CN109757419B - Intelligent feeding system and method based on fish feed consumption - Google Patents
Intelligent feeding system and method based on fish feed consumption Download PDFInfo
- Publication number
- CN109757419B CN109757419B CN201910117307.2A CN201910117307A CN109757419B CN 109757419 B CN109757419 B CN 109757419B CN 201910117307 A CN201910117307 A CN 201910117307A CN 109757419 B CN109757419 B CN 109757419B
- Authority
- CN
- China
- Prior art keywords
- feeding
- feed
- control module
- time
- depth map
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 241000251468 Actinopterygii Species 0.000 title claims abstract description 46
- 238000000034 method Methods 0.000 title claims abstract description 20
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 38
- 230000008034 disappearance Effects 0.000 claims description 12
- 230000003238 somatosensory effect Effects 0.000 claims description 3
- 230000008901 benefit Effects 0.000 abstract description 5
- 235000013305 food Nutrition 0.000 abstract description 2
- 230000006399 behavior Effects 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 230000000694 effects Effects 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 230000003993 interaction Effects 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 239000002245 particle Substances 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000009360 aquaculture Methods 0.000 description 1
- 244000144974 aquaculture Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000003086 colorant Substances 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000009313 farming Methods 0.000 description 1
- 230000004634 feeding behavior Effects 0.000 description 1
- 230000037406 food intake Effects 0.000 description 1
- 239000005337 ground glass Substances 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 238000002329 infrared spectrum Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000000149 penetrating effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000036186 satiety Effects 0.000 description 1
- 235000019627 satiety Nutrition 0.000 description 1
- 238000001228 spectrum Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
- Y02A40/80—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in fisheries management
- Y02A40/81—Aquaculture, e.g. of fish
Abstract
The invention discloses an intelligent feeding system based on fish feed consumption, which comprises a camera device, a control module and a feeder; the signal output end of the camera device is connected with the signal input end of the control module, and the control output end of the control module is connected with the control input end of the feeder; the camera device is used for acquiring the feed information of the water surface and sending the feed information to the control module, and the control module is used for generating a control signal of the feeder according to the feed information; the feeder feeds according to the control signal. An intelligent feeding method is that a camera device acquires feed information on the water surface in real time and converts the feed information into a depth map to be sent to a control module; and the control module controls the feeding machine to feed according to the depth map. The advantages are that: the method has the advantages that the feeding amount of the fish can be obtained according to the feed information on the water surface, a proper amount of feed is automatically fed according to the feeding amount, intelligent proper feeding is realized, the feeding cost of the feed is reduced, and meanwhile, the fish can be guaranteed to ingest enough food.
Description
Technical Field
The invention relates to the technical field of intelligent aquaculture, in particular to an intelligent feeding system and method based on fish feed consumption.
Background
Along with the continuous development of the cultivation mode, the industrial circulating water cultivation mode is taken as a novel efficient cultivation mode, and is more and more valued and gradually adopted by cultivation enterprises. In the cultivation process, the most effective feeding of the feed is a key technology for improving cultivation benefits, and the method is a problem to be solved in recent years. Excessive feeding and insufficient feeding can influence the cultivation effect: excessive feeding can cause excessive consumption of feed cost and increase of cultivation cost; meanwhile, the water quality of the culture water body is deteriorated, the growth of fish is affected, and even the death of the fish is caused. However, if the feeding is insufficient, the fish is insufficient to ingest, so that the optimal growth condition is difficult to achieve, and the cultivation effect is affected.
The current aquatic product cultivation is mainly operated manually, the feeding amount of the feed is mainly judged by human experience, the feeding process has great randomness, and excessive feeding or insufficient feeding can cause great negative influence on cultivation, so that the cultivation benefit is reduced. Moreover, with the development of the age, fewer feed delivery technicians working with low labor added value can be involved, and the whole aquatic industry is directly affected.
With the development of technology, research on intelligent feeding has been started. In the previous researches, the feeding system is mostly used for judging the feeding requirement of the fish based on the monitoring of the movement behaviors of the fish, but the defects of the method are that images of the behaviors of the fish are difficult to accurately obtain, and the movement of the fish cannot completely reflect the feeding requirement of the fish.
Disclosure of Invention
In order to solve the problems in the prior art, the invention aims to provide an intelligent feeding system and method based on the consumption of fish feed.
The invention relates to an intelligent feeding system based on fish feed consumption, which comprises a camera device, a control module and a feeder; the signal output end of the camera device is connected with the signal input end of the control module, and the control output end of the control module is connected with the control input end of the feeder; the camera device is used for acquiring feed information of the water surface and sending the feed information to the control module, and the control module is used for generating a control signal of the feeder according to the feed information; and the feeding machine feeds the feed according to the control signal.
Preferably, the control signal controls the feeding machine to start feeding, the camera device acquires the feed information on the water surface in real time and converts the feed information into a depth map, the depth map is sent to the control module, the control module analyzes the ratio of the feed image area in the depth map to the total image area, and when the ratio reaches a preset ratio threshold in the control module, the control module controls the feeding machine to stop feeding.
Preferably, the control signal includes a feeding amount control signal, the control module records a first feeding time t1 required by disappearance of the feed image in the depth map after feeding, when the first feeding time t1 is smaller than a preset time threshold, the control module controls the feeding machine to feed for the second time, records a second feeding time t2 required by disappearance of the feed image in the depth map after feeding for the second time, and when the second feeding time t2 is smaller than the time threshold and larger than the first feeding time t1, the control module adjusts the feeding amount control signal to reduce the feeding amount of the next feeding of the feeding machine.
Preferably, in the depth map, pixels of an image at a certain depth below the water surface are set to a first color, and pixels of images at other depths are set to a second color.
Preferably, the image pickup device comprises an infrared projector, and further comprises a color camera and an infrared camera which are arranged in parallel.
An intelligent feeding method based on fish feed consumption comprises the following steps:
the control module controls the feeder to start feeding feed;
the camera device acquires the feed information of the water surface in real time and converts the feed information into a depth map and sends the depth map to the control module;
and the control module controls the feeding machine to feed according to the depth map.
Preferably, the control module analyzes the ratio of the feed image area in the depth map to the total image area, and when the ratio reaches a preset ratio threshold in the control module, the feeder is controlled to stop feeding feed.
Preferably, the control module records a first feeding time t1 required by disappearance of the feed image in the depth map after feeding, when the first feeding time t1 is smaller than a preset time threshold, the control module controls the feeding machine to feed for the second time, records a second feeding time t2 required by disappearance of the feed image in the depth map after feeding for the second time, and when the second feeding time t2 is smaller than the time threshold and larger than the first feeding time t1, the control module controls the feeding machine to reduce the feeding amount of the next feeding.
The intelligent feeding system and method based on the fish feed consumption have the advantages that the camera device acquires feed information on the water surface, the control module receives the feed information and analyzes and generates control signals, and the operation of the feeder is controlled through the control signals. According to the consumption condition of the water surface feed, the water surface feeding process of the fish can be observed, the required feeding amount of the fish can be accurately obtained, and then a proper amount of feed is put in according to the feeding amount of the fish, so that the intelligentization of the feeding process of the fish is realized. The feed throwing cost is reduced, and the pollution of the feed allowance to the culture water is reduced; meanwhile, the fish can be ensured to ingest enough food.
Only the feed information at the water surface is monitored, and the pixels of the object below the water surface are all set to be the same color, so that the complex background image interference is avoided, and the difficulty of image processing is reduced. The camera device is an infrared camera device, and an infrared light source is adopted, so that the fish-catching device can work all the day, and meanwhile, the emergency response of the strong light source to fish is avoided. The invention can be suitable for circulating water culture and field fishpond culture, and can realize automatic intelligent feeding.
Drawings
FIG. 1 is a schematic diagram of the intelligent feeding system based on the consumption of fish feed;
FIG. 2 is a depth map of the water surface without the feed of the present invention;
FIG. 3 is a depth map of the water surface at the time of feeding according to the present invention;
fig. 4 is a depth map of the water surface after feeding of a fish school according to the invention.
Reference numerals illustrate: the device comprises a 1-control module, a 2-camera device, a 3-feeder, a 4-cultivation box, 5-infrared rays, a part with other depth in a depth map, b-feed and c-fish.
Detailed Description
As shown in fig. 1, the intelligent feeding system based on the fish feed consumption comprises a camera device 2, a control module 1 and a feeder 3; the signal output end of the camera device 2 is connected with the signal input end of the control module 1, and the control output end of the control module 1 is connected with the control input end of the feeder 3; the camera device 2 is used for acquiring feed information of the water surface and sending the feed information to the control module 1, and the control module 1 is used for generating a control signal of the feeder 3 according to the feed information; the feeder 3 feeds according to the control signal.
The camera device 2 is used for monitoring the feeding behavior of fish and the residual feed on the water surface, and the camera device 2 of the embodiment can adopt, but is not limited to, a KINECT 2.0 somatosensory camera of microsoft corporation. The camera is man-machine interaction equipment developed by Microsoft corporation and based on somatosensory interaction, and mainly comprises three components: the infrared projector actively projects near infrared spectrum to irradiate a rough object or after penetrating through ground glass, the spectrum is distorted to form random reflection spots, and the random reflection spots can be read by the infrared camera. And secondly, an infrared camera is used for acquiring infrared light reflected from the surface of the object, and according to the running time of the infrared light from the surface of the object to the camera, namely TOF: and judging the distance between the object and the camera by the Time of Flight, and further acquiring depth information of the surface of the whole object. And the color cameras are used for shooting color video images in a visual angle range, the color cameras and the infrared cameras are placed in parallel, two cameras shoot the same object to generate very close two-dimensional images, but the depth map is different from the pixels of the color map, so that the imaging position of the object has certain offset, and calibration is needed.
The control module 1 is arranged at a PC, a PCI slot on the PC is connected with an NI data acquisition card, the data acquisition card outputs a switch control signal to control the feeder 3 to start working, after the feeder 3 is powered on, feed is put into the cultivation box 4, and fish feed particles are randomly distributed on the water surface of the cultivation box 4. The model of the data acquisition card can be PCI 6520 type data acquisition card.
The control module 1 controls the feeder 3 to start feeding, the camera device 2 acquires feed information on the water surface in real time and converts the feed information into a depth map, the depth map is sent to the control module 1, the control module 1 analyzes the ratio of the feed image area in the depth map to the total image area, and when the ratio reaches a preset ratio threshold in the control module 1, the control module 1 controls the feeder 3 to stop feeding. The amount of feed in the farming box 4 can be accurately reflected by the occupancy of the feed image area in the total image area.
The control signal comprises a feeding amount control signal, the control module 1 records a first feeding time t1 required by disappearance of a feed image in the depth map after feeding, when the first feeding time t1 is smaller than a preset time threshold value, the control module 1 controls the feeding machine 3 to feed for the second time, records a second feeding time t2 required by disappearance of the feed image in the depth map after feeding for the second time, and when the second feeding time t2 is smaller than the time threshold value and larger than the first feeding time t1, the control module 1 adjusts the feeding amount control signal, and reduces the feeding amount of the next feeding of the feeding machine 3. The feed consumption rate can be accurately reflected by the time required for the feed image to disappear, i.e., the feeding time.
In the depth map, pixels of an image at a certain depth below the water surface are set to a first color, and pixels of images at other depths are set to a second color.
The feed image area is obtained by removing the area proportion of fish in the image of the first color. The method can be realized by removing the image area which accords with the characteristics of the fish in the image, and the characteristics of the fish can be the appearance or the movement track.
The camera device 2 comprises an infrared projector, and also comprises a color camera and an infrared camera which are arranged in parallel.
An intelligent feeding method based on fish feed consumption comprises the following steps:
the control module 1 controls the feeder 3 to start feeding feed;
the camera device 2 acquires the feed information of the water surface in real time and converts the feed information into a depth map and sends the depth map to the control module 1;
the control module 1 controls the feeder 3 to feed according to the depth map.
The control module 1 analyzes the ratio of the feed image area in the depth map to the total image area, and when the ratio reaches a preset threshold value in the control module 1, the feeder 3 is controlled to stop feeding feed.
The control module 1 records a first feeding time t1 required by the disappearance of the feed image in the depth map after feeding, when the first feeding time t1 is smaller than a preset time threshold, the control module 1 controls the feeding machine 3 to feed for the second time, records a second feeding time t2 required by the disappearance of the feed image in the depth map after the second feeding, and when the second feeding time t2 is smaller than the time threshold and larger than the first feeding time t1, the control module 1 controls the feeding machine 3 to reduce the feeding amount of the next feeding.
A KINECT 2.0 camera from microsoft corporation was mounted on top of the incubator 4 and photographed perpendicular to the water surface. Because the KINECT 2.0 camera can acquire depth information from the camera to an object on the water surface, the effective shooting distance of the camera needs to be larger than 0.5 meter, the camera is erected at a height of 0.6 meter above the water surface, pixel points with a distance smaller than 0.7 meter in a depth map are set as a first color, and pixel points with a distance larger than 0.7 meter are set as a second color. When there is no feed on the water surface and no fish activity, the entire background is a second color, as shown in fig. 2. The first color and the second color are colors with larger contrast difference. For example, the first color may be red and the second color black. But also dark grey and grey-white as shown in the figure. Color combinations with larger contrast differences can be selected, which is beneficial for the control module 1 to analyze and process the depth map.
In this embodiment, a depth of 10 cm below the water surface is set as a first color in the depth map, and other depths are set as a second color in the depth map.
When the control module 1 controls the feeder 3 to feed, the feed exists on the water surface of the cultivation box 4, the background of the depth map is of the second color, a series of small dots of the first color exist, and the small dots of the first color are the depth map of the feed, as shown in fig. 3. The control module 1 analyzes, when the image area of the first color particles accounts for fifty percent of the total area of the image interface, the control module 1 sends out a control signal to enable the feeder 3 to stop feeding, sends out the control signal, and starts the camera to record the ingestion behavior of fish.
After the feed is put in, the fishes in the culture box 4 can quickly float out of the water surface to snatch, and the snatch behavior of the fishes can be clearly recorded and analyzed by an image processing method, so that the snatch time of the fishes is recorded. After the feeding is finished, the feed consumption is finished, the first color dots on the water surface gradually disappear, and the effect of approaching the feeding completion is shown in fig. 4.
The camera device 2 and the control module 1 record the whole feeding-robbing behavior and time, if the fed feed is quickly and robbed, namely, the first color point quickly disappears, which means that the fish has strong feeding desire, the control module 1 controls the feeder 3 to work again, the feed is fed into the cultivation box 4 continuously, then the time of the feed consumption of the fish is recorded again, if the feeding time becomes long, which means that the fish enters a basic satiety state, the feeding amount is gradually reduced until the feeding is stopped completely.
It will be apparent to those skilled in the art from this disclosure that various other changes and modifications can be made which are within the scope of the invention as defined in the appended claims.
Claims (5)
1. An intelligent feeding system based on fish feed consumption is characterized by comprising a camera device (2), a control module (1) and a feeder (3); the signal output end of the camera device (2) is connected with the signal input end of the control module (1), and the control output end of the control module (1) is connected with the control input end of the feeder (3); the camera device (2) is used for acquiring feed information of the water surface and sending the feed information to the control module (1), and the control module (1) is used for generating a control signal of the feeder (3) according to the feed information; the feeder (3) feeds feed according to the control signal; the camera device (2) is a somatosensory camera;
the control module (1) controls the feeder (3) to start feeding, the camera device (2) acquires feed information on the water surface in real time and converts the feed information into a depth map and sends the depth map to the control module (1), the control module (1) analyzes the ratio of the feed image area in the depth map to the total image area, and when the ratio reaches a preset ratio threshold in the control module (1), the control module (1) controls the feeder (3) to stop feeding;
the control signals comprise feeding amount control signals, the control module (1) records a first feeding time t1 required by disappearance of a feed image in a depth map after feeding, when the first feeding time t1 is smaller than a preset time threshold value, the control module (1) controls the feeding machine (3) to feed for the second time, records a second feeding time t2 required by disappearance of the feed image in the depth map after the second feeding, and when the second feeding time t2 is smaller than the time threshold value and larger than the first feeding time t1, the control module (1) adjusts the feeding amount control signals to reduce the feeding amount of the next feeding of the feeding machine (3);
in the depth map, pixels of an image at a certain depth below the water surface are set to a first color, and pixels of images at other depths are set to a second color.
2. The intelligent feeding system based on the fish feed consumption according to claim 1, wherein the camera device (2) comprises an infrared projector, and further comprises a color camera and an infrared camera which are arranged in parallel.
3. A method of using the intelligent feeding system based on fish feed consumption according to any one of claims 1-2, comprising the steps of: the control module (1) controls the feeder (3) to start feeding feed; the camera device (2) acquires the feed information of the water surface in real time and converts the feed information into a depth map and sends the depth map to the control module (1); the control module (1) controls the feeding machine (3) to feed according to the depth map.
4. An intelligent feeding method based on fish feed consumption according to claim 3, wherein the control module (1) analyzes the ratio of the feed image area in the depth map to the total image area, and when the ratio reaches a preset ratio threshold in the control module (1), the feeder (3) is controlled to stop feeding feed.
5. An intelligent feeding method based on the consumption of fish feed according to claim 3, wherein the control module (1) records a first feeding time t1 required by the disappearance of the feed image in the depth map after feeding, when the first feeding time t1 is smaller than a preset time threshold, the control module (1) controls the feeding machine (3) to feed for the second time, records a second feeding time t2 required by the disappearance of the feed image in the depth map after feeding for the second time, and when the second feeding time t2 is smaller than the time threshold and larger than the first feeding time t1, the control module (1) controls the feeding machine (3) to reduce the feeding amount of the next feeding.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910117307.2A CN109757419B (en) | 2019-02-15 | 2019-02-15 | Intelligent feeding system and method based on fish feed consumption |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910117307.2A CN109757419B (en) | 2019-02-15 | 2019-02-15 | Intelligent feeding system and method based on fish feed consumption |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109757419A CN109757419A (en) | 2019-05-17 |
| CN109757419B true CN109757419B (en) | 2023-12-22 |
Family
ID=66456751
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910117307.2A Active CN109757419B (en) | 2019-02-15 | 2019-02-15 | Intelligent feeding system and method based on fish feed consumption |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109757419B (en) |
Families Citing this family (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110415209A (en) * | 2019-06-12 | 2019-11-05 | 东北农业大学 | A kind of cow feeding quantity monitoring method based on the estimation of light field space or depth perception |
| CN110583550B (en) * | 2019-09-20 | 2021-11-09 | 重庆工商大学 | Accurate feeding system and device are bred to fish shrimp sea cucumber based on target detection and tracking |
| CN111436386A (en) * | 2020-04-07 | 2020-07-24 | 玉林师范学院 | Swimming type cultured fish culture method and system based on ingestion intensity measurement |
| CN111857208B (en) * | 2020-06-10 | 2021-05-25 | 太原市高远时代科技有限公司 | Intelligent aquarium monitoring and protecting system based on NB-IoT technology |
| CN112931356B (en) * | 2021-02-09 | 2022-04-15 | 自然资源部第一海洋研究所 | Intelligent on-demand feeding device for aquaculture and operation method |
| CN112931355B (en) * | 2021-02-09 | 2022-04-15 | 自然资源部第一海洋研究所 | Method for automatically throwing bait on demand based on acoustic monitoring |
| CN115777608B (en) * | 2022-12-19 | 2023-11-17 | 佛山渔汇智慧渔业科技有限公司 | Aquatic product circulating water culture system based on intelligent control |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000201568A (en) * | 1999-01-18 | 2000-07-25 | Hitachi Ltd | Automatic feeding system for aquatic organism |
| CN104542411A (en) * | 2014-12-19 | 2015-04-29 | 浙江大学 | Intelligent bait feeding device and method based on image processing technology |
| CN107094683A (en) * | 2017-04-13 | 2017-08-29 | 同济大学 | The Autoamtic bait putting and water quality monitoring control system and method for a kind of aquaculture |
| CN107372267A (en) * | 2017-08-11 | 2017-11-24 | 浙江大学 | A kind of intelligent feeding system based on swimming type Fish behavior profile feedback |
| CN107590467A (en) * | 2017-09-14 | 2018-01-16 | 中国水产科学研究院渔业机械仪器研究所 | A kind of intelligence based on machine vision feeds system |
| CN209660186U (en) * | 2019-02-15 | 2019-11-22 | 玉林师范学院 | A kind of intelligent feeder based on fish meal consumption |
-
2019
- 2019-02-15 CN CN201910117307.2A patent/CN109757419B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000201568A (en) * | 1999-01-18 | 2000-07-25 | Hitachi Ltd | Automatic feeding system for aquatic organism |
| CN104542411A (en) * | 2014-12-19 | 2015-04-29 | 浙江大学 | Intelligent bait feeding device and method based on image processing technology |
| CN107094683A (en) * | 2017-04-13 | 2017-08-29 | 同济大学 | The Autoamtic bait putting and water quality monitoring control system and method for a kind of aquaculture |
| CN107372267A (en) * | 2017-08-11 | 2017-11-24 | 浙江大学 | A kind of intelligent feeding system based on swimming type Fish behavior profile feedback |
| CN107590467A (en) * | 2017-09-14 | 2018-01-16 | 中国水产科学研究院渔业机械仪器研究所 | A kind of intelligence based on machine vision feeds system |
| CN209660186U (en) * | 2019-02-15 | 2019-11-22 | 玉林师范学院 | A kind of intelligent feeder based on fish meal consumption |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109757419A (en) | 2019-05-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109757419B (en) | Intelligent feeding system and method based on fish feed consumption | |
| CN107094683B (en) | Automatic feeding and water quality monitoring control system for aquaculture | |
| US20210279860A1 (en) | Adaptive Feeding Device and Method for Swimming Fish Based on Photo-acoustic Coupling Technology | |
| CN109717120A (en) | A kind of fish culture monitoring feeding system and method based on Internet of Things | |
| JP3101938B2 (en) | Automatic feeding device and method for aquatic organisms | |
| WO2020046524A1 (en) | Automatic feed pellet monitoring based on camera footage in an aquaculture environment | |
| CN104123721B (en) | A kind of shoal of fish based on video streaming image distributed dynamic feature technology feeds autocontrol method | |
| US10935783B1 (en) | Optical system for capturing digital images in an aquaculture environment in situ | |
| US9691144B2 (en) | System and method for counting zooplankton | |
| CN111436386A (en) | Swimming type cultured fish culture method and system based on ingestion intensity measurement | |
| CN104542411A (en) | Intelligent bait feeding device and method based on image processing technology | |
| CN111161214B (en) | System and method for measuring pig weight and identifying drinking behavior based on binocular vision | |
| CN109380146A (en) | Live pig self-operated measuring unit and method | |
| Janssen | Searching for zooplankton just outside Snell's window 1 | |
| CN110089477A (en) | A kind of fish welfare intelligent cultivation system and method for circulating water cultivation mode | |
| DE102018217164A1 (en) | Device, method and system for data analysis | |
| CN209660186U (en) | A kind of intelligent feeder based on fish meal consumption | |
| CN113875670B (en) | Intelligent aquatic product accurate feeding platform and feeding method based on sonar array and visual identification | |
| DE102018215096A1 (en) | Autonomous underwater vehicle to support fishing | |
| CN208187400U (en) | A kind of long measuring device of Fish based on machine vision | |
| CN108121968B (en) | Fish shoal monitoring method | |
| Pedersen et al. | No machine learning without data: Critical factors to consider when collecting video data in marine environments | |
| Chidami et al. | Underwater infrared video system for behavioral studies in lakes | |
| CN114092687A (en) | Animal feeding device and method based on visual identification and readable storage medium | |
| US20240071072A1 (en) | Microplastics detector sensor coupling and data training |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |