JP7359429B2 - Red tide inspection system and red tide inspection method - Google Patents

Description

Application of Article 30, Paragraph 2 of the Patent Act ・Published on December 13, 2018 “Collection of Proceedings of the 19th Society of Instrument and Control Engineers (SICE) System Integration Division Lecture (pages 3058 to 3059)” ・2018 Presented at the Osaka Institute of Technology on December 15th at the 19th Society of Instrument and Control Engineers (SICE) System Integration Division Lecture ・January 22nd, 2019 Published on the Jatsu Complex NEXT MOBILITY website https: //www. nextmobility. jp/new_technology/four-nagasaki-university-et-al-a-demonstration-experiment-to-convert-nagasaki-prefecture-%C2%B7-goto- island-to-tuna-farming-base-at-iot20190122/ ・Broadcast on NHK "Evening Nagasaki" on January 22, 2019 - Broadcast on TV Nagasaki (NTK) Prime News on January 22, 2019 - Broadcast on Nagasaki Cultural Broadcasting Super J Channel on January 22, 2019・Published on the KDDI Corporation website on January 22, 2019 https://news. kddi. com/kddi/corporate/newsrelease/2019/01/22/3566. html ・Posted on KDDI Corporation's Mobile Watch site on January 22, 2019 https://k-tai. watch. impression. co. jp/docs/news/1165681. html ・Published in the Nagasaki Shimbun on January 23, 2019 ・Published in the Yomiuri Shimbun on January 23, 2019 ・Broadcast on Nagasaki Broadcasting System (NBC) “N Star” on January 23, 2019 ・January 2019 Broadcast on Nagasaki International Broadcasting (NIB) NNN Straight News on January 26th ・Published in Nishinippon Shimbun on January 27th, 2019 ・Published on Nishinippon Shimbun website on January 27th, 2019 https://www. Nishinippon. co. jp/item/n/482264/ ・Published in Nikkei Business Electronic Edition in June 2020 https://special. nikkeibp. co. jp/atclh/ONB/19/5G_IMPACT/summit09_2/

Application of Article 30, Paragraph 2 of the Patent Act - Posted on the Nagasaki University Yamamoto Research Institute website on June 7, 2020 http://robotics. mech. nagasaki-u. ac. jp/ - Announced at the KDDI 5G SUMMIT 2019 lecture on June 27, 2020 - Published on the Sensor and Materials website on August 6, 2020 https://myukk. org/SM2017/article. php? ss=2417

The present invention relates to a red tide inspection system and a red tide inspection method for determining the occurrence of red tide.

Early detection of red tide is an important issue in aquaculture operations in the fisheries industry. In particular, bluefin tuna is a fish species that is more susceptible to the effects of red tide than other fish species, so early detection of red tide is necessary. There are also reports that bluefin tuna die when the density of plankton, which causes red tide, is about 1/10th that of other fish species.

However, early detection of red tide is difficult with existing chlorophyll measurements carried out by ships navigating to fish farms.

On the other hand, a water sample detection method has been proposed in which a water sample is detected using an unmanned flying vehicle called a drone (for example, see Patent Document 1).

Patent No. 6340433

An object of the present invention is to provide a red tide inspection system and a red tide inspection method that use an unmanned flying vehicle to determine harmful red tide from seawater sampling and determine the harmful red tide discrimination results in a short time. .

In order to solve the above-mentioned problems, the present invention uses an unmanned flying vehicle equipped with a water sampling device to sample seawater, and detects plankton, which is a cause of red tide, from images taken with a microscope of the seawater sampled by the unmanned flying vehicle. This is a red tide inspection system comprising an information processing device that determines the type of plankton, counts the number of individuals of each type of plankton, determines harmful red tide, and displays the counting results for each type of plankton and the results of determining harmful red tide. .

The present invention also provides a step of photographing the sea surface with an unmanned flying vehicle, a step of selecting a seawater sampling point from an image of the sea surface taken by the unmanned flying vehicle, and a step of selecting an unmanned flying vehicle having a water sampling device. The process involved flying to designated water sampling points and collecting seawater at the sampling points, photographing the sampled seawater with a microscope, and identifying the types of plankton that cause red tide from the images taken with the microscope. This is a red tide inspection method that executes the steps of identifying harmful red tide by determining the number of individuals of each type of plankton, and displaying the harmful red tide determination result.

In the present invention, seawater can be sampled and analyzed in a short time, and the harmful red tide determination results can be displayed, so that when red tide occurs or when red tide is predicted to occur, measures can be taken quickly.

FIG. 1 is a functional block diagram showing an example of a red tide inspection system according to the present embodiment. FIG. 2 is a functional block diagram showing an example of an unmanned flying vehicle for seawater recovery. FIG. 1 is a configuration diagram showing an example of an unmanned flying vehicle for seawater recovery. FIG. 1 is a configuration diagram showing an example of an unmanned flying vehicle for seawater recovery. It is a flowchart which shows an example of operation of the red tide inspection system of this embodiment. It is an explanatory diagram showing an example of red tide occurrence information displayed on an information processing device.

DESCRIPTION OF EMBODIMENTS Hereinafter, embodiments of a red tide inspection system and a red tide inspection method of the present invention will be described with reference to the drawings.

<Configuration example of red tide inspection system of this embodiment>
FIG. 1 is a functional block diagram showing an example of a red tide inspection system 1 according to the present embodiment.

The red tide inspection system 1 of this embodiment is based on an unmanned flying vehicle 2A for collecting seawater, an unmanned flying vehicle 2B for photographing the sea surface, etc., and the number of plankton contained in the seawater collected by the unmanned flying vehicle 2A. It is equipped with an information processing device 4 that performs discrimination, display, etc. of harmful red tide.

FIG. 2 is a functional block diagram showing an example of an unmanned flying vehicle 2A for seawater recovery, and FIGS. 3A and 3B are configuration diagrams showing an example of the unmanned flying vehicle 2A for seawater recovery.

In this example, the unmanned aerial vehicle 2A includes four rotors 20A, a plurality of motors 21A that independently drive each rotor 20A, and a plurality of speed controllers (ESC: Electric speed controllers) that independently control each motor 21A. )22A.

The unmanned flying vehicle 2A also includes a camera 23A that photographs the surroundings of the aircraft, and a gimbal mechanism 24A that controls the attitude of the camera 22A.

Furthermore, the unmanned aerial vehicle 2A includes a water sampling device 25A that samples seawater. The water sampling device 25A includes a water sampling container 250A that is a water sampling device for sampling seawater, a wire 251A that suspends the water sampling container 250A, and a servo motor 252A that rotates a pulley (not shown) around which the wire 251A is wound. .

The water sampling device 25A includes a plurality of water sampling containers 250A, three water sampling containers 250A in this example, in order to be able to sample seawater at different depths or different points in one flight. Each water sampling container 250A is provided with a servo motor 252A that rotates a wire 251A and a pulley around which the wire 251A is wound, so that each water sampling container 250A can be raised and lowered independently. Note that the water sampling container 250A is equipped with a lid (not shown) that can be opened and closed according to water pressure, and the lid remains closed until a predetermined water pressure is applied at sea or in the sea, and the lid remains closed until a predetermined water pressure is applied underwater. The lid may be opened to allow seawater to be sampled. In addition, in order to be able to sample seawater at different depths in a single flight, the timing of opening and closing the lids of multiple water sampling containers 250A can be adjusted using springs, so that when a predetermined pressure depending on the depth is applied, the lids open and close. may be opened.

Moreover, the unmanned flying object 2A is equipped with a camera 26A that mainly photographs the water landing location of the water sampling container 250A.

Furthermore, the unmanned aerial vehicle 2A includes a flight controller 27A. The flight controller 27A includes a computer, a gyro sensor, an acceleration sensor, a GPS, etc., and controls each speed controller 22A, camera 23A, gimbal 24A, servo motor 252A, and camera 26A.

In addition, the unmanned aerial vehicle 2A receives control signals for flying the unmanned aerial vehicle 2A, control signals for controlling the cameras 23A and 26A, control signals for controlling the water sampling device 25A, etc., and also receives images taken by the cameras 23A and 26A. It is equipped with a transceiver 28A that transmits image signals and the like.

The unmanned aerial vehicle 2A is operated by a remote control device 3A. The remote control device 3A includes an operating section 30A that is operated by a person. The operation unit 30A performs operations such as flying the unmanned flying object 2A, taking pictures with the cameras 23A and 26A, and raising and lowering the water sampling container 250A with the water sampling device 25A.

The remote control device 3A also includes a monitor 31A that displays images taken by the camera 23A and images taken by the camera 26A. Further, the remote control device 3A transmits a control signal to fly the unmanned flying object 2A, a control signal to control the cameras 23A and 26A, a control signal to control the water sampling device 25A, etc. The transmitter/receiver 32A is provided to receive image signals and the like.

In addition, the unmanned flying vehicle 2B for photographing may have a configuration in which the water sampling device 25A is removed from the unmanned flying vehicle 2A for collecting seawater.

The information processing device 4 acquires an image from a microscope 5 that photographs a specimen prepared using seawater sampled by the unmanned flying vehicle 2A. The information processing device 4 includes a control unit 41 that executes a program for analyzing images captured by the microscope 5, a display unit 42 that displays images captured by the microscope 5, analysis results of the images, etc. 5, an operation section 43 for operating operations such as inputting an image photographed in step 5, analyzing the image, and outputting an analysis result, and a communication section 44 connected to a communication network 6 such as the Internet.

The red tide inspection system 1 counts the number of plankton in seawater and determines harmful red tide. First, in order to determine the type of plankton, the characteristics of each type of plankton, such as shape and color, are learned using, for example, a neural network, and the learning results are stored in the learning server 7.

The information processing device 4 acquires learning results regarding discrimination of plankton types from the learning server 7, and discriminates the plankton types in the image. The information processing device 4 counts the number of individuals of each type of plankton, compares the number of individuals with a reference value, and determines harmful red tide. Then, the counting results and harmful red tide discrimination results for each type of plankton are stored in the cloud server 8 via the communication network 6.

The results of determining harmful red tide are divided into multiple stages depending on the population of each type of plankton. In this example, the determination result of harmful red tide is set to two levels: an alert level that urges you to stop feeding and move fish cages, and a caution level that urges you to pay attention to plankton trends and make preparations or stop feeding and move fish cages. Ru.

<An example of the red tide inspection method of this embodiment>
FIG. 4 is a flowchart showing an example of the operation of the red tide inspection system according to the present embodiment, and an example of the red tide inspection method according to the present embodiment will be described below with reference to each figure.

Step 1
An unmanned aerial vehicle 2B for photographing is flown to photograph the sea surface from above.

Step 2
The image including the sea surface taken by the unmanned aerial vehicle 2B is displayed on the monitor of the remote control device of the unmanned aerial vehicle 2B, and the operator compares the sea surface image with the sea surface color sample, and determines whether red tide occurs based on the color of the sea surface. A water sampling point is selected by determining a location where red tide is expected to occur, a location where red tide is predicted to occur, etc., and the coordinates of the water sampling point are acquired based on the flight log and image of the unmanned aerial vehicle 2B.

Note that images taken by the unmanned aerial vehicle 2B are stored in the cloud server 8 via the communication network 6, a removable semiconductor memory (not shown), and the like. By accessing the cloud server 8, users of the red tide inspection system 1, such as aquaculture businesses, fishing cooperatives, and local governments, can display images of the sea surface including water sampling locations and a map specifying the water sampling locations. Moreover, since the unmanned flying vehicle 2A for seawater collection is also equipped with the camera 23A, the unmanned flying vehicle 2A may also serve as an unmanned flying vehicle used for selecting a water sampling point.

Step 3
Based on the positional information of the water sampling point, the unmanned aircraft 2A for seawater collection is flown, and the water sampling container 250A is dropped at the point of the predetermined positional information to sample seawater. When there are multiple water sampling points, the unmanned flying vehicle 2A is flown based on the positional information of each water sampling point, and the water sampling container 250A is dropped at the predetermined positional information to sample seawater. When seawater is sampled at different sampling depths, seawater at a desired depth is sampled by adjusting the altitude of the unmanned flying vehicle 2A, adjusting the length of the wire 251A fed out by the servo motor 252A, and the like. In order to sample seawater at a desired depth, for example, the timing of opening and closing the lids (not shown) of the plurality of water sampling containers 250A is adjusted using springs, and the lids are opened when a predetermined pressure corresponding to the depth is applied. . Compared to conventional water sampling by humans and boats, plankton can be discovered over a wide area by photographing from above, and water can be sampled in a short time. Also, compared to fixed buoys, it is possible to freely select the water sampling point.

Step 4
Seawater is collected from the water sampling container 250A of the unmanned aerial vehicle 2A.

Step 5
The seawater collected from the unmanned flying vehicle 2A is filtered to remove impurities larger than the plankton to be counted, and then injected into the plankton counting plate 50 to create a sample.

Step 6
The plankton injection plate 50 is photographed with a microscope 5 to obtain an enlarged image of plankton.

Step 7
The information processing device 4 acquires learning results regarding discrimination of plankton types from the learning server 7.

Step 8
The information processing device 4 determines the type of plankton in the image based on the learning results obtained from the learning server 7. The information processing device 4 counts the number of individuals of each type of plankton.

Step 9
The information processing device 4 compares the number of individuals of each type of plankton with a reference value to determine harmful red tide.

Step 10
The information processing device 4 stores the counting results for each type of plankton and the harmful red tide determination results in the cloud server 8 via the communication network 6.

Step 11
The information processing device 4 displays the counting results and harmful red tide discrimination results for each type of plankton.

In addition, the cloud server 8 provides information that can be visually recognized on a map that specifies water sampling points, based on the counting results for each type of plankton, the harmful red tide discrimination results, and a map. Edit to.

FIG. 5 is an explanatory diagram showing an example of red tide occurrence information displayed on the information processing device. Display information 100 includes red tide occurrence notification information 101 that notifies the occurrence of red tide, and URL information that indicates the address of an image that can be viewed on a map that specifies water sampling locations, as well as counting results for each type of plankton and harmful red tide determination results. 102, red tide occurrence point information 103 that specifies the red tide occurrence point, and red tide discrimination information 104 that indicates the type of red tide, the discrimination result, and the depth at which seawater was sampled. Note that the display information 100 may be displayable on the cloud server 8, which is a server.

1... Red tide inspection system, 2A... Unmanned aircraft, 20A... Rotor, 21A... Motor, 22A... Speed controller, 23A... Camera, 24A... Gimbal, 25A... Collection Water device, 250A...Water sampling container, 251A...Wire, 252A...Servo motor, 26A...Camera, 27A...Flight controller, 28A...Transmitter/receiver, 3A...Remote control Apparatus, 30A... Operating unit, 31A... Monitor, 32A... Transmitter/receiver, 4... Information processing device, 41... Control unit, 42... Display unit, 43... Operating unit , 44... Communication department, 5... Microscope, 50... Plankton injection plate, 6... Communication network, 7... Learning server, 8... Cloud server

Claims (5)

An unmanned flying vehicle equipped with a water sampling device that samples seawater;
From images taken with a microscope of seawater sampled by the unmanned aerial vehicle, the types of plankton that cause red tide are determined, the number of individuals of each type of plankton is counted, harmful red tide is determined, and each type of plankton is A red tide inspection system comprising an information processing device that displays counting results and harmful red tide determination results. Seawater sampling is performed by the unmanned aerial vehicle having a water sampling device at a water sampling point selected based on an image of the sea surface taken by the unmanned aerial vehicle having the water sampling device or another unmanned aerial vehicle. The red tide inspection system described in item 1. The red tide inspection system according to claim 1 or 2, wherein the unmanned flying vehicle having a water sampling device includes a plurality of water sampling devices that sample seawater at different depths and different points. The server that receives the counting results for each plankton type and the harmful red tide determination results counted by the information processing device is configured to make the counting results for each plankton type and the harmful red tide determination results visible on a map that specifies water sampling locations. The red tide inspection system according to any one of claims 1 to 3, wherein the red tide inspection system generates a red tide image. The process of photographing the sea surface with an unmanned aerial vehicle,
a step of selecting a seawater sampling point from an image of the sea surface taken by the unmanned aerial vehicle;
A step of flying an unmanned aircraft having a water sampling device to a selected water sampling location and sampling seawater at the water sampling location;
A process of photographing the sampled seawater with a microscope,
The process of determining the type of plankton that causes red tide from images taken with a microscope, counting the number of individuals of each type of plankton, and determining harmful red tide;
A red tide inspection method that performs the steps of: displaying a harmful red tide determination result;

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