Mosquito proliferation suppression program, computer-recordable recording medium with mosquito proliferation suppression program recorded therein, mosquito proliferation suppression system, and mosquito proliferation suppression method

Abstract

To provide a mosquito proliferation suppression program for analyzing a puddle having a high possibility of inhabitation of a larva of a mosquito on the basis of an image obtained from a flying object, a computer-readable recording medium with the mosquito proliferation suppression program recorded therein, a mosquito proliferation suppression system, and a mosquito proliferation suppression method.SOLUTION: A mosquito proliferation suppression program of the present invention causes a computer to execute: an acquisition step of acquiring spreading of scattered light of a laser beam in a puddle 4, the laser beam being emitted from a flying object 6 to the puddle, in an image obtained from the flying object; and a turbidity estimation step of estimating turbidity of the puddle on the basis of spreading W of the scattered light.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a mosquito breeding control program, a computer-readable recording medium on which the mosquito breeding control program is recorded, a mosquito breeding control system, and a mosquito breeding control method. [Background technology]

[0002] Preventing the spread of mosquito-borne infectious diseases such as malaria and dengue fever is a very important issue. In order to reduce mosquito-borne infectious diseases, a method called Larval Source Management (hereinafter referred to as "LSM") has been proposed. LSM is a method of reducing the population of mosquito larvae by spraying insecticides in water bodies that serve as breeding grounds for mosquito larvae. LSM is sometimes undertaken as a national project in African countries as a measure against infectious diseases. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2020-139871 Summary of the Invention [Problem to be solved by the invention]

[0004] However, LSM has not been widely adopted due to the following reasons: The first problem is that workers have to search for puddles by walking from the ground, which is labor-intensive and time-consuming. After it rains over a vast area of ​​land, many puddles form simultaneously. In addition, eggs are found on the dry surface of the ground, and within 2-3 days after the puddles form, the eggs turn into larvae, and within a few days to a week, the larvae go through a pupa stage called a giant mosquito larva and then become adults. After it rains and puddles form, it is necessary to quickly spray insecticides, etc. However, because workers have to search for puddles on foot, there is a problem of a shortage of workers, and the work cannot be completed in time.

[0005] The second problem is that, traditionally, when carrying out LSM, workers have to spray pesticides in all puddles. Spraying puddles over a wide area requires a large number of workers. Furthermore, spraying puddles requires a large amount of pesticide, which increases the cost of purchasing the pesticide. Using large amounts of pesticide also raises concerns about the environmental impact. Furthermore, spraying large amounts of pesticide leaves its residues for a long period of time, affecting not only mosquito larvae but also surrounding organisms. Given the living environment of malaria-prone areas, this could pose a health risk to humans.

[0006] In response to this problem, the inventors of the present invention have conducted research into how to efficiently search for puddles over a wide area and efficiently find puddles that are likely to be inhabited by mosquito larvae. As described in the description of the present invention, the inventors of the present invention have found through their research that mosquito larvae are likely to inhabit puddles with a certain turbidity.

[0007] However, conventional turbidity measurement methods such as those shown in Patent Document 1 required investigators to actually go to the location of puddles to collect water samples, or to collect water samples and measure them on-site. Therefore, implementing such turbidity measurement methods required time and manpower, making it impossible to efficiently search for puddles over a wide area and efficiently find puddles that are likely to be inhabited by mosquito larvae, and therefore did not contribute to the spread of LSM.

[0008] The present invention has been made to solve such problems, and aims to provide a mosquito breeding suppression program that analyzes puddles where mosquito larvae are likely to live based on images obtained from a flying object, a computer-readable recording medium on which the mosquito breeding suppression program is recorded, a mosquito breeding suppression system, and a mosquito breeding suppression method. [Means for solving the problem]

[0009] In order to achieve the above-mentioned object, according to one embodiment of the present invention, there is provided a mosquito breeding control program that analyzes puddles that are likely to be inhabited by mosquito larvae based on images obtained from an aerial vehicle, and causes a computer to execute an acquisition step of acquiring the spread of scattered light in the puddle of laser light irradiated from the aerial vehicle onto the puddle in the images obtained from the aerial vehicle, and a turbidity estimation step of estimating the turbidity of the puddle based on the spread of scattered light. According to one embodiment of the present invention, the mosquito breeding control program can execute a turbidity estimation step, which estimates the turbidity of the puddle based on the spread of the scattered light acquired by the acquisition step. This allows the turbidity of the puddle, a biologically important factor in analyzing puddles likely to be home to mosquito larvae, to be estimated, and puddles likely to be home to mosquito larvae can be efficiently identified based on images acquired from the flying object. Therefore, since puddles likely to be home to mosquito larvae can be efficiently identified, a limited number of workers can spray insecticide on the identified puddles, thereby reducing the number of workers, labor, and amount of insecticide used. Furthermore, for example, by identifying puddles unlikely to be home to mosquito larvae, a limited number of workers can avoid spraying insecticide on puddles unlikely to breed, thereby reducing the number of workers, labor, and amount of insecticide used.

[0010] According to one embodiment of the present invention, the acquisition step of the mosquito breeding control program preferably acquires the spread of scattered light in a puddle of infrared wavelength laser light irradiated from the flying object onto the puddle in an image obtained from the flying object. According to one embodiment of the present invention configured as described above, because infrared laser light is easily absorbed by water, it is easy to distinguish between scattered light resulting from the reflection of infrared laser light by colloids in the water and regions of water where the infrared laser light is absorbed. This improves the accuracy of measuring the spread of scattered light and the accuracy of turbidity estimation. Furthermore, by using an infrared camera and an infrared laser, each device is easily available, allowing the system to be constructed relatively easily and inexpensively.

[0011] According to one embodiment of the present invention, the wavelength of the laser light is preferably within the range of 950 nm to 1000 nm. According to one embodiment of the present invention configured in this manner, the wavelength of the laser light is within the range of 950 nm to 1000 nm, making it easier to build a system using an infrared camera and an infrared laser.

[0012] According to one embodiment of the present invention, the acquisition step of the mosquito breeding control program preferably further calculates the spread of scattered light in the image obtained from the flying object based on the flight altitude of the flying object at the time the image obtained from the flying object was taken. According to one embodiment of the present invention configured as described above, the acquisition step of the mosquito breeding control program calculates the spread of scattered light in the image obtained from the flying object based on the flying object's flight altitude at the time the image was captured, thereby allowing the mosquito breeding control program to more accurately recognize the spread of scattered light based on the flying object's altitude.

[0013] According to one embodiment of the present invention, the mosquito breeding control program preferably further causes the computer to execute an evaluation step of evaluating the risk of mosquito larvae inhabiting the puddle based on the turbidity estimated by the turbidity estimation step. According to one embodiment of the present invention configured as described above, the mosquito breeding control program can execute an evaluation step of evaluating the risk of mosquito larvae inhabiting the puddle based on the turbidity estimated by the turbidity estimation step, thereby enabling the risk of mosquito larvae inhabiting each puddle to be evaluated and allowing a limited number of workers to spray insecticide preferentially to puddles with a high risk, thereby further reducing the number of workers, labor, and amount of insecticide used.

[0014] According to one embodiment of the present invention, the mosquito breeding control program preferably further includes an output step of displaying puddles that are evaluated as high risk by the evaluation step on a display device, distinguishing them from other puddles in the image obtained from the flying object. According to one embodiment of the present invention, the mosquito breeding control program can execute an output step in which a computer displays puddles evaluated as high risk in the evaluation step, distinguishing them from other puddles in the image obtained from the flying object, thereby making it easier for workers spraying puddles to know which puddles to spray with the insecticide, thereby improving the speed and efficiency of the worker's spraying work.

[0015] According to one embodiment of the present invention, preferably, a computer-readable recording medium having any of the above-mentioned mosquito breeding control programs recorded thereon. According to one embodiment of the present invention configured in this manner, a computer-readable recording medium having the above-described mosquito breeding suppression program recorded thereon can be used to cause a computer to execute predetermined steps, thereby efficiently detecting puddles that are likely to be inhabited by mosquito larvae.

[0016] According to one embodiment of the present invention, there is provided a mosquito breeding control system that analyzes puddles that are likely to be inhabited by mosquito larvae based on images obtained from a flying object, and the system includes: a flying object that flies above the ground; an irradiation device that is attached to the flying object and irradiates laser light; a camera that is attached to the flying object and acquires images; and an estimation device that acquires the spread of scattered light in the puddle of the laser light irradiated from the flying object to the puddle in the images acquired by the camera, and estimates the turbidity of the puddle based on the spread of scattered light. According to one embodiment of the present invention, the estimation device of the mosquito breeding control system can acquire the spread of scattered light in a puddle from the laser beam irradiated from the airborne object onto the puddle in an image acquired by the camera, and estimate the turbidity of the puddle based on the spread of scattered light. This allows for estimation of the turbidity of a puddle, which is a biologically important factor in analyzing puddles likely to be home to mosquito larvae, and can efficiently identify puddles likely to be home to mosquito larvae based on the image acquired from the airborne object. Therefore, since puddles likely to be home to mosquito larvae can be efficiently identified, a limited number of workers can spray insecticide on puddles where mosquito larvae are likely to be present, thereby reducing the number of workers, labor, and amount of insecticide used. Furthermore, for example, by identifying puddles unlikely to be home to mosquito larvae, a limited number of workers can avoid spraying insecticide on puddles unlikely to be home to mosquitoes, thereby reducing the number of workers, labor, and amount of insecticide used.

[0017] According to one embodiment of the present invention, the flying object is preferably a multicopter drone. According to one embodiment of the present invention configured as described above, the flying object is a multicopter drone, which makes it easy to hover vertically above a puddle (at the same latitude and longitude position), thereby improving the accuracy of obtaining the spread of scattered light in the puddle of laser light irradiated from the flying object onto the puddle. Also, because the flying object is a multicopter drone, adjusting the altitude above a puddle at a predetermined position (a predetermined latitude and longitude position) is relatively easy compared to adjusting the altitude of a fixed-wing drone.

[0018] According to one embodiment of the present invention, it is preferable to further include an altitude sensor which is an altitude measurement device for measuring the flight altitude of the flying object. According to one embodiment of the present invention, the mosquito breeding control system further includes an altitude sensor, which is an altitude measurement device that measures the flight altitude of the flying object. This allows the mosquito breeding control system to recognize the altitude of the flying object when the image is captured by the camera, and to more accurately recognize the extent of the spread of scattered light based on the altitude of the flying object.

[0019] According to one embodiment of the present invention, the flying object preferably further comprises a GPS mounted thereon. According to one embodiment of the present invention, the mosquito breeding control system further includes a GPS mounted on the air vehicle. This allows the air vehicle of the mosquito breeding control system to autonomously fly above a puddle at a predetermined location and automatically return to the base after measuring the turbidity of the puddle or acquiring an image. Therefore, the mosquito breeding control system can function as a turbidity information collection system that operates an air vehicle that automatically flies and collects turbidity information about puddles.

[0020] According to one embodiment of the present invention, the method for suppressing mosquito breeding preferably analyzes puddles that are likely to be inhabited by mosquito larvae based on images obtained from an aerial vehicle, and includes the steps of: acquiring the spread of scattered light in the puddle of laser light irradiated from the aerial vehicle onto the puddle in the images obtained from the aerial vehicle; and estimating the turbidity of the puddle based on the spread of scattered light. According to one embodiment of the present invention, the mosquito breeding control method includes an acquisition step of acquiring the spread of scattered light in a puddle of laser light irradiated from the airborne object onto the puddle in an image acquired from the airborne object, and a turbidity estimation step of estimating the turbidity of the puddle based on the spread of scattered light. This allows the turbidity of a puddle, a biologically important factor in analyzing puddles likely to be inhabited by mosquito larvae, to be estimated, and puddles likely to be inhabited by mosquito larvae can be efficiently identified based on the image acquired from the airborne object. Therefore, since puddles likely to be inhabited by mosquito larvae can be efficiently identified, a limited number of workers can spray insecticide on the identified puddles, thereby reducing the number of workers, labor, and amount of insecticide used. Furthermore, for example, by identifying puddles unlikely to be inhabited by mosquito larvae, a limited number of workers can avoid spraying insecticide on puddles unlikely to be inhabited by mosquitoes, thereby reducing the number of workers, labor, and amount of insecticide used. [Effects of the Invention]

[0021] The mosquito breeding suppression program, computer-readable recording medium on which the mosquito breeding suppression program is recorded, mosquito breeding suppression system, and mosquito breeding suppression method of the present invention make it possible to analyze puddles that are likely to be inhabited by mosquito larvae based on images obtained from flying objects. [Brief explanation of the drawings]

[0022] [Figure 1] 1 is a schematic diagram of a mosquito breeding control system equipped with a mosquito breeding control program according to one embodiment of the present invention; [Figure 2]FIG. 10 is a diagram showing the state of a puddle analyzed using the mosquito breeding control program according to one embodiment of the present invention. [Figure 3] 1 is a block diagram showing the configuration of a mosquito breeding control system according to one embodiment of the present invention. [Figure 4] 1 is a block diagram showing the configuration of an estimation device in a mosquito breeding control system according to one embodiment of the present invention. FIG. [Figure 5] 5 is a diagram showing the relationship between the estimation device and the mobile information terminal of the mosquito breeding control system of FIG. 4. [Figure 6] 1 is a block diagram showing the configuration of an estimation device in a mosquito breeding control system according to one embodiment of the present invention. FIG. [Figure 7] FIG. 10 is a diagram showing the mechanism of the altitude correction function that corrects and calculates the spread of scattered light in an image obtained from a flying object in one embodiment of the mosquito breeding control system of the present invention. [Figure 8] FIG. 2 illustrates a process flow chart for a mosquito breeding control system according to one embodiment of the present invention. [Figure 9] FIG. 10 is a diagram showing an example of displaying a puddle evaluated as being high risk in distinction from its surroundings in the mosquito breeding control system of one embodiment of the present invention. [Figure 10] FIG. 1 is a diagram showing an example of an experimental device used in an experiment to confirm the correlation between the turbidity of water and the diameter of scattered laser light. [Figure 11] FIG. 10 is a diagram showing the scattered light diameter of laser light when the turbidity of water is 0%. [Figure 12] FIG. 10 is a diagram showing the scattered light diameter of laser light when the turbidity of water is 5%. [Figure 13] FIG. 10 is a diagram showing the scattered light diameter of laser light when the turbidity of water is 10%. [Figure 14] FIG. 10 is a diagram showing the scattered light diameter of laser light when the turbidity of water is 25%. [Figure 15] FIG. 10 is a diagram showing the scattered light diameter of laser light when the turbidity of water is 50%. [Figure 16]FIG. 10 is a diagram showing the scattered light diameter of laser light when the turbidity of water is 75%. [Figure 17] FIG. 10 is a diagram showing the scattered light diameter of laser light when the turbidity of water is 100%. [Figure 18] FIG. 10 is a diagram showing the scattered light diameter of laser light obtained when the turbidity of water is changed. [Figure 19] FIG. 10 is a diagram showing the correlation between the turbidity of water and the diameter of scattered laser light obtained when the turbidity of water is changed. DETAILED DESCRIPTION OF THE INVENTION

[0023] The inventors of the present invention have been conducting research into how to efficiently search for puddles over a wide area and efficiently find puddles that are likely to be inhabited by mosquito larvae. In the course of their research, the inventors have discovered that mosquito larvae are likely to inhabit puddles with a predetermined turbidity (a predetermined turbidity range), but conversely, mosquito larvae are unlikely to inhabit puddles with turbidity outside the predetermined turbidity range (a predetermined turbidity range).

[0024] Based on this new finding, the inventors of the present invention conducted research to efficiently search for puddles over a wide area and efficiently identify puddles that are likely to be home to mosquito larvae. For example, if puddles with a predetermined turbidity (a predetermined turbidity range) can be efficiently identified, puddles that are likely to be home to mosquito larvae can be efficiently identified. A conventional method for measuring water turbidity is a transmission-type turbidity meter. However, this turbidity measurement method requires an investigator to actually go to the puddle location and collect water samples, or to collect and measure water on-site. Therefore, implementing this turbidity measurement method requires time and manpower, making it difficult to efficiently search for puddles over a wide area and efficiently identify puddles that are likely to be home to mosquito larvae.

[0025] To solve this problem, the inventors of the present invention have studied a technology for estimating the turbidity of a puddle using images obtained from a flying object. More specifically, the inventors of the present invention conducted extensive research and discovered a relationship between the scattered light diameter of laser light and the turbidity of the water in a puddle. When a laser light enters a puddle and hits a colloid in the water, the laser light is reflected by the colloid. Due to Huygens' principle and other factors, the laser light forms scattered light that spreads in an arc (spherical) shape from the colloid. When the turbidity of the water in a puddle is very low, the laser light hardly hits colloids in the water and is hardly scattered. In this case, almost no scattered light centered on the laser light is measured at the water surface. On the other hand, when the turbidity of the water in a puddle is relatively high, the laser light is more likely to hit colloids in the water, and scattered light centered on the laser light is observed at the water surface. In this case, the scattered light is measured as spreading in a circular shape centered on the laser light. The higher the turbidity and the greater the amount of colloids present in the water, the more scattered light the laser beam will be, as it is reflected by colloids near the water surface before being absorbed by the water, resulting in a larger scattered light diameter. Therefore, the inventors of the present invention discovered a correlation between the turbidity of a puddle and the scattered light diameter centered on the laser beam. The control device stores typical examples of the correlation between the turbidity of a puddle and the scattered light diameter. Therefore, it is possible to estimate the turbidity of a puddle based on the scattered light diameter. Note that the mud and soil components contained in puddles vary depending on the region, and the state of colloids in the water may vary, which may affect the correlation between turbidity and the scattered light diameter. By obtaining a puddle water sample in advance and measuring the correlation between the turbidity of the puddle and the scattered light diameter centered on the laser beam, it is possible to improve the accuracy of estimating the turbidity of a puddle based on the scattered light diameter. In this way, the inventors of the present invention have researched a technology for estimating the turbidity of puddles using images obtained from an aerial vehicle, and have made it possible to efficiently search for puddles over a wide area from an aerial vehicle and efficiently discover puddles that are likely to be inhabited by mosquito larvae.

[0026] Hereinafter, a mosquito breeding control system 1 including a computer that executes a mosquito breeding control program 2 (stored in the control device 7 of FIG. 3) according to one embodiment of the present invention will be described with reference to the accompanying drawings. The embodiments of the present disclosure have been described as examples, and it will be apparent to those skilled in the art that many variations, modifications, and substitutions can be made within the spirit and scope of the present invention. Therefore, the present invention is not limited to the disclosed embodiments, and various variations, modifications, etc. can be made in form and details without departing from the scope of the claims. Furthermore, the components disclosed in the specification can be freely combined.

[0027] As shown in FIG. 1 , a mosquito breeding control system 1 according to one embodiment of the present invention analyzes puddles 4 where mosquito larvae 3 (see FIG. 2 ) are likely to emerge (exist) and inhabit, based on images captured by an airborne object 6. The mosquito breeding control system 1 can estimate which puddles 4 are likely to be inhabited by larvae 3 by estimating the turbidity of the puddles 4. Conversely, for example, the mosquito breeding control system 1 can estimate which puddles 4 are unlikely to be inhabited by larvae 3 by estimating the turbidity of the puddles 4. The mosquito breeding control system 1 estimates which puddles 4 are likely to be inhabited by larvae 3 by estimating the turbidity of the puddles 4. The mosquito breeding control system 1 can also be used as a mosquito-borne infectious disease control system by estimating puddles 4 where mosquito larvae 3 emerge, and then administering an insecticide to the puddles using an airborne object or an operator, thereby effectively suppressing mosquito breeding. Similarly, the mosquito breeding control program is a mosquito-borne infectious disease control program, and the mosquito breeding control method described below is a mosquito-borne infectious disease control method.

[0028] FIG. 2 shows an example of a puddle 4 in which mosquito larvae 3 exist. The water surface 4a of the puddle 4 is indicated by a dashed line. The mosquito larvae 3 are hatched from eggs 3a in the puddle 4. The larvae 3 are so-called mosquito larvae. For example, when rain falls while the eggs are present, the larvae 3 develop into larvae approximately two to three days after the formation of the puddle 4. It is known that Anopheles eggs can withstand nine months of dryness and hatch into adult mosquito larvae after the formation of puddles due to rain, even during a long dry season. The larvae 3 develop into adult mosquitoes in the puddle 4 within approximately several days to one week. The mosquitoes are, for example, Anopheles species. Mosquitoes feed on human blood, and Anopheles species mosquitoes transmit, for example, the infectious disease malaria. Other types of mosquitoes transmit infectious diseases such as dengue fever, Japanese encephalitis, West Nile fever, and Zika virus infection, depending on the type of mosquito.

[0029] Puddles 4 are puddles that form on the ground G after rain, for example. They are formed when water accumulates on uneven or sloped areas of the ground G. The size of puddles 4 is not limited. Puddles 4 may be puddles after rain, puddles that accumulate in depressions, seepage puddles, ponds, swamps, reservoirs, rice paddies, water in depressions, water in irrigation ditches, lakes, etc. Puddles 4 include, for example, puddles measuring 30 cm x 30 cm and puddles measuring 200 cm x 200 cm. Puddles 4 include not only those that form short-term after rain, but also those that exist for long periods due to weather or climate. Depending on the target mosquito species, puddles 4 may not include places with constant flowing water, lakes or relatively large ponds (e.g., ponds 100 m x 100 m) that are home to other aquatic organisms that serve as predators for mosquito larvae and where it is difficult for larvae 3 to grow. Since Anopheles species mosquitoes prefer to breed in relatively small puddles 4, the puddle 4 may be a relatively small puddle, such as one that is smaller than 500 cm x 500 cm.

[0030] As shown in Figures 1 to 3, the mosquito breeding control system 1 includes a flying object 6 that flies above the ground, an irradiation device 8 that is mounted on the flying object 6 and emits laser light, a camera 10 that is mounted on the flying object 6 and acquires images, a GPS 9 that is mounted on the flying object 6, an altitude sensor 11 that is an altitude measuring device that measures the flight altitude of the flying object 6, and a control device 7 (mosquito breeding control device) that controls the flying object 6, the irradiation device 8, the camera 10, etc. and estimates the turbidity of the puddle 4.

[0031] The flying object 6 is a device that flies above the ground G by autonomous flight or remote control flight, and in this embodiment is a multicopter drone. The flying object 6 may be, for example, an unmanned aerial vehicle, a fixed-wing drone, an airship, or the like. Compared to fixed-wing drones, multicopter drones have the advantage of flying at heights ranging from approximately 1 meter to approximately 15 meters above the puddle 4 and tending to stay in a position in the sky generally directly above the puddle 4 (at the same latitude and longitude position). Multicopter drones also tend to stay in a position vertically above the puddle (at the same latitude and longitude position) compared to fixed-wing drones, making altitude adjustments at the same latitude and longitude position easier than with fixed-wing drones. Multicopter drones also have the advantage of being able to easily fine-tune their forward, backward, left, and right positions (horizontal position) compared to fixed-wing drones. Multicopter drones are also characterized by their relative ease of maintaining low altitudes of about 1 to 15 meters, and are cheaper and easier to fly than manned aircraft, helicopters, etc.

[0032] The irradiation device 8 is attached to the flying object 6 and configured to irradiate laser light downward. The irradiation device 8 is attached to the lower part of the flying object 6 so that the lens faces vertically downward. The irradiation device 8 is a laser light source device that irradiates laser light. The irradiation device 8 irradiates (oscillates), for example, laser light of an infrared wavelength. The wavelength of the laser light is, for example, within the range of 780 nm to 1700 nm, more preferably within the range of 950 nm to 1000 nm, for example, 980 nm. For example, infrared light has the property of being easily absorbed by water when it penetrates into water. For example, in an absorption spectrum where the horizontal axis represents wavelength and the vertical axis represents the extinction coefficient, water has absorption peaks that absorb infrared light with wavelengths around 970 nm and 1200 nm. For example, infrared light in a frequency band close to 980 nm has the property of being easily absorbed by water when it penetrates into water. The irradiation device 8 irradiates, for example, infrared light with a wavelength of 980 nm. The output of the irradiation device 8 is, for example, 500 mW. The diameter (light diameter) of the laser spot of the laser light is 0.5 mm. When the laser light from the irradiation device 8 hits the colloid 5 (colloid particles, for example, soil particles) in the puddle 4, it is reflected and generates scattered light A that spreads radially.

[0033] The camera 10 is attached to the flying object 6 and captures images of ground objects (such as puddles) from the sky. The camera 10 is attached to the bottom of the flying object 6 with its lens facing vertically downward. The camera 10 is a camera without an infrared filter and can capture scattered light of infrared wavelength laser light. In other words, the camera 10 can record infrared wavelength light as an image. Therefore, for example, the camera 10 is an infrared camera that can capture infrared wavelength light as an image. For example, the camera 10 is a trail camera 4K from COCOCAM. The camera 10 does not need to be an infrared camera with an infrared light, and may be an infrared camera without an infrared light, such as a night vision camera. In another variation, the camera 10 may be a camera with the ability to capture visible light images. The camera 10 may be capable of capturing not only still images but also videos. In addition to the camera 10 capable of capturing scattered light of infrared wavelength laser light, the flying object 6 may also be provided with a separate visible light camera capable of capturing visible light images of objects on the ground (e.g., puddles).

[0034] The GPS 9 shown in Figure 3 is a global positioning system, and indicates a satellite positioning system. The GPS 9 can measure and recognize position information such as latitude and longitude of the flying object 6. The GPS 9 is electrically connected to the control device 7, and transmits position information such as latitude and longitude of the flying object 6 to the control device 7. Furthermore, the GPS 9 allows the control device 7 to grasp the position of the flying object 6, such as latitude and longitude, and the flying object 6 can autonomously move up to the sky above the puddle 4 at a predetermined position, and after measuring the turbidity of the puddle 4 or acquiring an image, can automatically return to the base.

[0035] The altitude sensor 11 measures the flight altitude of the flying object 6. The altitude sensor 11 is, for example, a barometric pressure sensor, and measures the altitude of the drone by detecting changes in barometric pressure. Because the altitude sensor 11 monitors the altitude at which the camera 10 captures an image, the diameter of the scattered light in the captured image can be more accurately corrected. As will be described later, the mosquito breeding control program 2 can further execute an altitude correction function in the acquisition step, which calculates the spread of scattered light in the image obtained from the flying object 6 based on the flight altitude of the flying object 6 at the time the image was captured. Note that, based on the flight altitude measured by the altitude sensor 11 (or the altitude from the ground obtained by the flight altitude), the scale between the spread distance of the scattered light in the captured image and the actual spread distance can be calculated. Figure 7 explains the mechanism of the altitude correction function, which calculates the correct spread W of the scattered light in the image obtained from the flying object 6. As shown in Figure 7, for example, the scale can be reflected using the formula "f: distance from the center O of the camera lens to the shooting surface within the camera / H: flight altitude at the time of shooting = l: distance of the object in the captured image (distance recognized within the camera) / L: horizontal distance of the actual object photographed." This allows the diameter of the scattered light in the captured image to be accurately corrected based on the diameter of the actual scattered light. By controlling the flight altitude of the flying object 6 within a predetermined altitude range, the mosquito breeding control program 2 may execute a simple altitude correction function using a predetermined scale, or may omit the altitude sensor 11. Alternatively, the altitude may be estimated by another method, and a simple altitude correction function may be executed.

[0036] The control device 7 includes a functional unit that controls the flight of the flying object 6 and a functional unit that functions as the estimation device 12. For example, the functional unit of the control device 7 that controls the flight of the flying object 6 is provided on the flying object 6, and the functional unit of the control device 7 that functions as the estimation device 12 is provided in a computer on the ground. Note that the control device 7 may be configured such that the functional unit that controls the flight of the flying object 6 and the functional unit that functions as the estimation device 12 are integrated into one unit. Furthermore, some of these functional units may be provided on the cloud. For example, the functional units of the control device 7 may be executed by a program stored on the cloud.

[0037] The control device 7 controls the flying object 6, and remotely or autonomously controls the flight course, position, altitude, attitude, speed, etc. of the flying object 6. The control device 7 can also control the illumination device 8, camera 10, altitude sensor 11, GPS 9, etc. The flying object 6 can fly autonomously along a predetermined flight course unmanned under the control of the control device 7. The control device 7 recognizes the position (e.g., latitude and longitude) of the flying object 6 using the GPS 9 provided in the flying object 6. The control device 7 recognizes the flight altitude of the flying object 6 (e.g., the flight altitude at the time of photographing) using an altitude sensor provided in the flying object 6. The control device 7 is equipped with a storage device and a processor capable of executing flight control of the flying object 6.

[0038] The control device 7 functions as the estimation device 12, and acquires the spread W (diameter of the spread of scattered light) of the laser light irradiated from the flying object 6 onto the puddle 4 in the image acquired by the camera 10, and estimates the turbidity of the puddle 4 based on the spread W of the scattered light. The control device 7 is thus equipped with a mosquito breeding control program 2 that analyzes puddles 4 that are likely to be inhabited by mosquito larvae based on the image acquired from the flying object 6. The functional unit of the control device 7 as the estimation device 12 is configured, for example, by one or more servers that function as computers. The control device 7 does not have to be configured as a single server, and may be configured in whole or in part by another server located in a remote location via the Internet 32.

[0039] As shown in FIG. 4 , the control device 7 includes a storage device 16 and a processor 18. The control device 7 also functions as a control unit for a series of control processes. The storage device 16 is, for example, a volatile memory capable of high-speed reading and writing of information, and is used as a storage area and a working area when the processor 18 processes information. The storage device 16 may be a nonvolatile storage or nonvolatile memory, for example, a flash memory such as eMMC, UFS, or SSD. The storage device 16 stores programs and various data for executing the mosquito breeding control program of this embodiment. The storage device 16 constitutes a computer-readable tangible recording medium and stores the mosquito breeding control program 2. The processor 18 controls the operation of the control device. The processor 18 is, for example, a CPU. Note that the processor 18 may also be an electronic circuit such as an MPU. The processor 18 performs various processes by reading and executing programs and data stored in the control device. If the program of this embodiment is stored in another computer-readable recording medium, the processor 18 may execute instructions from the program in that recording medium. The computer-readable recording medium may be other recording media capable of storing data, such as a USB memory, an SD card, or a DVD. The control device 7 may be a tablet computer, a smartphone, other personal digital assistant devices, a smart watch, a wearable device, or other electronic devices. The control device 7 may include a communication device 20 for transmitting and receiving data to and from other devices, a display device 22 such as a display for displaying output results to the user, and an input device 23 for receiving input commands to the control device 7. The communication device 20 may be a device or module for wireless communication or a device or module for wired communication. The input device 23 is, for example, a keyboard or a mouse for receiving keyboard input. These components are connected by a bus 13. Note that an interface is provided between the bus 13 and each component device as needed.

[0040] As shown in FIG. 5, the control device 7 can communicate with a mobile information terminal 34 via the Internet 32, and information is transmitted between them. The mobile information terminal 34 is provided so that the worker spraying the insecticide can easily check the information. For example, each worker has a mobile information terminal 34 such as a smartphone. The mobile information terminal 34 can be configured as a smartphone, mobile phone, smartwatch, tablet PC, notebook PC, desktop PC, or the like. The mobile information terminal 34 has a display device 34a that forms a display screen. The display device 34a can be, for example, a monitor display, a display screen of a mobile information terminal, or a display screen of a smartphone. The control device 7 can output the output result in the output step S6 (see FIG. 8) on the display screen of the mobile information terminal 34. Therefore, in the output step S5, puddles 4 evaluated as high risk (or puddles evaluated as having a certain level of risk or higher) are displayed on the display screen of the mobile information terminal 34 of the worker spraying the insecticide, distinguishing them from other puddles. Such a mobile information terminal 34 may or may not be included in the mosquito breeding control system 1. A plurality of portable information terminals 34 can be provided for one control device 7. This allows many workers to simultaneously perform tasks such as spraying pesticides while checking information on their own portable information terminals 34. This makes the pesticide spraying process more efficient.

[0041] 6, the estimation device 12 of the control device 7 includes an acquisition step function unit 24 that executes an acquisition step S3 (see FIG. 8) based on the mosquito breeding inhibition program 2, a turbidity estimation step function unit 26 that executes a turbidity estimation step S4, an evaluation step function unit 28 that executes an evaluation step S5, and an output step function unit 30 that executes an output step S6. Therefore, the mosquito breeding inhibition program 2 stored in the storage device 16 of the control device 7 can cause a computer to execute the following steps: an acquisition step of acquiring the spread W of scattered light in the puddle 4 of laser light (e.g., infrared wavelength laser light) irradiated from the flying object 6 onto the puddle 4 in an image obtained from the flying object 6; a turbidity estimation step of estimating the turbidity of the puddle 4 based on the spread W of scattered light; an evaluation step of evaluating the risk of mosquito larvae inhabiting the puddle 4 based on the turbidity estimated in the turbidity estimation step; and an output step of distinguishing the puddle 4 evaluated as having a high risk in the evaluation step from other puddles on a display device in the image obtained from the flying object 6. Furthermore, in the acquisition step, the mosquito breeding suppression program 2 can further cause the computer to calculate the spread of scattered light in the image obtained from the flying object 6 based on the flight altitude of the flying object 6 at the time the image obtained from the flying object 6 was captured. The mosquito breeding suppression program 2 can also cause the computer to execute a function of selecting and displaying puddles 4 that are likely to be inhabited by mosquito larvae 3 from puddles in the image obtained from the flying object 6. Note that the estimation device 12 may have a preparation step function unit that executes a preparation step S1 (see FIG. 8) and / or an image acquisition step function unit that executes an image acquisition step S2 (see FIG. 8) based on the mosquito breeding suppression program 2.

[0042] The acquisition step function unit 24 has a function to cause the control device 7 as a computer to execute an acquisition step S3 (see FIG. 8 ) to acquire the spread W of scattered light in the puddle 4 of laser light (e.g., infrared wavelength laser light) irradiated from the flying object 6 onto the puddle 4 in the image acquired from the flying object 6. Therefore, the acquisition step function unit 24 has a function to detect the spread W of scattered light in the puddle 4 in the captured image. Such an acquisition step function unit 24 is configured as a part of the mosquito breeding control program 2.

[0043] The turbidity estimation step function unit 26 has a function of causing the control device 7 as a computer to execute a turbidity estimation step S4 of estimating the turbidity of the puddle 4 based on the spread W of scattered light. Such a turbidity estimation step function unit 26 is configured as a part of the mosquito breeding control program 2.

[0044] The evaluation step function unit 28 has the function of causing the control device 7 as a computer to execute an evaluation step S5 of evaluating the risk of mosquito larvae living in the puddle 4 based on the turbidity estimated in the turbidity estimation step S4. The output step function unit 30 has a function of causing the control device 7 as a computer to execute an output step S6 in which the puddles 4 evaluated as high risk in the evaluation step S5 are displayed on the display device, distinguished from other puddles in the image obtained from the flying object 6. Such an evaluation step function unit 28 is configured as a part of the mosquito breeding control program 2.

[0045] Next, a series of operations relating to the mosquito breeding control system of this embodiment will be described with reference to FIG. In the preparation step S1 of the mosquito breeding control method, the control device 7 acquires information on the correlation between the turbidity of the puddle and the diameter of scattered light radiating from the laser beam. This information is obtained by previously measuring the scattered light diameter for the turbidity of the puddle 4 using the irradiation device 8 attached to the flying object 6. Specifically, similar to an experiment to confirm the correlation between the turbidity of water and the diameter of scattered light of laser light, as described below, the laser beam is irradiated onto water of different turbidities, and the diameter of scattered light of the laser beam is measured. The information on the correlation between the turbidity of the puddle 4 and the diameter of scattered light radiating from the laser beam is stored in the control device 7. For example, the correlation between the turbidity of the puddle and the diameter of scattered light radiating from the laser beam is shown in FIG. 19. Note that correlations obtained under similar conditions may also be used.

[0046] The control device 7 acquires information about the position of the target puddle 4, such as latitude and longitude. For example, the position of the puddle 4, such as latitude and longitude information, is acquired based on ground image data of an aerial image previously captured by another drone or the like. The control device 7 may cause a computer to execute a puddle position acquisition step, using the mosquito breeding control program, to acquire the position and size of the puddle in an image acquired from the flying object 6 or another flying object, or the control device 7 may acquire position information of the puddle that has already been analyzed. As a variant, the control device 7 may omit the step of acquiring such puddle position information, and instead, in the image acquisition step described below, the flying object may be guided to the puddle that is the target for turbidity estimation by remote control or the like. After executing the preparation step S1, the control device 7 proceeds to S2.

[0047] Next, in S2, the control device 7 executes an image acquisition step of acquiring, from the flying object 6, an image of the puddle 4 for estimating turbidity. Based on the position information of the puddle 4, the control device 7 causes the flying object 6 to take off from the base, fly up to the position of the puddle 4, acquire an image from the flying object 6, and then return the flying object 6 to the base. Such a flight is executed autonomously by the control device 7. Position information for a plurality of puddles 4 may be set within one flight course, and the control device 7 may cause the flying object 6 to continuously acquire images for estimating turbidity for each of the plurality of puddles 4. Note that such a flight may also be executed by remotely controlling the flight by an operator. After executing the image acquisition step S2, the control device 7 proceeds to the next step S3.

[0048] d2 includes a measurement step in which the control device 7 causes the flying object 6 to acquire an image. In the measurement step, the control device 7 positions (hovers) the flying object 6 vertically above the puddle 4 to be measured. The control device 7 also maintains the flying object 6 at a flight altitude within a predetermined range, for example, a flight altitude between 1 m and 15 m, or, for example, a flight altitude of 5 m above the ground. Next, the control device 7 causes the illumination device 8 to irradiate the puddle 4 with infrared laser light. At this time, the control device 7 controls the attitude, etc., of the flying object 6 so that the infrared laser light is incident on the water surface of the puddle 4 at a substantially right angle. The control device 7 also captures an image of the puddle using the camera 10 in conjunction with the illumination by the illumination device 8. The control device 7 acquires a still image of the puddle using a camera, for example, an infrared camera. After acquiring the image of the puddle 4, the control device 7 ends the measurement step and returns the flying object 6 to the base. The control device 7 may transmit the acquired image of the puddle 4 to another computer on the ground (for example, a computer or server constituting the estimation device 12) and execute the acquisition step S3 etc. regardless of whether the flying object 6 has returned.

[0049] In S3, the control device 7 executes an acquisition step of acquiring the spread of scattered light in the puddle 4 of laser light (e.g., infrared wavelength laser light) irradiated from the flying object 6 to the puddle in S2, in the image acquired from the flying object 6. The control device 7 analyzes the spread of scattered light in the puddle 4 of the laser light (e.g., infrared wavelength laser light) in the image acquired from the flying object 6 in S2. Specifically, the control device 7 measures the scattered light diameter (indicated by W in FIG. 2) of the scattered light in the image. When analyzing and measuring the scattered light diameter, the control device 7 may perform predetermined image processing so as to make it easier to distinguish the diameter of the scattered light. When infrared wavelength laser light is irradiated onto the puddle 4 and the puddle is photographed with the camera 10 that detects infrared wavelength light, the infrared wavelength laser light is basically absorbed by the water, and therefore the puddle area is displayed in black (a background color that does not indicate the detection of infrared light), in which the reflection of infrared light is not generally detected. On the other hand, scattered light reflected by colloids from the incident infrared wavelength laser light is displayed in a bright color (a color indicating the detection of infrared light) that stands out from the background color in the image. Therefore, the scattered light is displayed in contrast to the puddle portion, further improving the accuracy of measuring the scattered light diameter. In the puddle 4, soil particles are dispersed in the liquid, and these soil particles act as colloids and reflect the laser light. Note that the measurement of the scattered light diameter is not limited to using the characteristics of infrared light as described above. When analyzing and measuring the scattered light diameter, the diameter of the scattered light may also be determined by measuring the spread of the scattered laser light in a visible light image.

[0050] In the acquisition step S3, the mosquito breeding control program 2 may further calculate the spread W of scattered light in the image obtained from the flying object 6 based on the flight altitude of the flying object 6 at the time the image obtained from the flying object 6 was captured. That is, the control device 7 is equipped with an altitude correction function unit 33 that recognizes the flight altitude of the flying object 6 at the time the image obtained from the flying object 6 was captured using the altitude sensor 11 and executes an altitude correction function to correct and calculate the spread W of scattered light in the image obtained from the flying object 6 based on this flight altitude. The altitude correction function unit 33 allows the control device 7 to more accurately calculate the diameter of the actual scattered light from the diameter of the scattered light in the captured image. After executing the acquisition step S3, the control device 7 proceeds to the next step S4.

[0051] In S4, the control device 7 executes a turbidity estimation step in which the turbidity of the puddle 4 is estimated based on the spread W of the scattered light. The control device 7 previously stores information on the correlation between the turbidity of the puddle 4 (turbidity [%]) and the scattered light diameter (diameter [mm]) centered on the laser beam, as shown in FIG. 19 . The control device 7 can estimate the turbidity of the puddle 4 by comparing the spread of the scattered light (scattered light diameter) in the image obtained from the flying object 6 with the correlation information. The control device 7 acquires the turbidity of the puddle 4 using the flying object 6 for each measured puddle 4. Therefore, the flying object 6 can fly above the puddle and measure the scattered light diameter, without the need for an operator to directly go to the puddle and collect water. Therefore, the turbidity of the puddle 4 can be estimated simply and quickly.

[0052] In S5, the control device 7 further causes the computer to execute an evaluation step of evaluating the risk of mosquito larvae inhabiting the puddle 4 based on the turbidity estimated in the turbidity estimation step S4. According to the evaluation step S5, the risk of the puddle 4 is evaluated based on the estimated turbidity, and the risk of the puddle can be communicated to the system user in an easy-to-understand manner. For example, if the turbidity of the puddle 4 is within a range of 5% to 50%, the control device 7 evaluates that the risk of mosquito larvae inhabiting the puddle 4 is relatively high. Also, for example, if the turbidity of the puddle 4 is lower than 5%, the control device 7 evaluates that the water is too clean to be inhabited by living organisms, and therefore the risk of mosquito larvae inhabiting the puddle 4 is relatively low. Also, for example, if the turbidity of the puddle 4 is higher than 50%, the control device 7 evaluates that the oxygen concentration in the water is low, making it inhabitable for living organisms, and therefore the risk of mosquito larvae inhabiting the puddle 4 is relatively low. The predetermined turbidity range in evaluation step S5 can be changed depending on the external environment, such as soil and climate, and the turbidity range in which mosquito larvae are likely to inhabit. For example, taking into consideration the external environment and the type and nature of mosquitoes, the control device 7 may evaluate that there is a relatively high risk of mosquito larvae inhabiting the puddle 4 when the turbidity of the puddle 4 is within a range of 5% to 60%, or may also evaluate that there is a relatively high risk of mosquito larvae inhabiting the puddle 4 when the turbidity of the puddle 4 is within a range of 10% to 40%.

[0053] In S6, as shown in FIG. 8 and other figures, the control device 7 executes an output step S6 in which puddles 4 evaluated as high risk in the evaluation step S5 are displayed on the display device 34a of the mobile information terminal 34, distinguishing them from other puddles (e.g., puddles 4 evaluated as low risk or puddles 4 not evaluated as high risk) in the image obtained from the flying object 6. A map display function for puddles 4 is realized in the output step S6. In FIG. 9, among the detected puddles 4, puddles 4 evaluated as high risk or having a certain level of risk or higher are highlighted by being surrounded by a dashed line (roughly surrounded by a circle). Note that puddles 4 evaluated as low risk may also be displayed. In this way, the control device 7 has a function of highlighting puddles 4 evaluated as high risk because their risk evaluation value or evaluation is above a certain level so that they can be distinguished on a predetermined image. The predetermined image is, for example, an image obtained from the flying object 6 or an image based on the obtained image. The control device 7 can operate application software to realize each of these functions on the application software. For example, the control device 7 may implement a map display function of the puddles 4 in application software that runs on the mobile information terminal 34.

[0054] As shown in Fig. 9, the control device 7 highlights a specific puddle 4 on the image, making it easier for the person spraying the pesticide to recognize the puddle 4 to which the pesticide should be sprayed. Also, by displaying a dashed line D (see Fig. 9) that surrounds the puddle 4, the location of the puddle 4 in the image can be made easier to see. Furthermore, the control device 7 has a function to display on the image puddles 4 with a risk assessment value or assessment above a certain level, together with the current location of the worker (the location of the mobile information terminal 34). This makes it easier for the worker F spraying the pesticide to decide what route to take to spray the puddles 4 in the future.

[0055] Furthermore, the control device 7, in output step S6, produces a display as shown in FIG. 9. For example, the periphery of the puddle 4 is highlighted with a dashed line, as shown by dashed line D. This allows the worker spraying the pesticide to easily identify the puddle that is the target of the spraying work. This also makes it easier for the worker to decide which route to take to spray the puddle 4. Furthermore, because the puddle 4 is displayed on a map based on an actual image, the worker can use surrounding trees, stones, paths, etc. as landmarks, allowing the work to proceed efficiently. Furthermore, because the puddle 4 is displayed on a map based on an actual image in a way that makes it easy to distinguish it from surrounding objects, the position of the puddle 4 can be easily recognized, and the worker can recognize it in advance by looking at the image. Furthermore, a direction is displayed on the screen (see FIG. 1), helping the worker find the puddle. Furthermore, the map output in output step S6 can be attached to a report after the pesticide spraying work, etc., has been completed. Furthermore, if necessary, each puddle 4 may be individually assigned an identification index (index), allowing for management of the puddles 4 and information registration (such as information on whether pests have been killed). Because the puddles 4 are individually recognized by the control device 7, a report indicating the completion of work can be created for each puddle. Therefore, workers can submit the puddle information on the map along with photographs of the spraying evidence and receive payment. In this way, a map with puddle information allows evidence and records of work to be kept, and can be used as a fair report. After executing the output step S6, the control device 7 proceeds to END and ends the series of control processes.

[0056] According to one embodiment of the present invention configured as described above, the mosquito breeding control program 2 can cause a computer to execute a turbidity estimation step S4, which estimates the turbidity of the puddle 4 based on the spread W of scattered light acquired in the acquisition step S3. This allows the turbidity of the puddle 4, a biologically important factor in analyzing puddles 4 likely to be inhabited by mosquito larvae, to be estimated, and puddles 4 likely to be inhabited by mosquito larvae can be efficiently identified based on images acquired from the flying object 6. Therefore, since puddles 4 likely to be inhabited by mosquito larvae can be efficiently identified, a limited number of workers can spray insecticide on the identified puddles 4, thereby reducing the number of workers, labor, and amount of insecticide used. Furthermore, for example, by being able to identify puddles 4 unlikely to be inhabited by mosquito larvae, a limited number of workers can avoid spraying insecticide on puddles 4 unlikely to be inhabited by mosquitoes, thereby reducing the number of workers, labor, and amount of insecticide used.

[0057] According to one embodiment of the present invention configured as described above, infrared laser light is easily absorbed by water, making it easier to distinguish between scattered light resulting from infrared laser light reflected by colloids 5 in the water and regions of water where infrared laser light is absorbed. This improves the accuracy of measuring the spread W of scattered light A, and also improves the accuracy of turbidity estimation. Furthermore, by using a camera 10 capable of detecting infrared light and an infrared laser from the irradiation device 8, each device is readily available, allowing the system to be constructed relatively easily and inexpensively.

[0058] According to one embodiment of the present invention configured in this manner, the wavelength of the laser light is within the range of 950 nm to 1000 nm, making it easier to build a system using a camera 10 that can detect light of infrared wavelengths and an infrared laser from an irradiation device 8.

[0059] According to one embodiment of the present invention configured as described above, the acquisition step S3 of the mosquito breeding control program 2 calculates the spread W of scattered light in the image obtained from the flying object 6 based on the flight altitude of the flying object 6 at the time the image obtained from the flying object 6 was captured. This allows the mosquito breeding control program 2 to more accurately recognize the size of the spread W of scattered light based on the altitude of the flying object 6.

[0060] According to one embodiment of the present invention configured as described above, the mosquito breeding control program 2 can execute an evaluation step S5 in which a computer evaluates the risk of mosquito larvae inhabiting the puddles 4 based on the turbidity estimated in the turbidity estimation step S4. This allows the risk of mosquito larvae inhabiting each puddle 4 to be evaluated, and a limited number of workers can preferentially spray insecticide on puddles 4 with a high risk, thereby further reducing the number of workers, labor, and amount of insecticide used.

[0061] According to one embodiment of the present invention configured as described above, the mosquito breeding control program 2 can execute an output step S6 in which the computer displays, on a display device, puddles 4 evaluated as high risk in the evaluation step S5, distinguished from other puddles 4 in the image obtained from the flying object 6. This makes it easier for an operator spraying puddles 4 to know which puddles 4 to spray with the insecticide, thereby increasing the speed and efficiency of the operator's spraying work.

[0062] According to one embodiment of the present invention configured in this manner, a computer-readable recording medium having the above-described mosquito breeding suppression program 2 recorded thereon can be used to cause a computer to execute predetermined steps, thereby efficiently detecting puddles 4 that are likely to be inhabited by mosquito larvae.

[0063] According to one embodiment of the present invention, the estimation device of the mosquito breeding control system configured as described above can acquire the spread W of scattered light in the puddle 4 of laser light irradiated from the flying object 6 onto the puddle 4 in an image acquired by the camera 10, and estimate the turbidity of the puddle 4 based on the spread W of scattered light. This allows the turbidity of the puddle 4, which is a biologically important factor in analyzing puddles 4 that are likely to be inhabited by mosquito larvae, to be estimated, and puddles 4 that are likely to be inhabited by mosquito larvae can be efficiently identified based on the image acquired from the flying object 6. Therefore, since puddles 4 that are likely to be inhabited by mosquito larvae can be efficiently identified, a limited number of workers can spray insecticide on the identified puddles, thereby reducing the number of workers, labor, and amount of insecticide used. Furthermore, for example, by being able to identify puddles 4 that are unlikely to be inhabited by mosquito larvae, a limited number of workers can avoid spraying insecticide on puddles 4 that are unlikely to be inhabited by mosquitoes, thereby reducing the number of workers, labor, and amount of insecticide used.

[0064] According to one embodiment of the present invention configured in this manner, the flying object 6 is a multicopter drone, and therefore is likely to hover vertically above the puddle 4 (at the same latitude and longitude position), improving the accuracy of obtaining the spread W of scattered light in the puddle 4 of laser light irradiated from the flying object 6 onto the puddle 4. Furthermore, because the flying object 6 is a multicopter drone, adjusting the altitude above the puddle 4 at a predetermined position (a predetermined latitude and longitude position) is relatively easy compared to adjusting the altitude of a fixed-wing drone.

[0065] According to one embodiment of the present invention configured as described above, the mosquito breeding control system 1 further includes an altitude sensor 11, which is an altitude measurement device that measures the flight altitude of the flying object 6. This allows the mosquito breeding control system 1 to recognize the altitude of the flying object 6 when the image is captured by the camera 10, and to more accurately recognize the size of the spread W of the scattered light based on the altitude of the flying object 6.

[0066] According to one embodiment of the present invention configured as described above, the mosquito breeding control system 1 further includes a GPS 9 mounted on the flying object 6. This allows the flying object 6 of the mosquito breeding control system 1 to autonomously fly above the puddle 4 at a predetermined location, and after measuring the turbidity of the puddle 4 or acquiring an image, automatically return to the base. Therefore, the mosquito breeding control system 1 can function as a turbidity information collection system that operates the flying object 6 to automatically fly and collect turbidity information of the puddle 4.

[0067] According to one embodiment of the present invention configured as described above, the mosquito breeding control method includes an acquisition step S3 for acquiring the spread W of scattered light in the puddle 4 of laser light irradiated from the flying object 6 onto the puddle 4 in an image acquired from the flying object 6, and a turbidity estimation step S4 for estimating the turbidity of the puddle 4 based on the spread W of scattered light. This makes it possible to estimate the turbidity of the puddle 4, which is a biologically important factor in analyzing puddles 4 that are likely to be inhabited by mosquito larvae, and to efficiently find puddles 4 that are likely to be inhabited by mosquito larvae based on the image acquired from the flying object 6. Therefore, since puddles 4 that are likely to be inhabited by mosquito larvae can be efficiently found, a limited number of workers can spray insecticide on the found puddles 4, thereby reducing the number of workers, labor, and amount of insecticide used. Furthermore, for example, by being able to identify puddles 4 that are unlikely to be inhabited by mosquito larvae, a limited number of workers can avoid spraying insecticide on puddles 4 where mosquitoes are unlikely to breed, thereby reducing the number of workers, labor, and amount of insecticide used.

[0068] The inventors of the present invention conducted the following experiment to confirm the correlation and principle between the turbidity of water and the diameter of scattered laser light. As shown in Figure 10, the experimental apparatus comprises a camera 10 mounted on top of a tripod and an illumination device 8 mounted below the camera 10. The camera 10 is positioned above a container 40 containing a liquid sample to be measured. A one-liter graduated cylinder was used as the container 40 for storing the liquid sample. The container 40 has a predetermined depth so as not to affect the measurement. The amount of liquid is 1 liter, and the water depth is constant.

[0069] A COCOCAM trail camera 4K was used as the camera 10. The camera 10 is capable of capturing images including infrared light. The lens of the camera 10 is pointed vertically downward into the container. The irradiation device 8 is an infrared laser that irradiates (oscillates) laser light with an infrared wavelength. The infrared laser light from the irradiation device 8 was irradiated perpendicularly to the water surface of the liquid sample. The wavelength of the laser light was 980 nm.

[0070] The experimental procedure was as follows: 1. to 3. 1. For the experiment, Megmilk Snow Brand's "Snow Brand Coffee" (registered trademark) was used as a liquid sample with 100% turbidity. The commercially available liquid of this coffee was used as the liquid with 100% turbidity, and liquids with different turbidities were prepared by diluting the "Snow Brand Coffee" with water to relatively change the concentration. For example, the liquid samples to be measured were liquid samples with turbidities of 5%, 10%, 25%, 50%, 75%, and 100%. The volume of the liquid was 1 liter, and the water depth was constant. In African countries that are implementing so-called mosquito larvae source management (LSM), puddles 4 often contain very fine soil particles, and puddles 4 in which soil particles remain mobile within the water for a very long period of time are often observed. Therefore, Megmilk Snow Brand's "Snow Brand Coffee" (registered trademark), which has a color and state similar to that of such puddles 4, was used as a simulated liquid sample for the experiment. 2. An infrared laser beam was irradiated perpendicularly onto the water surface of the liquid sample from the irradiation device 8, and an image of the water surface and the scattered light on the water surface was captured by the camera 10. 3. The diameter of the scattered infrared light appearing on the water surface in the acquired images was measured on the images. The diameter of the scattered infrared light was measured on the images for each liquid sample with varying turbidity (5%, 10%, 25%, 50%, 75%, and 100%). The correlation between the scattered light diameter obtained through such measurements and turbidity was confirmed. For example, at 100% turbidity, the diameter of the scattered light (diameter [mm]) was 16.03 mm. The diameter of the laser spot of the laser light was 0.05 mm.

[0071] As shown in Figures 11 to 17, the diameter of scattered light was measured when the turbidity of the liquid sample was changed to 5%, 10%, 25%, 50%, 75%, and 100%. As shown in Figure 11, when the turbidity was 0%, diffuse reflection of infrared light by colloids was not observed, and scattered light was not measured. Therefore, it was confirmed that the scattered light due to infrared reflection observed at turbidity levels between 5% and 100% was caused by colloid particles in the water (the effect of turbidity). In Figures 12 to 17, the scattered light appears as a white glow on the water surface. As shown in Figures 12 to 17 and 18, the diameter of the scattered light measured increased with increasing turbidity. The measurement results of the scattered light diameter as a function of turbidity are shown in Figures 18 and 19.

[0072] In Figure 18, the left column shows the turbidity (%) of puddle 4, and the right column shows the measured diameter (mm) of scattered light. In Figure 19, the vertical axis shows the diameter (mm) of scattered light, and the horizontal axis shows the turbidity (%) of puddle 4. Therefore, it can be seen that when the turbidity of the liquid sample changes from 0% to 5%, the diameter (mm) of scattered light increases rapidly. It can also be seen that when the turbidity of the liquid sample changes from 5% to 100%, the diameter (mm) of scattered light increases at a roughly constant rate. Therefore, it can be seen that if the diameter (mm) of scattered light is measured from 5% to 100% of turbidity, the corresponding turbidity (%) can be estimated.

[0073] The embodiments of the present invention are not limited to those described above, and other modifications may be applied. Various alternative embodiments and examples will be apparent to those skilled in the art based on the disclosed technology. The components of the mosquito breeding suppression program 2 can be freely rearranged to configure the mosquito breeding suppression program 2. The computer-readable recording medium can be configured to include the mosquito breeding suppression program 2 with the components freely rearranged. It is expressly stated that the computer-readable recording medium, mosquito breeding suppression system, and mosquito breeding suppression method may each be configured as a modification including various variations of the components of the mosquito breeding suppression program 2.

[0074] The technology of this embodiment can be applied to the analysis of puddles 4 that are likely to be inhabited by various mosquito larvae. Therefore, the technology of this embodiment will be specifically described to include the following example: The turbidity and other conditions of the puddles 4 that mosquitoes prefer may differ depending on the type of mosquito. The technology of this embodiment can also be applied, for example, to the analysis of puddles 4 that are likely to be inhabited by Culex tritaeniorhynchus larvae. Culex tritaeniorhynchus may transmit Japanese encephalitis. Culex tritaeniorhynchus larvae 3 prefer to inhabit relatively large puddles 4 formed in rice paddies, depressions, irrigation ditches, ponds, swamps, etc. For example, Culex tritaeniorhynchus larvae 3 can inhabit puddles 4 that are larger than those inhabited by Anopheles larvae 3 and that have a current within the puddle 4. Therefore, in the analysis of puddles 4 that are likely to be inhabited by Culex tritaeniorhynchus larvae, for example, if the turbidity of the puddle is within a predetermined range (e.g., a turbidity within a range preferred by Culex tritaeniorhynchus larvae), the control device 7 may evaluate the puddle 4 as having a high risk of inhabiting the larvae 3.

[0075] As another example, the technology of this embodiment can also be applied to the analysis of puddles 4 that are likely to be inhabited by larvae of Aedes aegypti or Aedes albopictus. Aedes aegypti or Aedes albopictus may transmit dengue fever. Larvae 3 of Aedes aegypti or Aedes albopictus prefer to inhabit not only small puddles 4 formed on the ground but also extremely small puddles 4 formed in depressions in everyday objects such as water bottles, flower vases, empty cans, old tires, tree stumps, and blue tarps. In the analysis of puddles 4 that are likely to be inhabited by larvae of Aedes aegypti or Aedes albopictus, for example, the control device 7 may evaluate the puddle 4 as having a high risk of inhabiting the larvae 3 if the turbidity of the puddle is within a predetermined range (e.g., a turbidity range preferred by Aedes aegypti larvae). In this way, the technology of this embodiment can estimate the turbidity of puddles that mosquitoes like to collect for other mosquito-borne infectious diseases and analyze the puddles that mosquitoes like to collect. [Explanation of symbols]

[0076] 1: Mosquito breeding control system 2: Mosquito breeding control program 3: Larva 6: Flying object 8: Irradiation device 9: GPS 10: Camera 11: Altitude sensor 12: Estimation device 22:Display device 34a:Display device A:Scattered light G: Ground S3: Acquisition step S4: Turbidity estimation step S5: Evaluation step S6: Output step W: Spread

Claims

1. A mosquito breeding control program that analyzes puddles where mosquito larvae are likely to live based on images obtained from a flying object, the program comprising: an acquiring step of acquiring a spread of scattered light in a puddle of laser light irradiated from the flying object onto the puddle in an image acquired from the flying object; a turbidity estimation step of estimating the turbidity of the puddle based on the spread of the scattered light.

2. The mosquito breeding control program of claim 1, wherein the acquisition step of the mosquito breeding control program acquires the spread of scattered light in a puddle of infrared wavelength laser light irradiated from the flying object onto the puddle in an image obtained from the flying object.

3. 3. The mosquito breeding control program according to claim 2, wherein the wavelength of the laser light is within a range of 950 nm to 1000 nm.

4. The mosquito breeding control program of claim 1, wherein the acquisition step of the mosquito breeding control program further calculates the spread of the scattered light in the image obtained from the flying object based on the flight altitude of the flying object at the time the image obtained from the flying object was taken.

5. The mosquito breeding control program of claim 1, further causing the computer to execute an evaluation step of evaluating the risk of mosquito larvae inhabiting the puddle based on the turbidity estimated by the turbidity estimation step.

6. The mosquito breeding control program of claim 5, further comprising an output step of displaying puddles evaluated as high risk by the evaluation step on a display device, distinguishing them from other puddles in an image obtained from the flying object.

7. A computer-readable recording medium on which the mosquito breeding control program according to any one of claims 1 to 6 is recorded.

8. A mosquito breeding control system that analyzes puddles where mosquito larvae are likely to live based on images obtained from a flying object, the flying object flying above the ground; an irradiation device that is provided on the flying object and irradiates the flying object with laser light; a camera provided on the flying object to acquire images; A mosquito breeding control system comprising: an estimation device that acquires the spread of scattered light in a puddle of laser light irradiated from the flying object onto the puddle in an image acquired by the camera, and estimates the turbidity of the puddle based on the spread of scattered light.

9. The mosquito breeding control system according to claim 8 , wherein the flying object is a multicopter drone.

10. The mosquito breeding control system according to claim 8, further comprising an altitude sensor which is an altitude measuring device for measuring the flight altitude of the flying object.

11. The mosquito breeding control system according to claim 8 , further comprising a GPS mounted on the flying object.

12. A mosquito breeding control method that analyzes puddles where mosquito larvae are likely to live based on images obtained from a flying object, an acquiring step of acquiring a spread of scattered light in a puddle of laser light irradiated from the flying object onto the puddle in an image acquired from the flying object; A turbidity estimation step of estimating the turbidity of the puddle based on the spread of the scattered light.

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