JP2023045056A - Measurement device - Google Patents

Abstract

To improve the measurement efficiency.SOLUTION: A measurement device 100 has a low-frequency sampling part 2 which detects the surrounding environment in water by sampling about once per second, a control part 1 which determines whether to detect the sound in the water according to the detection result of the low-frequency sampling part 2, and a high-frequency sampling part 4 which detects the sound in the water at a frequency higher than the sampling frequency of the low-frequency sampling part 2 when the control part 1 determined to detect the sound in the water.SELECTED DRAWING: Figure 1

Description

The present invention relates to a measuring device.

Many marine organisms are sound users and are sensitive to sound. For example, they generate sounds for underwater exploration, communication, intimidation, and breeding.

Under water, sound travels farther than light. The speed of sound in air is about 330m per second, but in water it is about 4.5 times faster, or about 1500m per second. It is much slower than light, but it travels long distances and its effects are immediate.

In recent years, there have been many reports on the effects of sound exposure on organisms. There are various artificial sound sources in the sea. Ships are the most numerous. It has been pointed out that the sounds emanating from ships accompanying shipping shorten the distances that whales and fish can communicate, and in some cases affect their reproduction.

On the other hand, there are also naturally occurring noises in the sea. Natural sounds include wind and rain, waves, currents, volcanic sounds, and the like. Underwater sounds are also caused by weather and sea conditions. Broadband sound due to precipitation is radiated from the surface of the sea into the sea. Broadband sound is also generated from bubbles generated by waves crashing in stormy weather.

Further, the biological sounds include not only sounds generated by living organisms (fish, cetaceans, etc.), but also all sounds associated with the actions and movements of living organisms, such as chewing sounds and swimming sounds of schools of fish. For example, there is also a pulse sound such as an archer shrimp that is emitted continuously from the coastal area.
Artificial sounds include sounds generated by ships, pile driving, air guns, offshore wind power, sonar, and divers.
As described above, underwater sounds are composed of artificial sounds, natural sounds, and biological sounds, and by monitoring underwater sounds, it is possible to collect various information caused by various sound sources.

So far, underwater sound monitoring has been performed by suspending underwater microphones from ships to observe underwater sounds, and by using surface-installed (buoys) or underwater-installed recorders to observe underwater sounds. In mobile objects, sound observations are carried out using ocean gliders and the like. However, marine gliders are difficult to use in shallow waters. Observation from a ship is difficult to implement for a long time and over a wide area from the viewpoint of cost and labor. Surface-installed (buoy) and underwater-installed recorders are often difficult to implement in coastal areas, such as requiring special installation permits for maritime security reasons or being limited to locations where they can be installed.

In order to measure the behavior, physiology, and experience environment of wildlife, biologging and biotelemetry methods are known, in which measurement devices equipped with various sensors are directly attached to living organisms for measurement.

Here, biologging refers to, for example, recording measured data inside a measuring device. In addition, biotelemetry refers to, for example, sending measured data wirelessly to the outside of a measuring device and collecting the measured data remotely (in a broad sense, biotelemetry is also included in biologging).

A measuring device used for biologging has, for example, a battery, an electronic board on which a sensor, a memory, a wireless terminal, etc. are mounted, and a case covering them (a case made of resin, metal, etc., or having equivalent performance).

The use of biologging can also be considered for the observation of underwater sounds. For example, by installing underwater sound recorders in marine organisms such as sea turtles and seals, it becomes possible to monitor underwater sounds as autonomous moving bodies. In addition, some marine organisms such as sea turtles and seals periodically rise to the surface of the water for respiration. It is possible to transmit data by short-range wireless communication. In the case of bio-logging, there is no need to install equipment underwater or on the surface, so it is thought that it will be possible to observe underwater sounds over a wide area even in coastal areas.

“Biologging” [online] May 2019: First edition published, National Institute for Environmental Studies [searched July 13, 2021], Internet <URL: https://tenbou.nies.go. en/science/description/detail.php?id=109>

In this way, observing underwater acoustics by bio-logging is considered to be an effective method for observing underwater artificial sounds, environmental sounds, and biological sounds. However, if the underwater sound data does not have quality to be analyzed, the data will be meaningless even if it is recorded in the first place. In biologging, there is a burden of attaching equipment to living organisms, so it is preferable to reduce the size of the equipment to be attached to living organisms as much as possible.
In one aspect, an object of the present invention is to improve the efficiency of observation.

In order to achieve the above object, the disclosed measuring device is provided. This measurement device includes a first detection unit that detects the surrounding environment underwater and the behavior of an individual wearing the measurement device at a first frequency, and detects underwater sounds according to the detection results of the first detection unit. and a second detection unit that measures and detects underwater sound at a frequency higher than the first frequency when the determination unit determines that underwater sound is detected. ing.

In one mode, efficiency of observation can be improved. By narrowing down the preferable period for actual observation, instead of continuously observing underwater sounds, it is possible to reduce the power required for observation and promote the miniaturization of the battery.

It is a figure which shows the measuring device of embodiment. It is a block diagram explaining the function of the measuring device of an embodiment. It is a flow chart explaining operation of a measuring device. FIG. 4 is a diagram showing an example of depth data obtained from a sea turtle; It is a figure which shows an example of the hardware constitutions of the measuring device of embodiment.

A measuring device according to an embodiment will be described in detail below with reference to the drawings.

The position, size, shape, range, etc. of each configuration shown in the following drawings may not represent the actual position, size, shape, range, etc., in order to facilitate understanding of the invention. Therefore, the present invention is not necessarily limited to the positions, sizes, shapes, ranges, etc. disclosed in the drawings and the like.
Elements presented in the singular in the embodiments shall include the plural unless the context clearly dictates otherwise.
<Embodiment>
FIG. 1 is a diagram showing a measuring device according to an embodiment.
A measuring device 100 shown in FIG. 1 is directly attached to a living body, for example. Examples of living organisms include, but are not limited to, fish, reptiles that live in water, and mammals.

For example, methods of attaching the measuring device 100 to fish include internal attachment, in which the measuring device 100 is inserted into the abdominal cavity of the fish, and external attachment, in which the measuring device 100 is attached to the body surface of the fish. In the case of external attachment, there are cases where metal wires, extremities, cable ties, etc. are passed through the body during attachment. In the case of external attachment, there are many cases in which it is generally not suitable for long-term attachment, such as increased fluid resistance and festering wounds at the attachment portion. For this reason, it is generally believed that internal attachment is often more suitable for long-term attachment in fish.
FIG. 2 is a block diagram illustrating functions of the measuring device according to the embodiment.

The measuring device 100 has a control section 1 , a low frequency sampling section 2 , an underwater microphone 3 , a high frequency sampling section 4 , a memory 5 , a data processing section 6 and a data transmission section 7 .
The control unit 1 controls the measuring device 100 as a whole.

The low frequency sampling section 2 has a plurality of sensors. These sensors perform sampling at, for example, a fraction of a Hz to several tens of Hz (for example, about once per second). The low frequency sampling section 2 has an environment sensor section 21 and an action sensor section 22 .

The environment sensor unit 21 collects data on the environment of the living body. Specifically, the environment sensor section 21 has a temperature sensor 211 , a salinity sensor 212 , a dissolved oxygen sensor 213 and an illuminance sensor 214 . A sensor included in the environment sensor unit 21 is not particularly limited, and in addition to the above, a chlorophyll sensor, a turbidity sensor, a pH sensor, an alkali sensor, and the like that can measure the environment can be used.
A temperature sensor 211 detects the temperature of the water in which the measuring device 100 is located.
The salinity sensor 212 detects the salinity in the water in which the measuring device 100 is located.
Dissolved oxygen sensor 213 detects the amount of dissolved oxygen in the water in which measuring device 100 is located.
The illuminance sensor 214 detects the illuminance in the water where the measuring device 100 is located.

The behavior sensor unit 22 collects data on the behavior of the living body. Specifically, the action sensor unit 21 has a speed sensor 221 , an acceleration sensor 222 , a depth sensor 223 , a gyro sensor 224 and a geomagnetic sensor 225 . The sensors included in the behavior sensor unit 22 are not particularly limited, and may include, in addition to the above, an ultrasonic oscillator capable of estimating a position, a depth sounder, an illumination device, and the like.
A speed sensor 221 detects the speed of the living body.
The acceleration sensor 222 detects the acceleration of the living body.
The depth sensor 223 detects the depth of the place where the living body is located.
The gyro sensor 224 detects changes in rotation and orientation of the living body as angular velocities.
A geomagnetic sensor 225 detects the geomagnetism at the location where the living body is located.

It should be noted that the sensors included in the environment sensor unit 21 and the behavior sensor unit 22 described above can be arbitrarily divided. Also, the environment sensor section 21 and the behavior sensor section 22 may each have separate sensors. Some sensors may be omitted The underwater microphone 3 is used when the low-frequency sampling unit 2 and the high-frequency sampling unit 4 sample underwater sounds (artificial sounds, environmental sounds, biological sounds).

A high-frequency sampling unit 4 samples underwater sounds to be observed. These sounds are composed of sound waves in a frequency band from several Hz to several hundred kHz. Therefore, the high-frequency sampling unit 4 performs sampling at a frequency higher than that of the low-frequency sampling unit 2 (for example, several tens of kHz to several hundred kHz). Data obtained by sampling (collected sound data) is stored in the memory 5 .

The data processing unit 6 reads the collected sound data sampled by the high-frequency sampling unit 4 from the memory 5 and performs so-called edge processing. Examples of edge processing include noise processing such as moving average filters and median filters, statistical processing for extracting statistical values (average value, effective value, maximum value, minimum value), and frequency analysis processing such as fast Fourier transform. mentioned. In addition, voice detection and classification are performed using models such as machine learning and deep learning. Edge processing can reduce the amount and time of data transmission.
The data transmission unit 7 transmits the data processed by the data processing unit 6 to, for example, a satellite or a base station. The transmitted data is stored in a cloud server or the like.
Note that the data processing unit 6 and the data transmission unit 7 can also be arranged outside the measurement device 100 .
Next, an example of the operation of the measuring device 100 will be described.
FIG. 3 is a flow chart explaining the operation of the measuring device.
The measuring device 100 performs the following processing each time the low-frequency sampling unit 2 performs sampling.
[Step S1] The control unit 1 performs sampling with each sensor of the low-frequency sampling unit 2 and obtains detection results.

[Step S2] The control unit 1 determines whether or not the high-frequency sampling unit 4 performs sampling based on the detection result of each sensor. Specifically, based on the detection result of each sensor, the control unit 1 determines (a) environmental conditions, (b) depth, (c) horizontal position, (d) shake state of logger, (e) date and time, (f) Determining some or all of the sound, such as sound pressure, background noise level, etc.

(a) Environmental conditions are determined based on the detection results of the temperature sensor 221, the salinity sensor 212, the dissolved oxygen sensor 213, and the illuminance sensor 214. (b) Depth is calculated based on the detection result of the depth sensor 223 . (c) The horizontal position is determined by satellites (GNSS: Global Navigation Satellite System, Argos satellite, Iridium satellite, etc.), radio waves from short-range wireless (LPWA: Low Power Wide Area), etc., and multiple receivers and transmitters of ultrasonic waves. The current position is calculated by checking the time difference between arrival times, inertial navigation (consisting of speed, acceleration, gyro, geomagnetism, depth sensor, etc.), tide and illumination, etc., and the calculated position is stored in advance. By collating the submarine topographic map and the habitat map of marine organisms stored in 5, it is determined whether or not the conditions are met. (d) The shaking state of the logger is determined based on the detection results of the acceleration sensor 222, gyro sensor 224, geomagnetic sensor 225, speed sensor 221, depth sensor 223, and the like. (e) Date and time are obtained by RTC (Real-Time Clock) inside the logger. (f) Sound pressure and background noise level are determined based on the results of sampling by the low-frequency sampling unit 2 using the underwater microphone 3 .
The combination conditions of (a) to (f) and their priorities are stored in the memory 5 in advance depending on the sensor configuration for low-frequency sampling of the device and the purpose of recording.

For example, when the purpose is to detect and classify all underwater sounds (not targeting specific sounds), the only conditions are the depth suitable for underwater sound observation where the effect of water surface reflection is small and the logger's shaking state where the effect of noise is small. can be On the other hand, when targeting specific sounds, the time period when the desired sound is expected to occur (e.g., when targeting nocturnal creatures and activity sounds, target nighttime, artificial sounds of underwater construction, etc.) In the case of daytime, etc.), horizontal/vertical position (for example, the area where the target organism is thought to exist, or the area where the influence of artificial sound is to be evaluated), and the environment (environmental conditions where the target still life is thought to exist) can be an additional condition. For specific examples of each condition, see Example 1-5 below.

The control unit 1 determines whether or not the high-frequency sampling unit 4 should perform sampling based on these calculated results. The criteria for determination are not particularly limited, but the following examples are given.

(Example 1) The depth where the living body is located is within a certain range (for example, a depth that is at least one wavelength of the target sound: Since the wavelength of a 200 Hz sound wave is 7.5 m, the depth is 7.5 m or more from the water surface. ), the control unit 1 determines to execute underwater sound sampling. Marine organisms move from the surface of the water to the bottom of the sea in various ways (changes depending on species, season, time, etc.). On the other hand, in principle, underwater sound cannot exist directly below the water surface due to reflection from the water surface. For this reason, when observing underwater sounds in the environment using marine organisms, it is difficult to measure underwater sounds composed of artificial sounds, environmental sounds, and biological sounds with high quality, even if they are measured near the surface of the water ( Excludes breathing sounds, which are sounds emitted by the attached creature on the surface of the water).

In addition, it is affected by anti-phase reflection from the water surface up to a depth several times the wavelength. Therefore, if the sound pressure is measured while the underwater microphone 3 is submerged at the same distance from the sound source, the received sound pressure fluctuates depending on the water depth. Another reflector for sound propagation in water is the seabed. Since the seafloor is solid, the reflected wave does not undergo phase inversion like the water surface, and it is not a perfect reflector like the water surface. Depending on the geological structure, the sound wave once entering the seafloor may be reflected back at the boundary surface. In shallow waters, the underwater microphone 3 is desirably installed as far away as possible from both the reflection from the water surface and the reflection from the bottom of the water. The distance from the water surface can be ascertained by measuring the depth with a pressure sensor, but the distance from the seabed can be ascertained by measuring the depth using ultrasonic waves or comparing the horizontal position with a bathymetry map. be done.

As described above, marine organisms move in various ways from the surface of the water to the bottom of the sea. Sound can be observed and electric power can be reduced. For reference, FIG. 4 shows an example of depth data obtained from sea turtles.

(Example 2) Furthermore, flow noise may occur during swimming. Whether marine organisms are moving or resting can be detected by an acceleration sensor 222 (several Hz to several tens of Hz) and a depth sensor 223.

It can be judged from the value of (about once per second at most). Therefore, when the change in acceleration or depth per unit time is less than a certain value, it is determined that marine organisms are resting, and the control unit 1 determines to execute underwater sound sampling. As a result, the flow noise of collected sound data can be reduced.

(Example 3) In the coastal area, pulse sounds such as those of the teppo shrimp are generated, but they are not observed offshore to some extent. For this reason, if the observation of underwater sounds in coastal areas is not the target, it is determined whether or not the living body wearing the measuring device 100 has moved offshore. decides to perform underwater sound sampling. As a result, noise in collected sound data can be reduced.

(Example 4) When targeting biological sounds, the distribution of organisms varies depending on environmental information such as water temperature, dissolved oxygen, salinity, and illuminance. It is also conceivable to It is determined whether or not the living body wearing the measuring device 100 has moved to the water area of the target marine environment, and when it is determined that it has moved to the water area of the target marine environment, the control unit 1 determines to execute underwater sound sampling. . This makes it possible to collect sound in the sea area where you want to collect sound.

(Example 5) Underwater sound is also obtained by low-frequency sampling, and the sound pressure and background noise level are determined. 1 determines to perform high frequency sampling of underwater sound. This makes it possible to reduce noise in data to be collected. Further, when underwater sound is sampled by low-frequency sampling, the acoustic characteristics of the specific sound are determined, and if the acoustic characteristics match those previously stored in the memory 5, the control unit 1 performs high-frequency sampling of the underwater sound. (eg, sample the sound at 10 kHz, and if a particular sound signature is observed, sample the sound at 200 kHz). As a result, the specific sound to be collected can be collected efficiently.
According to Examples 1 to 5 described above, it is possible to observe underwater sounds at appropriate (meaningful data can be obtained) timings, and power consumption can be reduced.

When the control unit 1 determines that the high-frequency sampling unit 4 performs sampling (Yes in step S2), the process proceeds to step S3. If it is determined that the high-frequency sampling unit 4 does not perform sampling (No in step S2), the process of FIG. 3 is terminated.
[Step S<b>3 ] Upon receiving the instruction from the control section 1 , the high-frequency sampling section 4 measures underwater sounds using the underwater microphone 3 and stores the obtained collected sound data in the memory 5 .

[Step S4] As described above, the data processing unit 6 reads the collected sound data sampled by the high frequency sampling unit 4 from the memory 5 and performs edge processing.

[Step S5] The data transmission unit 7 transmits the data processed by the data processing unit 6 to, for example, a satellite or a base station. In this embodiment, data processing is performed and data is transmitted each time sampling is performed. However, not limited to this, the timing of data processing and the timing of data transmission may be executed at arbitrary timings.

As described above, according to the measuring device 100 of the embodiment, the low-frequency sampling unit 2 that detects the surrounding environment underwater by sampling about once per second, and the detection result of the low-frequency sampling unit 2 a control unit 1 for determining whether or not to detect underwater sounds according to the above; and when the control unit 1 determines to detect underwater sounds, the underwater sounds are detected at a frequency higher than the sampling frequency of the low-frequency sampling unit 2. and a high-frequency sampling unit 4 that

Generally, underwater sounds (artificial sounds, environmental sounds, and biological sounds) to be observed are composed of sound waves in a frequency band of several Hz to several hundred kHz. Therefore, underwater sounds are often observed at a sampling frequency of tens of thousands to hundreds of thousands of times per second (that is, several tens to hundreds of kHz). On the other hand, pressure sensors, temperature sensors, dissolved oxygen sensors, salinity sensors, etc. that measure the behavior and environment of marine organisms are often observed at a sampling frequency of about once per second at the most. For this reason, power consumption can be reduced if it is possible to determine whether or not to observe underwater sounds with a behavior/environment sensor whose sampling frequency is overwhelmingly small.

In recent years, in the observation of underwater sounds, it is often required to grasp so-called soundscape information, ie, when and to what extent sound sources (artificial sounds, environmental sounds, and biological sounds) are generated. However, since acoustic information is sampled at a higher frequency (up to several 100 kHz) compared to other sensors (temperature, pressure sensors, etc.), the amount of data is large and a large amount of power is required for recording. Since a huge amount of communication time and power is required to transmit a huge amount of data to a cloud server, so-called edge processing, which processes data on the device side, is effective. The measuring device 100 collects collected sound data by sampling underwater sounds with the high-frequency sampling unit 4 in response to triggers caused by the actions of living things or the environment, and processes the collected sound data with the data processing unit 6 to obtain the processed result. By transmitting only to the cloud server, the time and power required for transmission can be reduced. By efficiently collecting sounds only during the required period, there is also the compound effect of reducing the amount of data for data processing on the edge side.

Moreover, it is assumed that the measuring device 100 is not attached to a living organism. For example, the device can be installed in a stationary buoy, a fish tank, or the like. Even in installation-type observations with buoys and fish preserves, by judging whether or not to conduct acoustic observations according to triggers based on the environment and the state of the installed buoys, fish preserves, etc. (swaying state, etc.), long-term observations can be made with a limited battery. It is thought that it can be observed. If power consumption can be reduced, it will not only be possible to improve the total operation period, but it will also be possible to reduce the size of the equipment, which is expected to have the effect of simplifying the handling and installation of the equipment even for fixed-type observation equipment.
FIG. 5 is a diagram illustrating an example of a hardware configuration of the measuring device according to the embodiment;
The measuring apparatus 100 is entirely controlled by a CPU (Central Processing Unit) 101 .
A RAM (Random Access Memory) 102 and a plurality of peripheral devices are connected to the CPU 101 via a bus 106 .

A RAM 102 is used as a main storage device of the measuring device 100 . The RAM 102 temporarily stores at least part of an application program to be executed by the CPU 101 . Various data used for processing by the CPU 101 are stored in the RAM 102 .
Built-in memory 103 , various sensors 104 , underwater microphone 3 and communication interface 105 are connected to bus 106 .

The built-in memory 103 writes and reads data. A built-in memory 103 is used as a secondary storage device of the measuring device 100 . The built-in memory 103 stores application programs and various data. Note that the built-in memory includes, for example, a semiconductor storage device such as a flash memory.
Various sensors 104 are sensors provided in the low-frequency sampling unit 2 and the high-frequency sampling unit 3 described above.

Communication interface 106 may be connected to network 50 . Communication interface 106 transmits and receives data to and from other computers or communication devices via network 50 .
A battery 107 supplies control power to various devices.
The processing functions of this embodiment can be realized by the hardware configuration as described above.

As described above, the measuring apparatus of the present invention has been described based on the illustrated embodiments, but the present invention is not limited to this, and the configuration of each part can be replaced with any configuration having similar functions. can do. Also, other optional components and steps may be added to the present invention.
Moreover, the present invention may be a combination of any two or more configurations (features) of the above-described embodiments.

Note that the processing functions described above can be realized by a computer. In that case, a program describing the processing contents of the functions of the measuring device 100 is provided. By executing the program on a computer, the above processing functions are realized on the computer. A program describing the processing content can be recorded in a computer-readable recording medium. Examples of computer-readable recording media include magnetic storage devices, optical disks, magneto-optical recording media, and semiconductor memories. Magnetic storage devices include hard disk drives, flexible disks (FD), magnetic tapes, and the like. Optical discs include DVD, DVD-RAM, CD-ROM/RW, and the like. Magneto-optical recording media include MO (Magneto-Optical disk) and the like.

When distributing a program, for example, portable recording media such as DVDs and CD-ROMs on which the program is recorded are sold. It is also possible to store the program in the storage device of the server computer and transfer the program from the server computer to another computer via the network.

A computer that executes a program stores, for example, a program recorded on a portable recording medium or a program transferred from a server computer in its own storage device. The computer then reads the program from its own storage device and executes processing according to the program. The computer can also read the program directly from the portable recording medium and execute processing according to the program. In addition, the computer can also execute processing according to the received program every time the program is transferred from a server computer connected via a network.

At least part of the above processing functions can also be implemented by electronic circuits such as DSPs (Digital Signal Processors), ASICs (Application Specific Integrated Circuits), and PLDs (Programmable Logic Devices).

1 control unit 2 low frequency sampling unit 21 environment sensor unit 211 temperature sensor 212 salinity sensor 213 dissolved oxygen sensor 214 illuminance sensor 22 action sensor unit 221 speed sensor 222 acceleration sensor 223 depth sensor 224 gyro sensor 225 geomagnetic sensor 3 underwater microphone 4 high frequency sampling UNIT 5 MEMORY 6 DATA PROCESSING UNIT 7 DATA TRANSMITTER 100 MEASURING DEVICE

Claims (4)

a first detection unit that detects the surrounding environment in water at a first frequency;
a determination unit that determines whether or not to detect underwater sound according to the detection result of the first detection unit;
a second detection unit that detects underwater sound at a frequency higher than the first frequency when the determination unit determines that underwater sound is detected;
A measuring device comprising: The measuring device is attached to a living body,
The first detection unit detects the magnitude of movement of the living body,
2. The measuring device according to claim 1, wherein the determination unit determines to detect an underwater sound when the amount of movement of the living body is equal to or less than a predetermined value. The measuring device is attached to a living body,
The first detection unit detects the position of the living body,
2. The measuring device according to claim 1, wherein the determining unit determines to detect underwater sounds when the living body is positioned at a position that is less susceptible to ambient sounds. The first detection unit detects underwater sound,
2. The measuring device according to claim 1, wherein the determination unit determines to detect an underwater sound when the volume of the detected sound is below a certain level.

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