CN113854222B - Intelligent feeding control method - Google Patents
Intelligent feeding control method Download PDFInfo
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- CN113854222B CN113854222B CN202111275107.3A CN202111275107A CN113854222B CN 113854222 B CN113854222 B CN 113854222B CN 202111275107 A CN202111275107 A CN 202111275107A CN 113854222 B CN113854222 B CN 113854222B
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01K—ANIMAL HUSBANDRY; CARE OF BIRDS, FISHES, INSECTS; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
- A01K61/00—Culture of aquatic animals
- A01K61/80—Feeding devices
- A01K61/85—Feeding devices for use with aquaria
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30242—Counting objects in image
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- 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 relates to the technical field of intelligent fish farming, in particular to an intelligent feeding control method, which comprises the following steps: s1, acquiring image information and feeding parameters in a fish tank; s2, identifying the types of the fishes in the image information, acquiring preset feeding conditions corresponding to the types of the fishes, and judging whether feeding parameters meet the preset feeding conditions or not: if the feeding parameters meet the preset feeding conditions, S3 is carried out; if the feeding parameters do not meet the preset feeding conditions, returning to S1; s3, determining the quantity and the body length of each kind of fish; s4, determining the type of the fed fish according to the type of the fish, and determining the required feeding fish throwing amount according to the quantity and the body length of the fish; s5, uniformly feeding the fish into the fish tank according to the fish type and the fish feeding amount. According to the invention, the type of the fed fish material is determined according to the type of the fish, and the feeding amount of the fed fish material is determined according to the number and the body length of the fish, so that excessive or insufficient feeding of the fish material can be avoided, and the accuracy of the feeding amount of the fish material is improved.
Description
Technical Field
The invention relates to the technical field of intelligent fish farming, in particular to an intelligent feeding control method.
Background
With the continuous improvement of living standard, more and more people culture ornamental fish at home. Although fish farming brings little fun to life, fish needs to be fed frequently. When the fish is busy or travels, no one is at home, the fish cannot be fed in time.
In this way, the intelligent fish culture control technology can be utilized to automatically manage the fish tank, so that the fish tank is convenient for people to automatically feed when no people exist in the home. For example, automatic feeding control is realized through a controller, the controller is matched with a camera, a convolutional neural network and a model are built in the controller, the types and the numbers of fish in a fish tank are identified through an image identification technology, and the purposes of accurate feeding and ornamental enhancement are achieved; therefore, automatic control and local control can be realized through the controller, and the fish tank can be remotely observed through the remote intelligent monitoring equipment and controlled to perform corresponding operation, so that full-automatic control of feeding of the fish tank is realized.
Because the fish feed required to be fed by different kinds of fish is different, the ideal feeding mode should feed the corresponding fish feed to the different kinds of fish in a targeted manner; in addition, the fish with different sizes has different requirements on fish materials, and generally, the fish with larger body length needs more fish materials, the fish with smaller body length needs less fish materials, and the ideal feeding mode should ensure that the amount of the fish materials put in is in direct proportion to the body length of the fish. However, in the prior art, different kinds of fishes are not fed with corresponding fish materials in a targeted manner, and it is difficult to ensure that the amount of the fish materials put in is proportional to the body length of the fishes. Therefore, the feeding amount of the fish feed is inaccurate, the situation that the fed fish feed is too much or too little is likely to occur, the growth of the fish is not facilitated due to the too little fish feed, and unnecessary waste can occur due to the too much fish feed.
Disclosure of Invention
The invention provides an intelligent feeding control method, which solves the technical problem of inaccurate fish feed delivery in the prior art.
The basic scheme provided by the invention is as follows: the intelligent feeding control method comprises the following steps:
s1, acquiring image information and feeding parameters in a fish tank;
s2, identifying the types of the fishes in the image information, acquiring preset feeding conditions corresponding to the types of the fishes, and judging whether feeding parameters meet the preset feeding conditions or not: if the feeding parameters meet the preset feeding conditions, S3 is carried out; if the feeding parameters do not meet the preset feeding conditions, returning to S1;
s3, determining the quantity and the body length of each kind of fish;
s4, determining the type of the fed fish according to the type of the fish, and determining the required feeding fish throwing amount according to the quantity and the body length of the fish;
s5, uniformly feeding the fish into the fish tank according to the fish type and the fish feeding amount.
The working principle and the advantages of the invention are as follows:
(1) The feeding parameters in the fish tank are obtained, feeding is performed when the feeding parameters meet preset feeding conditions, and compared with the feeding conditions which are not considered in the prior art, the feeding conditions in the fish tank are ensured to be proper feeding conditions when feeding is performed directly, and the proper feeding conditions enable the fish to perform optimal biological activities (such as swimming) and optimal physiological activities (such as digestion), so that the fish can fully absorb fish materials, the fish growth is facilitated, and meanwhile, the waste of the fish materials is reduced;
(2) The method comprises the steps of acquiring image information in a fish tank, identifying the types of fish in the image information, determining the types of fed fish according to the types of the fish, wherein the types of the fish correspond to the types of the fish, ensuring the pertinence of the fish, and compared with the prior art that the fish is fed directly without considering the types of the fish, ensuring the 'best' feeding process, so that the types of the fish correspond to the types of the fish, not only preventing the waste of the fish, but also avoiding the misfeeding of the fish which does not correspond to the types of the fish, thereby avoiding the physiological poor of the fish caused by misfeeding; in addition, the types of the fishes correspond to the types of the fishes, the fishes only approach to the corresponding fishes, the phenomenon that the fishes are clustered and piled up in the feeding process is avoided, and the time for the fishes to eat the fishes is prolonged due to the fact that the fishes are clustered and piled up, so that the clustered and piled up fishes are reduced, the fishes can eat the fishes quickly, and the feeding efficiency is improved;
(3) The method comprises the steps of acquiring image information in a fish tank, determining the quantity and the body length of various fishes, determining the feeding fish feed throwing amount according to the quantity and the body length of the fishes, avoiding the situation that the throwing fish feed is too much or too little, and improving the accuracy of the fish feed throwing amount; meanwhile, the phenomenon that the big fish eats small fish due to too little fish feed is avoided, the mixed feeding of various fishes is facilitated, and the feeding efficiency is improved.
According to the invention, the type of the fed fish material is determined according to the type of the fish, and the feeding amount of the fed fish material is determined according to the number and the body length of the fish, so that excessive or insufficient feeding of the fish material can be avoided, and the accuracy of the feeding amount of the fish material is improved.
Further, in S4, the particle size of the fed fish feed is determined according to the body length of the fish, and the particle size of the fish feed is in direct proportion to the body length of the fish.
The beneficial effects are that: the fish with different body lengths have different volumes and sizes, and the chewing capacity of the large fish with larger volumes to the fish materials is generally stronger than that of the small fish with smaller volumes, so that the fish materials can be ensured to be chewed by the fish.
Further, in S4, the hardness of the fed fish material is determined according to the body length of the fish, and the hardness of the fish material is in direct proportion to the body length of the fish.
The beneficial effects are that: similarly, the digestion capability of the large fish with larger volume to the fish material is stronger than that of the small fish with smaller volume, so that the fish material can be quickly digested and absorbed by the fish.
Further, in S4, the feeding times of feeding are determined according to the body length of the fish, the single feeding amount is determined according to the feeding times and the feeding amount of the fish, and the feeding times are inversely proportional to the body length of the fish; and S5, feeding the fish tank according to the feeding times and the single feeding amount.
The beneficial effects are that: generally, the speed of the large fish with larger volume for eating the fish is faster than that of the small fish with smaller volume, after the fish feeding amount is determined, the more the feeding times are, the less the single feeding amount is, so that most of the fish fed each time can be eaten by the fish.
Further, in S2, whether the remaining fish material exists in the fish tank is identified according to the image information: if the fish tank does not contain residual fish materials, S3 is carried out; if the residual fish materials exist in the fish tank, returning to S1.
The beneficial effects are that: the fish bowl is fed when the residual fish materials do not exist in the fish bowl, so that the fish materials are prevented from being wasted as much as possible, and the feeding efficiency is improved.
Further, in S5, the fish material is put in accordance with a preset putting time interval, which is inversely proportional to the speed of the fish chewing the fish material.
The beneficial effects are that: ensures that the fish feed is eaten by fish in time, and avoids the phenomenon that the fed fish feed cannot be eaten by fish fast and is sunk or swelled by water.
Further, in S1, image information and feeding parameters in the fish tank are obtained according to a preset collection time interval.
The beneficial effects are that: therefore, whether residual fish materials exist in the fish tank or not can be timely found, and further feeding is timely carried out.
Further, in S1, the feeding parameters include water temperature, oxygen content and PH.
The beneficial effects are that: different fish have different requirements on water temperature, oxygen content and PH value, so that the environment in the fish tank is suitable for fish survival as much as possible.
Further, in S2, the image information is scaled according to a preset scaling ratio.
The beneficial effects are that: thus, the image with the required resolution can be obtained, and the accurate identification is convenient.
Further, in S2, if the feeding parameters do not meet the preset feeding conditions, the feeding parameters are adjusted until the feeding parameters meet the preset feeding conditions, and then S3 is performed.
The beneficial effects are that: if the feeding parameters do not meet the preset feeding conditions, the feeding parameters are adjusted, and the feeding can still be performed in time.
Drawings
FIG. 1 is a flow chart of an embodiment of the intelligent feeding control method of the present invention.
Detailed Description
The following is a further detailed description of the embodiments:
example 1
An embodiment is substantially as shown in fig. 1, comprising:
s1, acquiring image information and feeding parameters in a fish tank;
s2, identifying the types of the fishes in the image information, acquiring preset feeding conditions corresponding to the types of the fishes, and judging whether feeding parameters meet the preset feeding conditions or not: if the feeding parameters meet the preset feeding conditions, S3 is carried out; if the feeding parameters do not meet the preset feeding conditions, returning to S1;
s3, determining the quantity and the body length of each kind of fish;
s4, determining the type of the fed fish according to the type of the fish, and determining the required feeding fish throwing amount according to the quantity and the body length of the fish;
s5, uniformly feeding the fish into the fish tank according to the fish type and the fish feeding amount.
The specific implementation process is as follows:
s1, acquiring image information and feeding parameters in the fish tank. In this embodiment, the image information and feeding parameters in the fish tank are obtained according to a preset collection time interval, for example, 5 minutes; the camera is used for collecting image information in the fish tank, the image information comprises images of the water surface of the fish tank and images in water collected from different angles, and the images can comprehensively reflect the conditions in the fish tank; the feeding parameters comprise water temperature, oxygen content and PH value, for example, a temperature sensor is adopted to obtain the water temperature in the fish tank, a dissolved oxygen sensor is adopted to obtain the oxygen content of the water in the fish tank, and a PH measuring sensor is adopted to obtain the PH value of the water in the fish tank.
S2, identifying the types of the fishes in the image information, acquiring preset feeding conditions corresponding to the types of the fishes, and judging whether feeding parameters meet the preset feeding conditions or not: if the feeding parameters meet the preset feeding conditions, S3 is carried out; and if the feeding parameters do not meet the preset feeding conditions, returning to S1.
In this embodiment, the preset feeding conditions are also suitable feeding conditions, since the suitable feeding conditions for different kinds of fish are different. For example, the proper PH value of cold water fish (koi carp, grass carp, salmon, dragon fish and the like) is between 6.8 and 7.5, the proper oxygen content is between 6 and 8mg/L, the proper water temperature is between 20 and 25 ℃, and the water changing temperature difference is not more than 3 ℃; however, the proper PH value of the medium-sized hairtail (silver drum, blue shark, parrot fish, momordica grosvenori and the like) is between 6.5 and 7.1, the proper oxygen content is between 6 and 8mg/L, the proper water temperature is between 26 and 30 ℃, the optimal temperature is 28 ℃, and the temperature difference before and after water change is not more than 1 degree. Firstly, scaling the image information according to a preset scaling ratio to obtain the required resolution, and further obtaining the scaled image information; then, an image recognition algorithm is adopted to recognize the type of fish in the image information, for example, whether the fish in the fish tank is a cold water fish or a medium-sized tropical fish; then, obtaining preset feeding conditions corresponding to the species of the fish, for example, if the fish in the fish tank is cold water fish, the preset feeding conditions are that the PH value is between 6.8 and 7.5, the oxygen content is between 6 and 8mg/L, the water temperature is between 20 and 25 ℃, and if the fish in the fish tank is medium-sized tropical fish, the preset feeding conditions are that the PH value is between 6.5 and 7.1, the oxygen content is between 6 and 8mg/L, and the water temperature is between 26 and 30 ℃; finally, judging whether the feeding parameters meet preset feeding conditions, for example, if the fish in the fish tank is cold water fish, judging whether the PH value is between 6.8 and 7.5, the oxygen content is between 6 and 8mg/L and the water temperature is between 20 and 25 degrees one by one, if the feeding parameters meet the preset feeding conditions, carrying out S3, otherwise, if the feeding parameters do not meet the preset feeding conditions, returning to S1.
S3, determining the number and the body length of each kind of fish. In this example, it is assumed that there are two kinds of fish in the fish tank, which are denoted as a-kind fish and B-kind fish. For the A fishes, the number of the A fishes can be obtained through an image recognition algorithm and a statistical algorithm and is marked as N; the body length of each fish A can also be obtained through an image recognition algorithm, and is marked as Lj, wherein Lj is the body length of the fish A, and j is more than or equal to 1 and less than or equal to N. Similarly, for the B fishes, the number of the B fishes can be obtained through an image recognition algorithm and a statistical algorithm and is marked as M; the body length of each B-type fish can also be obtained through an image recognition algorithm, and is marked as Ki, wherein Ki is the body length of the ith B-type fish, i is more than or equal to 1 and less than or equal to M.
S4, determining the type of the fed fish according to the type of the fish, and determining the required feeding fish throwing amount according to the quantity and the body length of the fish. In the embodiment, firstly, the type of the fed fish materials is determined according to the type of the fish, and for the A-type fish and the B-type fish, the two fish only eat the fish materials favored by the fish, the type of the fish materials favored by the A-type fish is a fish material A, and the type of the fish materials favored by the B-type fish is a fish material B; then, determining the fish feed feeding amount according to the number and the body length of the fish, wherein the fish feed feeding amount Q1=alpha×ΣLjof the fish feed, and alpha is a coefficient obtained in advance according to the eating habits of A fishes, and j is more than or equal to 1 and less than or equal to N; the fish feed amount q2=β×Σki of the fish feed B, and β is a coefficient obtained in advance from the feeding habit of B fish species, and i is 1.ltoreq.i.ltoreq.m. The advantages are two: firstly, the types of fish materials correspond to the types of fish, so that the pertinence of the fish materials is ensured; secondly, the fish feed throwing amount is determined according to the number and the body length of the fish, so that the fish feed throwing amount is in direct proportion to the number and the body length of the fish, the situation that the thrown fish feed is too much or too little is avoided, and the accuracy of the fish feed throwing amount is improved.
Further, in the present embodiment, the particle size of the fed fish, the hardness of the fish, and the feeding number are determined according to the body length of the fish, specifically as follows:
firstly, determining the particle size of the fed fish according to the body length of the fish. For example, for the feed, r1=γ1×Σlj/N, R1 is the feed particle size of the feed, γ1 is a coefficient obtained in advance according to the eating habit of a fish, 1.ltoreq.j.ltoreq.n; similarly, for fish feed B, r2=γ2×Σli/M, R2 is the fish feed particle diameter of fish feed B, γ2 is a coefficient obtained in advance from the eating habit of B fish, 1.ltoreq.i.ltoreq.m. Thus, as the volumes of the fishes with different body lengths are different, the chewing capacity of the large fishes with larger volumes on the fish materials is generally stronger than that of the small fishes with smaller volumes, so that the particle size of the fish materials is in direct proportion to the body length of the fishes (the average body length is also referred to herein) and the fish materials can be ensured to be chewed by the fishes.
Secondly, the hardness of the fed fish material is determined according to the body length of the fish. For example, for the fish feed, b1=δ1×Σlj/N, B1 is the fish feed hardness of the fish feed, δ1 is a coefficient obtained in advance according to the eating habit of a fish, 1.ltoreq.j.ltoreq.n; similarly, for fish feed B, b2=δ2×Σli/M, B2 is the fish feed hardness of fish feed B, δ2 is a coefficient obtained in advance from the feeding habit of B fish, 1.ltoreq.i.ltoreq.m. Thus, since the digestion of the fish by the large fish with a larger volume is stronger than that of the small fish with a smaller volume, the hardness of the fish is in direct proportion to the body length of the fish (also referred to herein as the average body length), and the fish can be ensured to be rapidly digested and absorbed by the fish.
Thirdly, the feeding times of feeding are determined according to the body length of the fish, and the single feeding amount is determined according to the feeding times and the feeding amount of the fish. For example, for the fingerling, t1=ζ1× (1/Σlj/N), T1 is the feeding number of the fingerling, ζ1 is a coefficient obtained in advance according to the eating habit of a fish, 1+.j+.n, single-shot dose q1=q1/T1; similarly, for fish feed B, t2=ζ2× (1/Σli/M), T2 is the number of feeding times of fish feed B, ζ2 is a coefficient obtained in advance according to the feeding habit of B fish, 1.ltoreq.i.ltoreq.m, and single-shot dose q2=q2/T2. Generally, the speed of the large fish with larger volume for eating the fish is faster than that of the small fish with smaller volume, after the fish feed amount is determined, the feeding times are more, the single feed amount is less, so that the feeding times are inversely proportional to the body length of the fish, and most of the fish fed each time can be eaten by the fish.
S5, uniformly feeding the fish into the fish tank according to the fish type and the fish feeding amount. In the embodiment, the fish material is put in and evenly scattered on the water surface in the fish tank; for the first fish material, the particle size of the fish material is R1, the hardness of the fish material is B1, the single-time throwing amount is q1, and the throwing times are T1; for the fish material B, the particle size of the fish material is R2, the hardness of the fish material is B2, the single-time adding amount is q2, and the adding times are T2. In addition, whether the first fish material or the second fish material is fed, the fish material is fed according to a preset feeding time interval, the preset feeding time interval is inversely proportional to the speed of the fish chewing the fish material, the preset feeding time interval can be determined according to the experience of artificial feeding, the fish material is ensured to be timely eaten by the fish, and the phenomenon that the fed fish material cannot be eaten fast and is sunk or swelled by water is avoided.
Example 2
The difference from embodiment 1 is only that, in S2, an image recognition algorithm is used to recognize whether the remaining fish material exists in the fish tank according to the image information: if the fish tank does not contain residual fish materials, S3 is carried out; if the residual fish materials exist in the fish tank, returning to S1. Therefore, the fish bowl is fed when the residual fish materials do not exist in the fish bowl, the fish materials can be prevented from being wasted as much as possible, and the feeding efficiency is improved.
Example 3
The difference from example 2 is only that in S2, if the feeding parameters do not meet the preset feeding conditions, the feeding parameters are adjusted until the feeding parameters meet the preset feeding conditions, and then S3 is performed. For example, if the fish in the fish tank is cold water fish, the PH value is adjusted to be between 6.8 and 7.5, the oxygen content is between 6 and 8mg/L, and the water temperature is between 20 and 25 ℃; if the fish in the fish tank is medium-sized hairtail, the PH value is adjusted to be between 6.5 and 7.1, the oxygen content is between 6 and 8mg/L, and the water temperature is between 26 and 30 ℃. Thus, if the feeding parameters do not meet the preset feeding conditions, the feeding parameters are adjusted, and the feeding can still be performed in time.
The foregoing is merely an embodiment of the present invention, and a specific structure and characteristics of common knowledge in the art, which are well known in the scheme, are not described herein, so that a person of ordinary skill in the art knows all the prior art in the application day or before the priority date of the present invention, and can know all the prior art in the field, and have the capability of applying the conventional experimental means before the date, so that a person of ordinary skill in the art can complete and implement the present embodiment in combination with his own capability in the light of the present application, and some typical known structures or known methods should not be an obstacle for a person of ordinary skill in the art to implement the present application. It should be noted that modifications and improvements can be made by those skilled in the art without departing from the structure of the present invention, and these should also be considered as the scope of the present invention, which does not affect the effect of the implementation of the present invention and the utility of the patent. The protection scope of the present application shall be subject to the content of the claims, and the description of the specific embodiments and the like in the specification can be used for explaining the content of the claims.
Claims (5)
1. The intelligent feeding control method is characterized by comprising the following steps:
s1, acquiring image information and feeding parameters in a fish tank;
s2, identifying the types of the fishes in the image information, acquiring preset feeding conditions corresponding to the types of the fishes, and judging whether feeding parameters meet the preset feeding conditions or not: if the feeding parameters meet the preset feeding conditions, S3 is carried out; if the feeding parameters do not meet the preset feeding conditions, returning to S1;
s3, determining the quantity and the body length of each kind of fish;
s4, determining the type of the fed fish according to the type of the fish, and determining the required feeding fish throwing amount according to the quantity and the body length of the fish;
s5, uniformly feeding the fish in the fish tank according to the type and the feeding amount of the fish;
s4, determining the particle size, the hardness and the feeding times of the fed fish according to the body length of the fish:
the particle size of the fed fish feed is determined according to the body length of the fish, and the particle size is specifically as follows: r=γ×Σlj/N, R is the fish feed particle size, γ is a coefficient obtained in advance according to the eating habit of fish;
the hardness of the fed fish material is determined according to the body length of the fish, and the method comprises the following steps: b=δ×Σlj/N, B being the fish feed hardness, δ being a coefficient obtained in advance from the eating habit of the fish;
the feeding times of feeding are determined according to the body length of the fish, and the single feeding amount is determined according to the feeding times and the feeding amount of the fish, and specifically comprises the following steps: t=ζ× (1/Σlj/N), T is the number of feeding of the fish feed, ζ is a coefficient obtained in advance according to the eating habit of the fish, q=q/T, Q is a single dose;
wherein j is more than or equal to 1 and less than or equal to N, and N is the number of fish;
s5, feeding the fish tank according to the feeding times and the single feeding amount;
s2, identifying whether residual fish materials exist in the fish tank according to the image information: if the fish tank does not contain residual fish materials, S3 is carried out; if the residual fish materials exist in the fish tank, returning to S1;
and S5, throwing the fish according to a preset throwing time interval, wherein the preset throwing time interval is inversely proportional to the speed of the fish for chewing the fish.
2. The intelligent feeding control method according to claim 1, wherein in S1, image information and feeding parameters in the fish tank are obtained according to a preset collection time interval.
3. The intelligent feeding control method according to claim 2, wherein in S1, the feeding parameters include water temperature, oxygen content and PH.
4. The intelligent feeding control method according to claim 3, wherein in S2, the image information is scaled according to a preset scaling ratio.
5. The intelligent feeding control method according to claim 4, wherein in S2, if the feeding parameters do not meet the preset feeding conditions, the feeding parameters are adjusted until the feeding parameters meet the preset feeding conditions, and then S3 is performed.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3188617U (en) * | 2013-11-15 | 2014-01-30 | サン・アンド・シイ・コンサルタント株式会社 | Artificial fishing reef mainly made of farm sludge |
| CN110313560A (en) * | 2019-08-07 | 2019-10-11 | 烟台海益苗业有限公司 | Special bait for naked canopy larvae, preparation method and shaping device |
| CN112604593A (en) * | 2021-01-05 | 2021-04-06 | 南京文魅绘贸易有限公司 | Bait stirring and making equipment for fishing |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| JP3101938B2 (en) * | 1996-03-27 | 2000-10-23 | 株式会社日立製作所 | Automatic feeding device and method for aquatic organisms |
| CN105052804B (en) * | 2015-07-23 | 2017-10-20 | 青岛农业大学 | A kind of bait feeding system of body length based on shrimp |
| CN106719115A (en) * | 2016-10-26 | 2017-05-31 | 陈鸽 | Intelligent fish feeding method and device |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3188617U (en) * | 2013-11-15 | 2014-01-30 | サン・アンド・シイ・コンサルタント株式会社 | Artificial fishing reef mainly made of farm sludge |
| CN110313560A (en) * | 2019-08-07 | 2019-10-11 | 烟台海益苗业有限公司 | Special bait for naked canopy larvae, preparation method and shaping device |
| CN112604593A (en) * | 2021-01-05 | 2021-04-06 | 南京文魅绘贸易有限公司 | Bait stirring and making equipment for fishing |
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