JP7541542B2 - Signal processing device, signal processing system, program, and signal processing method - Google Patents

Description

The present invention relates to a signal processing device, a signal processing system, a program, and a signal processing method.

Patent Document 1 describes a piezoelectric braid.
[Prior Art Literature]
[Patent Documents]
[Patent Document 1] JP 2018-11334 A

According to one embodiment of the present invention, a signal processing device is provided. The signal processing device may include a piezoelectric signal acquisition unit that acquires a piezoelectric signal output by a piezoelectric braid incorporated in a fishing net. The signal processing device may include a position estimation unit that estimates a position in the fishing net where pressure is applied based on the piezoelectric signal.

The piezoelectric signal acquisition unit may acquire the piezoelectric signals output by each of the piezoelectric braids incorporated in the fishing net, and the position estimation unit may estimate the position of the fishing net where pressure is applied based on the piezoelectric signals. The position estimation unit may estimate the position of the fishing net where pressure is applied by inputting the piezoelectric signals acquired by the piezoelectric signal acquisition unit into a learning model in which the input is the piezoelectric signals output by the piezoelectric braids incorporated in the fishing net and the output is the position of the fishing net where pressure is applied. The signal processing device may further include a model generation unit that generates the learning model by machine learning using the position of the fishing net where pressure is applied and the piezoelectric signals output by the piezoelectric braids when the pressure is applied to the fishing net as learning data.

The signal processing device may further include a fish state estimation unit that estimates the state of the fish in the fishing net based on the position of the fishing net where pressure was applied and the time when pressure was applied, which are estimated by the position estimation unit. The fish state estimation unit may estimate the catch amount of the fishing net based on the position of the fishing net where pressure was applied and the time when pressure was applied, which are estimated by the position estimation unit. The position estimation unit may estimate the position and area of the fishing net where pressure was applied based on the piezoelectric signal, and the fish state estimation unit may estimate the size of the fish that collided with the fishing net based on the position and area estimated by the position estimation unit. The signal processing device may further include a water current state estimation unit that estimates the state of the water current in the water area in which the fishing net is located based on the position of the fishing net where pressure was applied and the time when pressure was applied, which are estimated by the position estimation unit.

According to one embodiment of the present invention, a signal processing system is provided. The signal processing device may include the signal processing device and the fishing net.

According to one embodiment of the present invention, a program is provided for causing a computer to function as the signal processing device.

According to one embodiment of the present invention, a signal processing method executed by a computer is provided. The signal processing method may include a piezoelectric signal acquisition step of acquiring a piezoelectric signal output by a piezoelectric braid incorporated in a fishing net. The signal processing method may include a position estimation step of estimating a position in the fishing net where pressure is applied based on the piezoelectric signal.

Note that the above summary of the invention does not list all of the necessary features of the present invention. Also, subcombinations of these features may also be inventions.

1 illustrates a schematic diagram of an example of a system 10. 2 illustrates an example of a functional configuration of a signal processing device 200. 10 is an explanatory diagram for explaining an estimation process performed by the signal processing device 200. FIG. 10 is an explanatory diagram for explaining an estimation process performed by the signal processing device 200. FIG. 1 shows a schematic diagram of an example of an environment in which the fishing net 100 is installed. 10 illustrates an example of a processing flow by the signal processing device 200. 1 shows an example of a hardware configuration of a computer 1200 that functions as the signal processing device 200.

Fishing nets are essential for fishing and aquaculture. With fixed nets, it is impossible to know how many fish are caught in them until the net is raised. Raising the net when there are only a few fish is undesirable from the standpoint of cost-effectiveness, etc. For this reason, it is desirable to provide technology that can grasp the situation inside the fishing net. In the system 10 according to this embodiment, a fishing net incorporating a piezoelectric braid is used to provide technology that can grasp the situation inside the fishing net and the situation around the fishing net.

The present invention will be described below through embodiments of the invention, but the following embodiments do not limit the invention according to the claims. Furthermore, not all of the combinations of features described in the embodiments are necessarily essential to the solution of the invention.

Figure 1 shows a schematic diagram of an example of a system 10. The system 10 includes a fishing net 100 and a signal processing device 200.

The fishing net 100 according to this embodiment incorporates a piezoelectric braid. A piezoelectric braid is a sensor in which a piezoelectric body is braided. The piezoelectric braid is produced, for example, by braiding a piezoelectric body using polylactic acid fibers. The piezoelectric braid makes it possible to sense the applied pressure. The piezoelectric braid can output a signal (sometimes referred to as a piezoelectric signal) that corresponds to the applied pressure.

The fishing net 100 may be produced by weaving a plurality of piezoelectric braids. The fishing net 100 may also be produced by incorporating piezoelectric braids into each of the linear members of a so-called normal fishing net.

In FIG. 1, multiple piezoelectric braids 110 are braided vertically and horizontally. The multiple piezoelectric braids 110 are electrically connected to a signal processing unit 130. The signal processing unit 130 transmits the piezoelectric signals output by each of the multiple piezoelectric braids 110 to a signal processing device 200.

The signal processing unit 130 and the signal processing device 200 may be connected by wire. The signal processing unit 130 and the signal processing device 200 may be connected wirelessly. For example, the signal processing unit 130 and the signal processing device 200 are wirelessly connected by short-range wireless communication.

The signal processing unit 130 may have a mobile communication function and transmit the piezoelectric signal to the signal processing device 200 via a wireless base station. The signal processing unit 130 may have a Wi-Fi (registered trademark) communication function and transmit the piezoelectric signal to the signal processing device 200 via a Wi-Fi access point or the like. The communication method between the signal processing unit 130 and the signal processing device 200 is not limited to these, and any existing communication method may be used.

The signal processing device 200 estimates the position in the fishing net 100 where pressure was applied based on the piezoelectric signal received from the signal processing unit 130. The piezoelectric braided cord 110 outputs a piezoelectric signal that exhibits different characteristics depending on the position where pressure was applied and the strength of the pressure. Therefore, by collecting and learning the piezoelectric signals output by the multiple piezoelectric braided cords 110 while applying various strengths of pressure to various positions on the fishing net 100, it is possible to estimate the position in the fishing net 100 where pressure was applied and the strength of the pressure from the piezoelectric signals output by the multiple piezoelectric braided cords 110.

Figure 2 shows an example of a schematic functional configuration of the signal processing device 200. The signal processing device 200 includes a learning data generation unit 202, a learning data acquisition unit 204, a model generation unit 206, a model storage unit 208, a model acquisition unit 210, a piezoelectric signal acquisition unit 212, an estimation unit 220, and an output control unit 230. Note that it is not essential that the signal processing device 200 includes all of these.

The learning data generating unit 202 generates learning data. The learning data may include positions in the fishing net 100 where pressure is applied, and multiple piezoelectric signals output by the multiple piezoelectric braids 110 when pressure is applied to the fishing net 100. The learning data may include positions in the fishing net 100 where pressure is applied and the strength of the pressure, and multiple piezoelectric signals output by the multiple piezoelectric braids 110 when pressure is applied to the fishing net 100. The learning data may include positions and areas in the fishing net 100 where pressure is applied, and multiple piezoelectric signals output by the multiple piezoelectric braids 110 when pressure is applied to the fishing net 100.

The learning data generating unit 202 may generate learning data using the results of an experiment in which pressure is applied to the fishing net 100. Any method may be used to apply pressure to the fishing net 100 to generate learning data. For example, an experimenter places the fishing net 100 in a laboratory on land, applies pressure using a robot arm, etc., and records the position on the fishing net 100 where the pressure is applied and the piezoelectric signals from the multiple piezoelectric braids 110. The experimenter may also record the strength of the pressure applied to the fishing net 100. The experimenter may further change the area where pressure is applied to the fishing net 100 and record the area. Note that if an experiment can be performed in the same environment or a similar environment to the environment in which the fishing net 100 is actually used, it is expected that the accuracy will be improved by performing the experiment in such an environment. Specifically, the fishing net 100 may be placed underwater for the experiment, or may be placed in the sea where the fishing net 100 is actually placed for the experiment.

The training data generating unit 202 may generate training data using synthetic data. The training data generating unit 202 may generate synthetic data indicating piezoelectric signals output by the multiple piezoelectric braids 110 when pressure is applied to the fishing net 100 in the virtual world, and use the synthetic data.

The learning data acquisition unit 204 acquires learning data. The learning data acquisition unit 204 may acquire learning data generated by the learning data generation unit 202. The learning data acquisition unit 204 may receive learning data generated by another device from the other device.

The model generation unit 206 generates a learning model using the learning data acquired by the learning data acquisition unit 204. For example, the model generation unit 206 generates a learning model in which the input is a plurality of piezoelectric signals output by the plurality of piezoelectric braids 110, and the output is the position of the fishing net 100 where pressure is applied. The model generation unit 206 may generate a learning model in which the input is a plurality of piezoelectric signals output by the plurality of piezoelectric braids 110, and the output is the position of the fishing net 100 where pressure is applied and the strength of the pressure. The model generation unit 206 may generate a learning model in which the input is a plurality of piezoelectric signals output by the plurality of piezoelectric braids 110, and the output is the position of the fishing net 100 where pressure is applied and the area. The model generation unit 206 may generate a learning model in which the input is a plurality of piezoelectric signals output by the plurality of piezoelectric braids 110, and the output is the position of the fishing net 100 where pressure is applied and the area and the strength of the pressure.

The model storage unit 208 stores the learning model generated by the model generation unit 206. The model acquisition unit 210 acquires the learning model generated by another device from the other device. The other device may generate the learning model in a similar manner to that of the model generation unit 206. The model storage unit 208 may store the learning model acquired by the model acquisition unit 210.

The piezoelectric signal acquisition unit 212 acquires the piezoelectric signal output by the piezoelectric braided cord 110 incorporated in the fishing net 100. The piezoelectric signal acquisition unit 212 may acquire the piezoelectric signal output by each of the multiple piezoelectric braided cords 110 incorporated in the fishing net 100. The piezoelectric signal acquisition unit 212 may receive the piezoelectric signal from the signal processing unit 130.

The estimation unit 220 executes estimation processing using the piezoelectric signal acquired by the piezoelectric signal acquisition unit 212. The output control unit 230 controls the estimation result by the estimation unit 220 to be output. For example, the output control unit 230 controls the estimation result by the estimation unit 220 to be displayed and output on a display provided in the signal processing device 200. For example, the output control unit 230 controls the estimation result by the estimation unit 220 to be transmitted and output to another device.

The estimation unit 220 has a position estimation unit 222, a fish state estimation unit 224, and a water current state estimation unit 226. Note that it is not essential that the estimation unit 220 has all of these.

The position estimation unit 222 estimates the position in the fishing net 100 where pressure is applied based on the piezoelectric signal. The position estimation unit 222 may estimate the position in the fishing net 100 where pressure is applied based on the multiple piezoelectric signals acquired by the piezoelectric signal acquisition unit 212.

The position estimation unit 222 may estimate the position in the fishing net 100 where pressure is applied by inputting the multiple piezoelectric signals acquired by the piezoelectric signal acquisition unit 212 to the learning model stored in the model storage unit 208. The position estimation unit 222 may estimate the position in the fishing net 100 where pressure is applied at each time. By controlling the output control unit 230 to output the estimation result, the output destination can grasp the state of pressure being applied to the fishing net 100 in real time.

The position estimation unit 222 may estimate the position where pressure is applied in the fishing net 100 and the strength of the pressure by inputting the multiple piezoelectric signals acquired by the piezoelectric signal acquisition unit 212 to the learning model stored in the model storage unit 208. The position estimation unit 222 may estimate the position where pressure is applied in the fishing net 100 and the strength of the pressure at each time. By controlling the output control unit 230 to output the estimation result, the output destination can grasp the state of pressure being applied to the fishing net 100 in real time.

The fish state estimation unit 224 estimates the state of the fish in the fishing net 100 based on the estimation result by the position estimation unit 222. For example, the fish state estimation unit 224 estimates the state of the fish in the fishing net 100 based on the position in the fishing net 100 where pressure was applied and the time when the pressure was applied, which are estimated by the position estimation unit 222.

For example, when the fishing net 100 is used as a fixed net, the fish state estimation unit 224 estimates the catch, i.e., the amount of fish present in the fishing net 100. The fish state estimation unit 224 pre-stores catch estimation information that associates catch information indicating the catch with, for example, the proportion of the position where pressure is applied to the entire fishing net 100. Table 1 below is an example of catch estimation information. As exemplified in Table 1, the catch estimation information may register a numerical value indicating the catch for each range of the proportion of the position where pressure is applied to the entire fishing net 100.

Table 2 below is an example of the catch volume estimation information. As shown in Table 2, the catch volume estimation information may register a word that expresses the catch volume for each range of the ratio of the position where pressure is applied to the entire fishing net 100.

The output control unit 230 may control the output of the estimation results by the fish state estimation unit 224 to a fisherman or the like who is fishing using the fishing net 100. This can, for example, prevent the fisherman from pulling up the net even if the catch is small.

The fish condition estimation unit 224 estimates the condition of the fish based on, for example, the position in the fishing net 100 where pressure was applied, the strength of the pressure, and the time when the pressure was applied, estimated by the position estimation unit 222. For example, in fish farms, fish may collide with the fishing net 100, resulting in injury or loss of scales, which may cause illness, but this is difficult to determine from the sea.

The fish condition estimation unit 224 estimates the health of the fish based on, for example, the number of fish in the fishing net 100, the position in the fishing net 100 where pressure was applied, the strength of the pressure, and the time when the pressure was applied. For example, the health of the fish can be estimated by calculating the average number of collisions and the degree of collisions of the fish for each predetermined period and estimating the state of injuries of the fish from the number of collisions and the degree of collisions. Note that this is just one example, and other methods may be used to estimate the health of the fish. The output control unit 230 controls the output of the estimation result by the fish condition estimation unit 224 to, for example, the manager of the fish farm. This can support the manager of the fish farm in understanding the health of the fish.

The water current state estimation unit 226 estimates the state of the water current in the water area where the fishing net 100 is placed based on the estimation result by the position estimation unit 222. For example, the water current state estimation unit 226 estimates the state of the water current in the water area where the fishing net 100 is placed based on the position where pressure was applied in the fishing net 100 estimated by the position estimation unit 222 and the time when the pressure was applied. For example, the water current state estimation unit 226 estimates the state of the water current in the water area where the fishing net 100 is placed based on the position where pressure was applied in the fishing net 100 estimated by the position estimation unit 222, the strength of the pressure, and the time when the pressure was applied.

For example, when the ratio of the positions where pressure is applied to the entire fishing net 100 is greater than a predetermined threshold, the water current state estimation unit 226 estimates that the water current is changing because force is being applied to the entire fishing net 100. The water current state estimation unit 226 may estimate the strength of the water current based on the average value of the strength of the pressure. For example, the water current state estimation unit 226 estimates that the stronger the average value of the strength of the pressure, the stronger the strength of the water current.

The water flow state estimation unit 226 prestores water flow estimation information that associates water flow information representing the water flow with each average value of pressure strength, for example. In the water flow estimation information, for example, a numerical value representing the water flow is registered for each range of the average value of pressure strength. In the water flow estimation information, for example, a word indicating the strength of the water flow is registered for each range of the average value of pressure strength.

When the fishing net 100 is used as a fixed net, the output control unit 230 may control the output of the estimation result by the water current state estimation unit 226 to a fisherman or the like who is fishing using the fishing net 100. This allows the fisherman to be informed that, for example, when a very strong water current is occurring, the fish in the fishing net 100 may be adversely affected or the fishing net 100 may be swept away.

When the fishing net 100 is used in a fish farm, the output control unit 230 may control the output of the estimation results by the water current state estimation unit 226 to the manager of the fish farm, etc. This makes it possible to analyze information such as the correlation between the amount of movement of fish due to tides and the taste of the fish, the amount of food, etc.

3 and 4 are explanatory diagrams for explaining the estimation process by the signal processing device 200. The position estimation unit 222 may estimate the position and area of the fishing net 100 where pressure is applied.

For example, the position estimation unit 222 estimates the positions in the fishing net 100 where pressure is applied and the strength of the pressure based on multiple piezoelectric signals, and estimates the area where pressure is applied using the estimation results. The area where pressure is applied can be calculated from the positional relationship between the positions where pressure is applied and the relationship between the strength of pressure.

The position estimation unit 222 may estimate the position and area of the fishing net 100 where pressure is applied based on the multiple piezoelectric signals. For example, the position estimation unit 222 estimates the position and area of the fishing net 100 where pressure is applied by inputting the multiple piezoelectric signals acquired by the piezoelectric signal acquisition unit 212 into a learning model generated using learning data including the position and area of the fishing net 100 where pressure is applied and the multiple piezoelectric signals output by the multiple piezoelectric braids 110 when pressure is applied to the fishing net 100.

These features make it possible to output the estimation result that estimates the area where pressure is applied in addition to the location on the fishing net 100 where pressure is applied. This makes it possible to analyze the situation, for example, in the case of the estimation result shown in Figure 3, where a fish is caught in the fishing net 100, and in the case of the estimation result shown in Figure 4, where a fish has collided with the fishing net 100.

Figure 5 shows a schematic diagram of an example of an installation environment for the fishing net 100. Here, the fishing net 100 is shown installed in a fish pen. The piezoelectric signal output by the piezoelectric braid 110 incorporated in the fishing net 100 may be transmitted to the signal processing device 200 by the signal processing unit 130 disposed above the fish pen (in the air). The signal processing device 200 uses the multiple piezoelectric signals received from the signal processing unit 130 to estimate the condition of the fish in the fish pen and the condition of the water current in the water area where the fish pen is located.

In the above embodiment, the piezoelectric braid 110 is mainly incorporated into the entire fishing net 100, but this is not limiting. The piezoelectric braid 110 does not have to be incorporated into the entire fishing net 100. For example, the piezoelectric braid 110 is incorporated every other predetermined number of times in the vertical direction of the fishing net 100. For example, the piezoelectric braid 110 is incorporated every other predetermined number of times in the horizontal direction of the fishing net 100. For example, the piezoelectric braid 110 is incorporated every other predetermined number of times in the vertical and horizontal directions of the fishing net 100. The interval at which the piezoelectric braid 110 is incorporated may be determined according to the size of the target fish.

For example, the piezoelectric braided cord 110 is incorporated only in the vertical direction of the fishing net 100. For example, the piezoelectric braided cord 110 is incorporated only in the horizontal direction of the fishing net 100.

For example, the piezoelectric braid 110 is incorporated only on a portion of the surface of the fishing net 100, rather than on the entire surface. For example, the piezoelectric braid 110 is incorporated only in the central region of the fishing net 100. For example, the piezoelectric braid 110 is incorporated only in the region excluding the central region of the fishing net 100.

When the fishing net 100 is incorporated into a fish pen as illustrated in FIG. 5, the piezoelectric braid 110 may be incorporated into each layer in the depth direction. For example, if the net is configured with three layers in the depth direction, the piezoelectric braid 110 may be incorporated into only one of the three layers, or may be incorporated into only two of the three layers.

For example, as illustrated in FIG. 5, when the fishing net 100 is arranged in a rectangular parallelepiped shape, the piezoelectric braid 110 may be incorporated only in the corners.

Also, for example, the piezoelectric braid 110 may be incorporated only in the portion of the fishing net 100 to which the anchor is connected. In this case, for example, the estimation unit 220 estimates the strength of pressure applied to the anchor from the piezoelectric signal acquired by the piezoelectric signal acquisition unit 212. The output control unit 230 may control to output warning information to the manager of the fish pen, etc., when the strength of pressure applied to the anchor estimated by the estimation unit 220 is stronger than a predetermined threshold value. This allows the manager of the fish pen, etc., to be informed that a strong force is being applied to the anchor, i.e., that the fish pen may be in danger of being swept away.

Figure 6 shows an example of the flow of processing by the signal processing device 200. Here, the starting state is described as a state in which the fishing net 100 is placed in the sea and the environment is ready for the signal processing unit 130 to transmit piezoelectric signals from the multiple piezoelectric braids 110 of the fishing net 100.

In S102, the piezoelectric signal acquisition unit 212 acquires a plurality of piezoelectric signals output by the plurality of piezoelectric braids 110. In S104, the position estimation unit 222 estimates the position in the fishing net 100 where pressure was applied based on the plurality of piezoelectric signals acquired by the piezoelectric signal acquisition unit 212 in S102.

If a preset time has elapsed since the start of processing (YES in S106), proceed to S108; if not (NO in S106), return to S102. In S108, the estimation unit 220 performs state estimation based on multiple piezoelectric signals acquired at multiple times by the piezoelectric signal acquisition unit 212. For example, the fish state estimation unit 224 estimates the state of the fish in the fishing net 100. For example, the water current state estimation unit 226 estimates the state of the water current in the water area in which the fishing net 100 is placed.

In S110, the output control unit 230 determines whether or not to execute a notification based on the estimation result by the estimation unit 220. For example, the output control unit 230 determines to execute a notification when the state of the fish estimated by the fish state estimation unit 224 satisfies a pre-registered notification condition. For example, the output control unit 230 determines to execute a notification when the state of the water current estimated by the water current state estimation unit 226 satisfies a pre-registered notification condition. If it is determined to execute a notification, the process proceeds to S112, and if it is determined not to execute a notification, the process proceeds to S114. In S112, the output control unit 230 controls to output the notification data.

In S114, it is determined whether or not to end monitoring of the fishing net 100. If the signal processing device 200 has received an instruction to end monitoring of the fishing net 100, it determines that it should be ended. If it determines that it should not be ended, it returns to S102.

7 shows an example of a hardware configuration of a computer 1200 functioning as a signal processing device 200. A program installed on the computer 1200 can cause the computer 1200 to function as one or more "parts" of the device according to the present embodiment, or to execute operations or one or more "parts" associated with the device according to the present embodiment, and/or to execute a process or steps of the process according to the present embodiment. Such a program can be executed by the CPU 1212 to cause the computer 1200 to execute specific operations associated with some or all of the blocks of the flowcharts and block diagrams described herein.

The computer 1200 according to this embodiment includes a CPU 1212, a RAM 1214, and a graphics controller 1216, which are connected to each other by a host controller 1210. The computer 1200 also includes input/output units such as a communication interface 1222, a storage device 1224, a DVD drive, and an IC card drive, which are connected to the host controller 1210 via an input/output controller 1220. The DVD drive may be a DVD-ROM drive, a DVD-RAM drive, etc. The storage device 1224 may be a hard disk drive, a solid state drive, etc. The computer 1200 also includes a ROM 1230 and a legacy input/output unit such as a keyboard, which are connected to the input/output controller 1220 via an input/output chip 1240.

The CPU 1212 operates according to the programs stored in the ROM 1230 and the RAM 1214, thereby controlling each unit. The graphics controller 1216 acquires image data generated by the CPU 1212 into a frame buffer or the like provided in the RAM 1214 or into itself, and causes the image data to be displayed on the display device 1218.

The communication interface 1222 communicates with other electronic devices via a network. The storage device 1224 stores programs and data used by the CPU 1212 in the computer 1200. The DVD drive reads programs or data from a DVD-ROM or the like and provides them to the storage device 1224. The IC card drive reads programs and data from an IC card and/or writes programs and data to an IC card.

ROM 1230 stores therein a boot program, etc., executed by computer 1200 upon activation, and/or a program that depends on the hardware of computer 1200. I/O chip 1240 may also connect various I/O units to I/O controller 1220 via USB ports, parallel ports, serial ports, keyboard ports, mouse ports, etc.

The programs are provided by a computer-readable storage medium such as a DVD-ROM or an IC card. The programs are read from the computer-readable storage medium, installed in storage device 1224, RAM 1214, or ROM 1230, which are also examples of computer-readable storage media, and executed by CPU 1212. The information processing described in these programs is read by computer 1200, and brings about cooperation between the programs and the various types of hardware resources described above. An apparatus or method may be constructed by realizing the operation or processing of information according to the use of computer 1200.

For example, when communication is performed between computer 1200 and an external device, CPU 1212 may execute a communication program loaded into RAM 1214 and instruct communication interface 1222 to perform communication processing based on the processing described in the communication program. Under the control of CPU 1212, communication interface 1222 reads transmission data stored in a transmission buffer area provided in RAM 1214, storage device 1224, a DVD-ROM, or a recording medium such as an IC card, and transmits the read transmission data to the network, or writes received data received from the network to a reception buffer area or the like provided on the recording medium.

The CPU 1212 may also cause all or a necessary portion of a file or database stored in an external recording medium such as the storage device 1224, a DVD drive (DVD-ROM), an IC card, etc. to be read into the RAM 1214, and perform various types of processing on the data on the RAM 1214. The CPU 1212 may then write back the processed data to the external recording medium.

Various types of information, such as various types of programs, data, tables, and databases, may be stored in the recording medium and may undergo information processing. The CPU 1212 may perform various types of processing on the data read from the RAM 1214, including various types of operations, information processing, conditional judgment, conditional branching, unconditional branching, information search/replacement, etc., as described throughout this disclosure and specified by the instruction sequence of the program, and writes back the results to the RAM 1214. The CPU 1212 may also search for information in a file, database, etc. in the recording medium. For example, when multiple entries each having an attribute value of a first attribute associated with an attribute value of a second attribute are stored in the recording medium, the CPU 1212 may search for an entry whose attribute value of the first attribute matches a specified condition from among the multiple entries, read the attribute value of the second attribute stored in the entry, and thereby obtain the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

The above-described programs or software modules may be stored in a computer-readable storage medium on the computer 1200 or in the vicinity of the computer 1200. In addition, a recording medium such as a hard disk or RAM provided in a server system connected to a dedicated communication network or the Internet can be used as a computer-readable storage medium, thereby providing the programs to the computer 1200 via the network.

The blocks in the flowcharts and block diagrams in this embodiment may represent stages of a process in which an operation is performed or "parts" of a device responsible for performing the operation. Particular stages and "parts" may be implemented by dedicated circuitry, programmable circuitry provided with computer-readable instructions stored on a computer-readable storage medium, and/or a processor provided with computer-readable instructions stored on a computer-readable storage medium. The dedicated circuitry may include digital and/or analog hardware circuits and may include integrated circuits (ICs) and/or discrete circuits. The programmable circuitry may include reconfigurable hardware circuits including AND, OR, XOR, NAND, NOR, and other logical operations, flip-flops, registers, and memory elements, such as, for example, field programmable gate arrays (FPGAs) and programmable logic arrays (PLAs).

A computer-readable storage medium may include any tangible device capable of storing instructions that are executed by a suitable device, such that a computer-readable storage medium having instructions stored thereon comprises an article of manufacture that includes instructions that can be executed to create means for performing the operations specified in the flowchart or block diagram. Examples of computer-readable storage media may include electronic storage media, magnetic storage media, optical storage media, electromagnetic storage media, semiconductor storage media, and the like. More specific examples of computer-readable storage media may include floppy disks, diskettes, hard disks, random access memories (RAMs), read-only memories (ROMs), erasable programmable read-only memories (EPROMs or flash memories), electrically erasable programmable read-only memories (EEPROMs), static random access memories (SRAMs), compact disk read-only memories (CD-ROMs), digital versatile disks (DVDs), Blu-ray disks, memory sticks, integrated circuit cards, and the like.

The computer readable instructions may include either assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including object-oriented programming languages such as Smalltalk (registered trademark), JAVA (registered trademark), C++, etc., and conventional procedural programming languages such as the "C" programming language or similar programming languages.

The computer-readable instructions may be provided to a processor of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, or a programmable circuit, either locally or over a local area network (LAN), a wide area network (WAN), such as the Internet, etc., so that the processor of the general-purpose computer, special-purpose computer, or other programmable data processing apparatus, or the programmable circuit, executes the computer-readable instructions to generate means for performing the operations specified in the flowcharts or block diagrams. Examples of processors include computer processors, processing units, microprocessors, digital signal processors, controllers, microcontrollers, etc.

The present invention has been described above using an embodiment, but the technical scope of the present invention is not limited to the scope described in the above embodiment. It is clear to those skilled in the art that various modifications and improvements can be made to the above embodiment. It is clear from the claims that forms incorporating such modifications or improvements can also be included in the technical scope of the present invention.

The order of execution of each process, such as operations, procedures, steps, and stages, in the devices, systems, programs, and methods shown in the claims, specifications, and drawings is not specifically stated as "before" or "prior to," and it should be noted that the processes may be performed in any order, unless the output of a previous process is used in a later process. Even if the operational flow in the claims, specifications, and drawings is explained using "first," "next," etc. for convenience, it does not mean that it is essential to perform the processes in that order.

10 System, 100 Fishing net, 110 Piezoelectric braid, 130 Signal processing unit, 200 Signal processing device, 202 Learning data generation unit, 204 Learning data acquisition unit, 206 Model generation unit, 208 Model storage unit, 210 Model acquisition unit, 212 Piezoelectric signal acquisition unit, 220 Estimation unit, 222 Position estimation unit, 224 Fish state estimation unit, 226 Water current state estimation unit, 230 Output control unit, 1200 Computer, 1210 Host controller, 1212 CPU, 1214 RAM, 1216 Graphic controller, 1218 Display device, 1220 Input/output controller, 1222 Communication interface, 1224 Storage device, 1230 ROM, 1240 Input/output chip

Claims (20)

A piezoelectric signal acquisition unit that acquires a plurality of piezoelectric signals outputted from a plurality of piezoelectric braids that are incorporated in the vertical direction and the horizontal direction of the fishing net;
and a position estimation unit that estimates a position in the fishing net where pressure is applied based on the plurality of piezoelectric signals. 2. The signal processing device according to claim 1, wherein the position estimation unit estimates the position where pressure is applied in the fishing net by inputting the plurality of piezoelectric signals acquired by the piezoelectric signal acquisition unit into a learning model in which an input is a plurality of piezoelectric signals output by a plurality of piezoelectric braids incorporated in a fishing net and an output is a position where pressure is applied in the fishing net. 3. The signal processing device according to claim 2, further comprising: a model generation unit configured to generate the learning model by machine learning using learning data including positions where pressure is applied in the fishing net into which the plurality of piezoelectric braids are incorporated and a plurality of piezoelectric signals output by the plurality of piezoelectric braids when the pressure is applied to the fishing net . The signal processing device according to claim 1 , further comprising: a fish state estimation unit that estimates a state of fish in the fishing net based on a position in the fishing net where pressure was applied estimated by the position estimation unit and a time when the pressure was applied. The signal processing device according to claim 4 , wherein the fish state estimation unit estimates the amount of fish caught by the fishing net based on a position in the fishing net where pressure was applied estimated by the position estimation unit and a time when the pressure was applied. The position estimation unit estimates a position and an area of the fishing net to which pressure is applied based on the plurality of piezoelectric signals,
The signal processing device according to claim 4 , wherein the fish state estimation unit estimates a size of the fish that has collided with the fishing net based on the position and the area estimated by the position estimation unit. The signal processing device according to claim 1 , further comprising: a water current state estimation unit that estimates a water current state of a water area in which the fishing net is placed based on a position of the fishing net where pressure was applied estimated by the position estimation unit and a time when the pressure was applied. a piezoelectric signal acquiring unit for acquiring a piezoelectric signal outputted by a piezoelectric braid incorporated in a fishing net;
a position estimation unit that estimates the position where pressure is applied in the fishing net by inputting the plurality of piezoelectric signals acquired by the piezoelectric signal acquisition unit into a learning model in which an input is a plurality of piezoelectric signals output by a plurality of piezoelectric braids incorporated in a fishing net and an output is a position where pressure is applied in the fishing net;
A signal processing device comprising: a piezoelectric signal acquiring unit for acquiring a piezoelectric signal outputted by a piezoelectric braid incorporated in a fishing net;
a position estimation unit that estimates a position in the fishing net where pressure is applied based on the piezoelectric signal;
a fish state estimation unit that estimates a state of fish in the fishing net based on the position of the fishing net where pressure was applied and the time when pressure was applied, the position estimation unit having been estimated;
A signal processing device comprising: a piezoelectric signal acquiring unit that acquires a piezoelectric signal outputted by a piezoelectric braid incorporated in a fishing net;
a position estimation unit that estimates a position and an area of the fishing net where pressure is applied based on the piezoelectric signal;
A signal processing device comprising: The signal processing device according to claim 10 , further comprising a fish state estimation unit that estimates a size of the fish that has collided with the fishing net based on the position and the area estimated by the position estimation unit. a piezoelectric signal acquiring unit that acquires a piezoelectric signal outputted by a piezoelectric braid incorporated in a fishing net;
a position estimation unit that estimates a position where pressure is applied in the fishing net based on the piezoelectric signal;
a water current state estimation unit that estimates a water current state of the water area in which the fishing net is placed based on the position of the fishing net where pressure was applied and the time when the pressure was applied, the position estimation unit having been estimated;
A signal processing device comprising: A signal processing device according to any one of claims 1 to 12 ;
The fishing net. A program for causing a computer to function as the signal processing device according to any one of claims 1 to 12 . 1. A computer-implemented signal processing method, comprising:
A piezoelectric signal acquisition step of acquiring a plurality of piezoelectric signals outputted by a plurality of piezoelectric braids incorporated in each of the vertical and horizontal directions of the fishing net;
and a position estimating step of estimating a position in the fishing net where pressure is applied based on the plurality of piezoelectric signals. 1. A computer-implemented signal processing method, comprising:
A piezoelectric signal acquisition step of acquiring a piezoelectric signal outputted by a piezoelectric braid incorporated in a fishing net;
a position estimation step of estimating the position where pressure is applied in the fishing net by inputting the plurality of piezoelectric signals acquired in the piezoelectric signal acquisition step into a learning model in which the input is a plurality of piezoelectric signals output by a plurality of piezoelectric braids incorporated in the fishing net and the output is the position where pressure is applied in the fishing net;
A signal processing method comprising: 1. A computer-implemented signal processing method, comprising:
A piezoelectric signal acquisition step of acquiring a piezoelectric signal outputted by a piezoelectric braid incorporated in a fishing net;
A position estimation step of estimating a position where pressure is applied in the fishing net based on the piezoelectric signal;
a fish state estimation step of estimating a state of fish in the fishing net based on the position of the fishing net where pressure was applied and the time when pressure was applied, which were estimated in the position estimation step;
A signal processing method comprising: 1. A computer-implemented signal processing method, comprising:
A piezoelectric signal acquisition step of acquiring a piezoelectric signal outputted by a piezoelectric braid incorporated in a fishing net;
a position estimation step of estimating a position and an area of the fishing net where pressure is applied based on the piezoelectric signal;
A signal processing method comprising: The signal processing method according to claim 18, further comprising a fish state estimation step of estimating a size of the fish that has collided with the fishing net based on the position and the area estimated in the position estimation step. 1. A computer-implemented signal processing method, comprising:
A piezoelectric signal acquisition step of acquiring a piezoelectric signal outputted by a piezoelectric braid incorporated in a fishing net;
A position estimation step of estimating a position where pressure is applied in the fishing net based on the piezoelectric signal;
a water current state estimation step of estimating a water current state of the water area in which the fishing net is placed based on the position of the fishing net where pressure was applied and the time when pressure was applied, which are estimated by the position estimation step;
A signal processing method comprising:

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