and recalculating the fitness of all planning schemes, sorting the planning schemes from low to high according to the new fitness, repeating the process of updating all planning schemes, calculating fitness and sorting until the maximum number of iterations is reached, and taking the planning scheme with the lowest fitness as the final spraying sequence; The spray sequence matrix is: In the formula, is the position of the unmanned ship in the jth sub-area in the i-th planning scheme, i∈[1,n], j∈[1,m], n is the number of planning schemes, and m is the number of target sub-areas; Each row in the spray sequence matrix P represents a planning scheme; The distance matrix is: In the formula, S jk is the distance between the jth target sub-region and the kth target sub-region; The fitness calculation is as follows: f=minP i (∑S i(mm) ) Where P i is the spraying sequence represented by the i-th planning scheme, S i(mm) is the distance of the spraying sequence represented by the i-th planning scheme.

6. The method for precise spraying of cyanobacteria inhibitors based on an unmanned boat according to claim 4, characterized in that: The step S32 is specifically as follows: taking the target sub-region with the front order in the two adjacent target sub-regions as the starting point and the other target sub-region as the end point, setting the maximum number of iterations of the shortest spraying path and the number of spraying paths, for each spraying path, calculating its transition probability and selecting its next sub-region according to the transition probability, adding the selected sub-region to the spraying path and updating the position of the unmanned ship in the current spraying path, calculating the distances of all spraying paths, if the shortest path distance of this round is less than the global shortest path distance, then updating the shortest path distance of this round to the new global shortest path distance, updating the pheromone and all spraying paths, repeatedly calculating the distances of all spraying paths, updating the global shortest path distance, updating the pheromone and all spraying paths until the maximum number of iterations is reached, and taking the spraying path corresponding to the global shortest path distance as the shortest spraying path between the two adjacent target sub-regions; The calculation of transition probability is: In the formula, is the probability of the unmanned ship transferring from sub-area i to sub-area j in the kth spraying path, G is the set of all transferable sub-areas when the unmanned ship is in a sub-area in the current spraying path, a, b, c are constants, R is the set of sub-areas that have not been visited, τ ij is the pheromone from sub-region i to sub-region j, d ij is the distance from sub-region i to sub-region j, r is the sub-region that has not been visited, τ ir is the pheromone from sub-region i to sub-region r, d ir is the distance from sub-region i to sub-region r, L k is the length of the kth spraying path; The updates for pheromones are: In the formula, is the updated pheromone, ρ is the pheromone retention rate, is the pheromone of the global shortest path.

7. The method for precise spraying of cyanobacteria inhibitors based on an unmanned boat according to claim 1, characterized in that: The step S4 is specifically as follows: the unmanned ship determines the dosage of the cyanobacteria inhibitor based on the cyanobacteria concentration data in the target sub-area, the speed data of the unmanned ship and the real-time detected water depth data, and the unmanned ship achieves precise control of the dosage of the cyanobacteria inhibitor by controlling the spraying rate of the cyanobacteria inhibitor.

8. A precise spraying system of cyanobacteria inhibitor based on unmanned boat, characterized in that: The method for precise spraying of cyanobacteria inhibitor based on an unmanned boat according to any one of claims 1 to 7 comprises: an unmanned boat, a planning and mapping module, a route planning module and a spraying control module; Among them, the unmanned ship is equipped with a cyanobacteria concentration detection instrument, a laser sensor and a cyanobacteria inhibitor spraying device; The unmanned boat is used to collect environmental data and cyanobacteria concentration data of the target waters and perform precise spraying of cyanobacteria inhibitors; The planning and mapping module is used to draw a route planning map of the target water area and determine the target sub-area where the inhibitor needs to be sprayed; The route planning module is used to plan the spraying path of the unmanned boat, and the spraying control module is used to determine the spraying plan for each target sub-area.

9. The blue algae inhibitor precision spraying system based on an unmanned boat according to claim 8, characterized in that: The unmanned boat is also provided with a GPS module and a depth sounder. The GPS module is used to obtain the real-time speed of the unmanned boat, and the depth sounder is used to obtain the depth of the water body. When the unmanned boat performs the spraying task, the system automatically controls the opening of the spraying system according to parameters such as the cyanobacteria concentration, the water body depth, and the speed of the unmanned boat, and accurately controls the dosage of the cyanobacteria inhibitor.

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