KR20230078348A - An Intergrated Service System for Smart Fish Farm - Google Patents

Abstract

The present invention relates to a smart aquaculture integrated service system, and more specifically, to analyze diseases and growth conditions of farmed fish by receiving farm information, and providing the related information to terminals such as farm site managers and operators. , It is about a smart aquaculture integrated service system that allows fish farmers to quickly and accurately deliver information on fish disease and growth management, and that allows system administrators to efficiently manage many farms.

Description

Smart Aquaculture Integrated Service System {An Integrated Service System for Smart Fish Farm}

The present invention relates to a smart aquaculture integrated service system, and more specifically, to analyze diseases and growth conditions of farmed fish by receiving farm information, and providing the related information to terminals such as farm site managers and operators. , It is about a smart aquaculture integrated service system that allows fish farmers to quickly and accurately deliver information on fish disease and growth management, and that allows system administrators to efficiently manage many farms.

As domestic demand for aquatic products increases while catches plummet, there is an increasing movement to replace the insufficient production of aquatic products with aquaculture.

However, the improvement of the aquatic product production system is required according to the decrease in the fishing license and the aging population.

Therefore, recently, a smart aquaculture system that automatically supplies feed, etc., has been developed and used, as shown in the patent document below, but only feed feed is automatically supplied, and fish diseases are not managed at all. it is not being done

(Patent Document) Patent Registration No. 10-2185637 (registered on November 26, 2020) "Smart Farm Feeding Device and Control Method"

The present invention has been made to solve the above problems,

The present invention enables farmers to manage disease and growth of fish by receiving farm information, analyzing disease and growth conditions of farmed fish, and providing this information to terminals such as farm site managers and operators. The purpose is to provide a smart aquaculture integrated service system that enables information to be delivered quickly and accurately and enables efficient management of many farms even on the system administrator's side.

An object of the present invention is to provide a smart aquaculture integrated service system that enables quick and accurate response to diseases by diagnosing diseases of farmed fish and providing solution information therefor.

An object of the present invention is to provide a smart aquaculture integrated service system that enables efficient treatment and removal of residual drugs by making prescriptions in consideration of the susceptibility and residual degree of drugs for diseases of each fish.

An object of the present invention is to provide a smart aquaculture integrated service system that identifies and responds to prevalent diseases by farm and region by analyzing and providing disease trends.

The present invention analyzes the correlation between the disease incidence rate with the farm environment, feed information, etc., and determines the disease when the incidence rate continues or repeats excessively or when the incidence rate rapidly increases. The purpose is to provide a smart form integration service system that enables efficient operation of the system.

The present invention analyzes the correlation between the environment, feed, input materials, etc., and the growth status of fish, and uses the analyzed correlation to supply feed and input materials, thereby enabling efficient growth of fish. The purpose is to provide a form integrated service system.

The purpose of the present invention is to provide a smart aquaculture integrated service system that enables aquaculture considering not only the size of fish but also the improvement of survival rate and reduction of incidence by determining the growth status in consideration of the growth rate, survival rate, and incidence of fish. .

An object of the present invention is to provide a smart aquaculture integrated service system that can lower the disease incidence rate by calculating the incidence rate according to the farm environment, feed, etc. and managing the incidence rate.

The present invention is implemented by an embodiment having the following configuration in order to achieve the above object.

According to an embodiment of the present invention, the smart aquaculture integrated service system according to the present invention receives and stores information on farms where fish are farmed, analyzes diseases and growth conditions of farmed fish, and provides related information to the management server. and; a farm terminal for receiving information on diseases and breeding analyzed from the management server; Characterized in that it includes; a manager terminal for inputting information necessary for disease and breeding analysis.

According to another embodiment of the present invention, in the smart aquaculture integrated service system according to the present invention, the management server includes a field information storage unit for receiving and storing field information of a farm where fish are farmed; and a disease monitoring unit that analyzes the field information stored by the field information storage unit to monitor disease risk and provides solution information for the disease, wherein the disease monitoring unit monitors the status of fish in each farm to detect diseases. It is characterized in that it includes a disease judgment unit that determines the occurrence of the disease, a disease diagnosis unit that performs precise analysis of the disease when it is determined that the disease has occurred, and a solution provider that provides solution information according to the diagnosis result of the disease.

According to another embodiment of the present invention, in the smart form integrated service system according to the present invention, the disease diagnosis unit includes a detection information receiving module for receiving information determined as a disease from the disease determination unit, and information determined as a disease is received, a diagnosis instruction transmission module for instructing the manager terminal to precisely diagnose the fish determined to be diseased, a diagnosis result input module for receiving disease diagnosis information from the manager terminal, and a diagnosis result for transmitting the diagnosis result to the farm terminal A diagnosis result loading module including a transmission module, wherein the solution providing unit calls a diagnosis result by the disease diagnosis unit; A prescription information retrieval module for retrieving prescription information for a disease according to a retrieved diagnosis result; A sensitivity information input module for receiving sensitivity information of the corresponding fish for the retrieved prescription information from a manager terminal; a prescription information determination module for determining a prescription for diseased fish in consideration of susceptibility information, and a prescription information providing module for transmitting the determined prescription information to a farm terminal; a residual information input module that receives residual information of the prescription substance for the fish after a certain period of time has elapsed after the prescription; It is characterized in that it includes; a modified prescription provision module for storing residual information and modifying and transmitting the prescription according to the residual information.

According to another embodiment of the present invention, in the smart modality integrated service system according to the present invention, the disease monitoring unit includes a trend analysis unit that analyzes and provides a trend for a diagnosed disease, and the trend analysis unit includes a diagnosed disease A disease information collection module that collects information, a pathogen classification module that classifies pathogens according to the disease to be diagnosed, an analysis module for each farm that analyzes the number of occurrences per unit period by classifying pathogens to be classified by farm, and pathogens that are classified It is characterized by including a regional analysis module that analyzes the number of occurrences for a unit period by classifying by region.

According to another embodiment of the present invention, in the smart aquaculture integrated service system according to the present invention, the disease monitoring unit analyzes the correlation between field information of each farm and disease incidence; A disease suspicion unit that calculates the incidence rate of each farm by using the correlation analyzed by the disease analysis unit, detects the risk of disease according to the calculated incidence rate, and determines the disease by the disease determination unit; The disease analysis unit includes a farm information input module for inputting identification information of each farm, a fish species information input module for inputting information on the fish species to be analyzed, an environment information input module for inputting farm environment information, A feed information input module for inputting information on the type and quantity, an input information input module for inputting information on additional input materials such as nutrients and vaccines added in addition to feed, and inputting information on the incidence of a specific disease of the fish species It is characterized in that it includes an incidence rate information input module and a correlation analysis module for analyzing the correlation between the input environment, feed, and input materials and the incidence rate.

According to another embodiment of the present invention, in the smart form integrated service system according to the present invention, the disease suspicion unit determines that the disease risk is high when the incidence rate for a specific disease continues to exceed the set value, A high-risk diagnosis unit that makes a judgment, and an abnormality diagnosis unit that judges that there is a possibility of an abnormality when the incidence rate repeatedly occurs within a certain range below the set value and determines the disease, and An incidence rate calculation module for calculating the incidence rate at regular time intervals using the correlation analyzed by the disease analysis unit, wherein the high-risk diagnosis unit includes an emergency diagnosis unit for diagnosing the disease in an urgently worsening state and making a judgment on the disease. And, a set value comparison module that compares the received incidence rate with a set value, a duration calculation module that calculates the duration when the incidence rate exceeds the set value, and a risk that is determined as a dangerous state when the duration exceeds the reference time It includes a determination module, wherein the abnormal diagnosis unit detects that the incidence rate reaches a certain range below the set value set by the set value comparison module, and a risk range detection module that calculates the frequency at which the risk range is detected. It includes a calculation module, a reference frequency comparison module that compares the risk frequency with a set reference frequency, and an anomaly notification module that determines and informs that an abnormality is likely to occur when the reference frequency is exceeded. A rate of change calculation module that calculates, a set-up comparison module that compares the calculated rate of change with a set standard, a continuous time calculation module that calculates the continuous time in which the rate of change exceeds the set standard, and an emergency when the continuous time exceeds the standard time It is characterized in that it includes an emergency notification module that determines a dangerous state and informs it.

According to another embodiment of the present invention, in the smart aquaculture integrated service system according to the present invention, the management server includes a feeding analysis unit that analyzes the correlation between environment and feed information and growth status for fish species in each farm , Includes a feeding control unit that adjusts the feeding according to the information analyzed by the feeding analysis unit, wherein the feeding analysis unit includes a farm information loading module that retrieves information about each farm, and information on fish species cultivated in each farm A fish species information loading module that loads environmental information such as water temperature, dissolved oxygen, pH, salinity, turbidity, and insolation in each farm, and information on feed, other vaccines, and nutrients used in each farm Analyzing the correlation between the breeding information loading module, the growth information loading module that brings up information on the growth status of each fish species, the growth index calculation module that digitizes the growth status of each fish, and the growth index and the environment and breeding information The feeding control unit includes a farm information receiving module for receiving farm information for adjusting feed, a fish species information receiving module for receiving fish species information, and environmental information for receiving environmental information of the corresponding farm. A receiving module, a feeding information calculation module that calculates feed and input material information that maximizes the growth index by using the correlation analyzed by the correlation analysis module, and feeding information that transmits the calculated information to the farm terminal. It is characterized in that it includes a provision module.

According to another embodiment of the present invention, in the smart aquaculture integrated service system according to the present invention, the growth index calculation module calculates the growth index by multiplying the growth rate for the size of the fish by the survival rate and multiplying this by the reciprocal of the incidence rate. It is characterized by doing.

According to another embodiment of the present invention, in the smart food integrated service system according to the present invention, the management server controls feed and input materials based on the incidence rate calculated through the correlation analyzed by the disease analysis unit. It includes a disease prevention unit that lowers the incidence rate, and the disease prevention unit monitors environmental information of each farm, a feed monitoring module that monitors feed information, and information such as nutrients and vaccines added in addition to feed. An incidence rate calculation module that calculates the incidence rate according to the correlation analyzed by the disease analysis unit using the input monitoring module and the information of the environment, feed, and input material being monitored, and a reference value comparison that compares the calculated incidence rate with a set reference value It is characterized in that it includes a module, a warning signal output module for generating a warning signal when the incidence rate exceeds a reference value, and an incidence rate control module for providing information on feed or input materials capable of lowering the incidence rate.

The present invention can obtain the following effects by combining and using the above embodiments and configurations to be described below.

The present invention enables farmers to manage disease and growth of fish by receiving farm information, analyzing disease and growth conditions of farmed fish, and providing this information to terminals such as farm site managers and operators. It has the effect of allowing possible information to be delivered quickly and accurately, and enabling efficient management of many farms on the system administrator's side.

The present invention has the effect of enabling quick and accurate response to diseases by diagnosing diseases of farmed fish and providing solution information therefor.

The present invention has the effect of enabling efficient treatment and removal of residual drugs by allowing prescriptions to be made in consideration of the susceptibility and residual degree of drugs for diseases of each fish.

The present invention analyzes and provides disease trends, thereby having an effect of identifying prevalent diseases by farms and regions so that countermeasures can be made.

The present invention analyzes the correlation between the disease incidence rate with the farm environment, feed information, etc., and determines the disease when the incidence rate continues or repeats excessively or when the incidence rate rapidly increases. This has the effect of enabling efficient operation of the system.

The present invention analyzes the correlation between the environment, feed, input materials, etc., and the growth status of fish, and uses the analyzed correlation to supply feed and input materials, thereby enabling efficient growth of fish. there is

The present invention has the effect of enabling aquaculture considering not only the size of the fish but also the improvement in survival rate and the reduction in incidence by determining the growth state in consideration of the growth rate, survival rate, and disease rate of the fish.

The present invention has an effect of lowering the disease incidence rate by calculating the incidence rate according to the farm environment, feed, etc. and managing the incidence rate.

1 is a block diagram of a smart form integrated service system according to an embodiment of the present invention
Figure 2 is a block diagram showing the configuration of the management server of Figure 1
Figure 3 is a block diagram showing the configuration of the field information storage unit of Figure 2
Figure 4 is a block diagram showing the configuration of the disease monitoring unit of Figure 2
Figure 5 is a block diagram showing the configuration of the disease analysis unit of Figure 4
Figure 6 is a block diagram showing the configuration of the disease suspicion unit of Figure 4
Figure 7 is a block diagram showing the configuration of the disease determination unit of Figure 4
Figure 8 is a block diagram showing the configuration of the disease diagnosis unit of Figure 4
Figure 9 is a block diagram showing the configuration of the solution provider of Figure 4
10 is a block diagram showing the configuration of the trend analysis unit of FIG. 4
Figure 11 is a block diagram showing the configuration of the feed analysis unit of Figure 2
Figure 12 is a block diagram showing the configuration of the feeding control unit of Figure 2
Figure 13 is a block diagram showing the configuration of the disease prevention unit of Figure 2

Hereinafter, preferred embodiments of the smart form integration service system according to the present invention will be described in detail with reference to the accompanying drawings. In the following description of the present invention, if it is determined that a detailed description of a known function or configuration may unnecessarily obscure the subject matter of the present invention, the detailed description thereof will be omitted. Throughout the specification, when a part "includes" a certain component, it means that it may further include other components without excluding other components unless otherwise stated, and also described in the specification. Terms such as "...unit" and "...module" refer to a unit that processes at least one function or operation, and may be implemented as hardware or software or a combination of hardware and software.

Referring to the smart aquaculture integrated service system according to an embodiment of the present invention with reference to FIGS. 1 to 13, the smart aquaculture integrated service system receives and stores information on farms where fish are farmed, and the disease for farmed fish and a management server 1 analyzing growth conditions and providing related information; a farm terminal 5 that receives information on diseases and breeding analyzed from the management server 1; It includes a manager terminal (3) for inputting information necessary for disease and breeding analysis.

The present invention is a system that can measure farm site information, analyze diseases, growth conditions, etc., and provide this information to farm site managers and farm operators. Information can be provided to the terminal 5, and the farm terminal 5 can be provided with related information through the installation of an application that can use this system. In addition, the information provided from the management server 1 of this system can be transmitted to automatic feeding facilities installed in the farm so that the feeding facilities can be directly controlled. To this end, in each farm, various environmental information of the farm can be measured, and videos and images in the farm can be taken, and these information is transmitted to the management server 1 to analyze diseases, growth conditions, etc. can make this happen. In addition, the manager terminal (3) of this system can analyze and manage diseases and growth conditions for a number of farms, and enter diagnosis and inspection information on diseases through the farm through the management server (1). It can be transmitted to the terminal 5, and through this, it is possible to efficiently manage a number of farms without having to visit them directly.

The management server 1 is configured to analyze and provide diseases and growth conditions of farmed fish, and receives and stores environment, breeding, growth, and image information measured in each farm. The management server 1 monitors the disease state by using the received information from each farm, and analyzes the feeding state so that the feeding can be adjusted in consideration of the disease, and the feeding to lower the incidence of disease The control of can reduce the occurrence of disease. To this end, the management server 1 may include a field information storage unit 11, a disease monitoring unit 12, a feeding analysis unit 13, a feeding control unit 14, and a disease prevention unit 15. can

The field information storage unit 11 is configured to receive and store information measured for each farm, and includes a farm information registration module 111, a farm information registration module 112, an environment information storage module 113, and breeding information. It may include a storage module 114, a growth information storage module 115, and an image information storage module 116.

The farm information registration module 111 is a configuration for registering identification information of farms to be managed, and enables management of a plurality of farms through the registered identification information.

The aquaculture information registration module 112 is a configuration for registering information about fish reared in each farm, and allows information about the type of fish to be registered.

The environmental information storage module 113 is configured to store information on each farm environment, and receives and stores information measured at each farm. The environmental information storage module 113 can store information such as water temperature, dissolved oxygen, pH, salinity, turbidity, and solar radiation in the farm, and sensors capable of measuring each information are measured from sensors installed in the farm. Information can be received and stored.

The breeding information storage module 114 is configured to receive and store information on feed and other input materials supplied for breeding fish, preferably to receive information on a feeder that automatically supplies feed in a farm. It can be done, and it can be received by input through the farm terminal (5). The breeding information storage module 114 may include a feed information storage module 114a for storing information on feed to be supplied and an input information storage module 114b for storing information on additionally input materials, The feed information storage module 114a stores information on the type and amount of feed, and the input information storage module 114b stores information on the type and amount of nutrients, enzymes, vaccines, and immune agents supplied for the growth of fish. information can be stored.

The growth information storage module 115 is a configuration for storing information on the growth state of farmed fish, and includes a stocking information storage module 115a for storing information on the species and quantity of fish input to the farm, and the size of the grown fish. It may include a size information storage module 115b for storing information about fish farms and a shipping information storage module 115c for storing information shipped from farms, and analyzing farm images stored by the image information storage module 116. It is possible to receive and store stocking information, size information, and shipping information according to input through or through the farm terminal 5.

The image information storage module 116 is a component that receives and stores image information captured in the farm, and can determine the disease state of fish through the stored image.

The disease monitoring unit 12 is configured to monitor the risk of disease by analyzing field information of the farm, and may provide solution information such as a prescription according to the monitored information. In particular, the disease monitoring unit 12 analyzes the correlation between information such as environment and breeding and the disease incidence rate, and uses the analyzed correlation to predict the incidence rate in each farm, and uses the predicted incidence rate. so that the risk of infection can be recognized. In addition, if the risk of outbreak is recognized, it is possible to determine whether the disease exists through image analysis in the farm, and if it is determined that the disease has occurred, a detailed examination can be ordered so that precise analysis of the farmed fish can be performed. In addition, the management server 1 can provide appropriate solution information when a disease is confirmed as a result of the examination, and can effectively cope with the disease by analyzing and displaying the trend of disease occurrence. To this end, the disease monitoring unit 12 includes a disease analysis unit 121, a disease suspicion unit 122, a disease determination unit 123, a disease diagnosis unit 124, a solution provider unit 125, a trend analysis unit ( 126) may be included.

The disease analysis unit 121 is a component that analyzes the correlation between farm field information and disease incidence, and can analyze the correlation for each disease type. The disease analysis unit 121 may analyze the correlation between the environment, feed, input materials, and the incidence rate for each fish species in each farm, and the disease suspicion unit 122 may analyze the disease in each farm by using the analyzed correlation. It is possible to determine the risk state and to determine and diagnose the disease. To this end, the disease analysis unit 121 includes a farm information input module 121a, a fish species information input module 121b, an environment information input module 121c, a feed information input module 121d, and an input information input module 121e. , an incidence information input module 121f, and a correlation analysis module 121g.

The farm information input module 121a is a component for inputting farm information to be analyzed for correlation, and can allow identification information of farms registered by the farm information registration module 111 to be input.

The fish species information input module 121b is a component for inputting information on fish species to be analyzed for correlation, and may allow information on the types of fish bred in each farm to be input.

The environmental information input module 121c is configured to input information about the farm environment, and can input environmental information such as water temperature, dissolved oxygen, pH, salinity, turbidity, and solar radiation in the farm. The environmental information input module 121c may receive and input information measured at each farm, and for example, may input an average value during the farming period.

The feed information input module 121d is a component for inputting information on feed supplied during fish farming, and allows an average value for the amount of feed to be input.

The input information input module 121e is configured to input information on input materials supplied to fish other than feed, and inputs the average value of input amounts of nutrients, vaccines, and enzymes stored by the input information storage module 114b. can make it

The incidence information input module 121f is configured to input information on the incidence rate for each disease, and the ratio of the number of individuals with each disease to the total number of each species of fish in the farm can be input as the incidence rate.

The correlation analysis module 121g is a component that analyzes the correlation between environment, feed, and input material information for each fish species in each farm and the incidence of each disease, and uses various mechanical learning methods using big data such as artificial neural networks. analysis can be made.

The disease suspicion unit 122 is a component that detects a high risk of disease in the farm, and uses the correlation analyzed by the disease analysis unit 121 to calculate the incidence rate according to the environment and breeding condition of each farm, If the calculated incidence rate is high, it is determined that the disease risk is high, and the disease determination unit 123 determines whether or not the disease exists. Therefore, the disease suspicion unit 122 may analyze the disease by the disease determination unit 123 only when the risk of the disease is high, thereby increasing the operating efficiency of the system and the accuracy of disease determination. In addition, the disease suspicion unit 122 calculates the incidence rate of each farm at regular time intervals, and not only when the incidence rate is high, but also when the incidence rate repeatedly increases in a lower risk range, the incidence rate is rapidly increased. By recognizing the case of an increase and determining the disease, it is possible to quickly and accurately determine the disease along with efficient operation of the system. To this end, the disease suspicion unit 122 may include a high risk diagnosis unit 122a, an abnormality diagnosis unit 122b, and an emergency diagnosis unit 122c.

The high-risk diagnosis unit 122a is configured to detect a high risk of disease, and determines a high-risk state when the incidence rate continues to exceed a set value. To this end, the high risk diagnosis unit 122a includes an incidence rate calculation module 122a-1, a set value comparison module 122a-2, a duration calculation module 122a-3, and a risk determination module 122a-4. can do.

The incidence rate calculation module 122a-1 is a component that calculates the incidence rate of each farm by using the correlation analyzed by the disease analysis unit 121. The average value information can be input into the correlation so that the incidence rate can be calculated at regular time intervals.

The set value comparison module 122a-2 is a component that compares the incidence rate calculated by the incidence rate calculation module 122a-1 with a set value, and sets the incidence rate to a level that can be determined as a high risk of disease. Set to so that comparison can be made.

The duration calculation module 122a-3 is configured to calculate the duration when the incidence rate calculated by the incidence rate calculation module 122a-1 exceeds a set value, and the incidence rate calculated at regular time intervals is the set value Calculate the duration of the state exceeding .

The risk determination module 122a-4 is configured to determine that the disease risk is high when the duration calculated by the duration calculation module 122a-3 exceeds a set reference time, and the disease determination unit 123 ) can be used to determine the disease of fish.

The abnormal diagnosis unit 122b notifies the high-risk diagnosis unit 122a that the disease is not determined to be in a high risk condition, but the calculated incidence rate repeatedly occurs within a certain range below the set value, so that the disease can be determined. make it happen Therefore, the abnormal diagnosis unit 122b can determine the disease not only when the disease risk condition continues but also when the disease is repeated in a close range, so that a more rapid response to disease occurrence can be achieved. To this end, the abnormal diagnosis unit 122b includes a risk range detection module 122b-1, a risk frequency calculation module 122b-2, a reference frequency comparison module 122b-3, and an abnormality notification module 122b-4. can include

The risk range detection module (122b-1) is a component that detects that the set value set by the set value comparison module (122a-2) reaches a certain range below, so that the frequency can be calculated do.

The risk frequency calculation module 122b-2 is configured to calculate the frequency when the risk range detection module 122b-1 detects that the incidence rate reaches the danger range, and the risk range at a predetermined number of times the incidence rate is calculated The number of times reaching is calculated so that the frequency can be calculated. For example, the risk frequency calculation module 122b-2 may calculate the frequency of reaching the risk range during 10 occurrence rate calculations.

The reference frequency comparison module 122b-3 compares the frequency calculated by the risk frequency calculation module 122b-2 with a set reference frequency, and determines whether or not the reference frequency is exceeded.

The anomaly notification module 122b-4 is configured to determine that a disease risk may occur when the frequency of reaching the risk range exceeds the reference frequency, and the disease determination unit 123 determines the disease make it happen

The emergency diagnosis unit 122c detects a rapid increase in the incidence rate and determines the disease. If the incidence rate increases rapidly even before the outbreak, it is quickly recognized and the judgment on the disease is made so that the risk of disease occurrence due to urgent environmental deterioration can be promptly dealt with. To this end, the emergency diagnosis unit 122c includes a change rate calculation module 122c-1, a set preparation preparation module 122c-2, a continuous time calculation module 122c-3, and an emergency notification module 122c-4. can do.

The change rate calculation module 122c-1 is configured to calculate the change rate of the incidence rate, and calculates the degree of change in the incidence rate calculated at regular time intervals.

The setting reference comparison module 122c-2 is a component that compares the calculated rate of change with a set standard, and sets a standard for the rate of change that can be judged as a rapid increase so that comparison can be made.

The continuous time calculation module 122c-3 is configured to calculate the continuous time in which the rate of change exceeds a set standard, and determines whether or not the continuous time is exceeded.

The emergency notification module 122c-4 is configured to determine an emergency risk state when the change rate exceeds a set standard and lasts for a set time or longer, and allows the disease determination unit 123 to determine the disease.

The disease determination unit 123 is a component that analyzes the fish in the farm to determine whether or not there is a disease. (122), it is possible to determine whether a disease exists only when it is determined that the disease risk is high. For example, the disease determination unit 123 may analyze image information in the farm to determine the disease, and if it is determined to be a disease, the disease diagnosis unit 124 may accurately diagnose the disease. let it be To this end, the disease determination unit 123 may include a determination information collection module 123a, a collection information analysis module 123b, an analysis information comparison module 123c, and a diagnosis need detection module 123d.

The determination information collection module 123a is a component that collects information for determining a disease, and can be configured to collect image information about a farm in a state of disease risk by the disease suspicion unit 122.

The collection information analysis module 123b is a component that analyzes the information collected by the determination information collection module 123a, and can analyze image information. For example, a fish image in image information or image information It can be used to analyze the movements of fish.

The analysis information comparison module 123c is a component that compares the information analyzed by the collection information analysis module 123b with stored information. For example, when a disease is determined through image comparison, the image of a fish in a normal state It can be compared with to determine whether damage has occurred to the outside of the fish. In addition, the analysis information comparison module 123c analyzes the movement pattern of the fish so that comparison can be made, stores the movement pattern of the fish in a diseased state, and compares the movement pattern of the fish in the image information with the disease. may make a decision.

The diagnosis necessity detection module 123d is configured to inform that a diagnosis is necessary when it is determined that a disease has occurred as a result of comparison by the analysis information comparison module 123c. so that a precise diagnosis can be made.

The disease diagnosis unit 124 is configured to make a precise diagnosis of the disease, and an accurate diagnosis of the disease can be made through genetic analysis of the fish determined to have the disease by the disease determination unit 123. let it be Therefore, the disease diagnosis unit 124 can perform precise analysis only on fish judged to be diseased by the disease determination unit 123 so that efficient management of the disease can be achieved, and the disease state can be quickly identified This can enable a rapid response to the disease. If the disease diagnosis unit 124 is determined to be a disease by the disease determination unit 123, the disease diagnosis unit 123 transmits information about the disease to the manager terminal 3 so that precise diagnosis can be performed, and precise diagnosis is performed through a separate device. It can be performed so that the diagnosis result is input. At this time, a separate device for precise diagnosis of the disease may be formed at the manager's side so that the inspection may be performed by bringing in the fish, or may be installed at the farm site so that the inspection may be performed directly on the site. The disease diagnosis unit 124 may include a detection information receiving module 124a, a diagnosis instruction transmission module 124b, a diagnosis result input module 124c, and a diagnosis result transmission module 124d.

The detection information receiving module 124a is a component for receiving information on fish requiring diagnosis, and receives information by the diagnosis required detection module 123d.

The diagnosis instruction transmission module 124b is a component that transmits information requiring diagnosis to the manager terminal 3, so that a detailed examination can be performed on a fish determined to have a disease.

The diagnosis result input module 124c is configured to input the result of a detailed examination of fish, and can be input through the manager terminal 3, or is interlocked with a separate device that performs genetic testing for diseases. It is also possible to input the results directly.

The diagnosis result transmission module 124d is configured to transmit the result input by the diagnosis result input module 124c and can be transmitted to the farm terminal 5.

The solution provider 125 is a component that provides solution information for a disease, and provides solution information when a disease is diagnosed as having occurred by the disease diagnosis unit 124 . The solution providing unit 125 can provide prescription information for treating diseases, such as antibiotics and natural remedies. It can be checked and the prescription can be modified and provided. To this end, the solution provider 125 includes a diagnosis result loading module 125a, a prescription information search module 125b, a sensitivity information input module 125c, a prescription information decision module 125d, and a prescription information providing module 125e. , a residual information input module 125f, and a modified prescription providing module 125g.

The diagnosis result loading module 125a is a component that loads disease information diagnosed by the disease diagnosis unit 124, so that a prescription for a disease to be diagnosed can be provided.

The prescription information retrieval module 125b is a component that searches prescription information stored in the system, and retrieves information such as a treatment for a diagnosed disease and a drug that can be solved.

The sensitivity information input module 125c is configured to input sensitivity information of fish to the drug retrieved by the prescription information search module 125b, and inspects the sensitivity of each drug to the diseased fish to obtain a manager terminal (3) ) through which information can be entered.

The prescription information determination module 125d is a component that determines the drug to be finally prescribed, and among the drugs retrieved by the prescription information search module 125b, drugs effective according to the information input by the sensitivity information input module 125c are selected. Choose to make a prescription.

The prescription information providing module 125e is configured to provide prescription information to the farm terminal 5, and transmits the drug information determined by the prescription information determination module 125d to the farm terminal 5.

The residual information input module 125f is configured to receive input of residual information on the prescribed drug, and the residual amount of the drug for fish and fish farms for which the drug was prescribed is examined and input at a time when a certain time has elapsed after the prescription of the drug. make it possible The residual information input module 125f can automatically transmit information instructing the inspection to the manager terminal 3 and the farm terminal 5 when a predetermined time elapses after the prescription of the drug, and after the inspection is completed, the manager terminal ( Residual inspection information can be input through 3).

The corrected prescription providing module 125g is configured to modify and provide the prescription according to the information input by the residual information input module 125f. If the treatment is not completed, another drug is prescribed or the remaining drug component is removed. Prescriptions of possible substances can be made.

The trend analysis unit 126 analyzes disease occurrence trends and provides them to the farm terminal 5, collects and stores the results diagnosed by the disease diagnosis unit 124, and collects and stores diseases for each farm and region. Analyze occurrence trends and provide them. To this end, the trend analysis unit 126 may include a disease information collection module 126a, a pathogen classification module 126b, an analysis module by farm 126c, and an analysis module by region 126d.

The disease information collection module 126a is a component that collects information diagnosed as a disease, and collects diagnosis result information by the disease diagnosis unit 124 .

The pathogen classification module 126b is a component that classifies the type of disease, and can classify according to the causative agent of the disease so that trend analysis can be performed.

The farm-specific analysis module 126c is a component that analyzes and provides disease occurrence trends for each farm, and can display the number of disease occurrences per unit period according to the type of pathogen as a graph for each farm.

The region-specific analysis module 126d is configured to analyze and provide disease occurrence trends by region, and may display and provide the number of disease occurrences per unit period in a graph according to the type of pathogen by region.

The feeding analysis unit 13 is a component that analyzes the growth state of fish according to feeding, and can analyze the correlation between the environment, feeding state and the growth state of fish for each fish species in each farm. . At this time, the growth state of the fish can be determined by considering the growth size, survival rate, disease rate, etc. of the fish. To this end, the feeding analysis unit 13 includes a farm information loading module 131, fish species information loading module 132, environment information loading module 133, breeding information loading module 134, breeding information loading module 135 ), a growth index calculation module 136, and a correlation analysis module 137.

The farm information loading module 131 is a component that loads farm information to analyze feeding, and can load farm information according to identification information of the farm registered by the farm information registration module 111.

The fish species information loading module 132 is a component that loads fish species information to analyze feed, and loads information on one of the fish species cultivated in each farm.

The environmental information loading module 133 is a component that loads information on the environmental state during aquaculture, and can load information on water temperature, dissolved oxygen, pH, salinity, turbidity, solar radiation, etc., measured in each farm, and the environment The information stored by the information storage module 113 is called.

The breeding information loading module 134 is a component that loads feeding information supplied to the fish, and loads not only feed information but also information on additionally input substances such as nutrients and vaccines.

The growth information loading module 135 is configured to load information on the growth state of fish, including a size information loading module 135a for loading fish size information, a survival rate loading module 135b for loading survival rate information, and a component for loading information on disease rates. Incidence loading module 135c may be included.

The size information loading module 135a is a component for loading fish size information, and can load initial size and shipping size information of fish, analyze image information, or store information input through the farm terminal 5. you can call it

The survival rate loading module 135b is a component that loads information about the survival rate of fish, and can calculate the ratio of the number of fish stocked and the number of surviving fish to be released as the survival rate, and bring it back.

The incidence rate loading module 135c is a component that loads information on the disease invention rate, and can calculate the ratio of the number of stocked fish and the number of people diagnosed with the disease by the disease diagnosis unit 124 as the incidence rate and load it. there is.

The growth index calculation module 136 is a component that calculates a growth index representing the degree of healthy growth of fish, and can calculate the growth index by considering the size, survival rate, and incidence of fish. For example, the growth index calculation module 136 may calculate the ratio of the size of the fish to be shipped from the initial size of the fish, and multiply the survival rate by the reciprocal of the incidence rate to calculate the growth index. The higher the growth rate, the higher the survival rate, and the lower the incidence rate, the higher the value.

The correlation analysis module 137 is a component that analyzes the correlation between the environment, breeding information, and growth index, and analyzes the correlation according to the mechanical learning method using accumulated data for each farm and fish species. can

The feeding control unit 14 is configured to provide feeding information capable of optimizing the growth state, and calculates and provides feeding information capable of increasing the growth state according to the environmental conditions of each farm. Therefore, the feeding control unit 14 receives environmental information from each farm at regular time intervals, and applies the received environmental information to the correlation analyzed by the feeding analysis unit 13 to determine the growth index. Allows you to determine the amount of feed that can be increased. To this end, the feeding control unit 14 includes a farm information receiving module 141, a fish species information receiving module 142, an environment information receiving module 143, a feeding information calculation module 144, and a feeding information providing module. (145) may be included.

The farm information receiving module 141 is a component that receives farm information to adjust feeding, and can enable identification information of the farm to be received according to a request through the farm terminal 5.

The fish species information receiving module 142 is a component that receives fish species information to adjust feeding, and receives information on the type of fish together with farm information.

The environmental information receiving module 143 is a component that receives environmental information of the farm, and receives information about water temperature, dissolved oxygen, pH, salinity, turbidity, solar radiation, and the like.

The feeding information calculation module 144 is configured to apply the environmental information received by the environmental information receiving module 143 to the correlation derived by the feeding analysis unit 13, and maximizes the growth index. Calculate the amount of feed and input materials that can be used.

The feeding information providing module 145 is configured to provide the feeding information calculated by the feeding information calculation module 144 to the farm terminal 5, preferably with an automatic feeder at the farm. It is provided so that feed and input materials can be supplied automatically.

The disease prevention unit 15 is configured to prevent disease by adjusting the feeding amount, and calculates the incidence rate using the correlation analyzed by the disease analysis unit 121, while the incidence rate is set to a reference value. If it exceeds, the incidence rate can be lowered through the control of the feeding amount to lower the incidence rate of the disease. Therefore, this system monitors the incidence rate by the disease prevention unit 15 while controlling the feeding amount through the feeding control unit 14 to maximize the growth state, so that the incidence rate does not exceed the reference value. It is also possible to reduce the occurrence of disease by adjusting the feeding amount in the same direction. In addition, when the incidence rate increases even though the feeding amount is adjusted to lower the incidence rate, the risk of disease occurrence is detected by the disease suspicion unit 122 so that the disease diagnosis can be made. The disease prevention unit 15 includes an environmental monitoring module 151, a feed monitoring module 152, an input monitoring module 153, an incidence rate calculation module 154, a reference value comparison module 155, and a warning signal output module 156 , Incidence rate control module 157 may be included.

The environmental monitoring module 151 is a component that monitors the environmental state of the farm, and receives and monitors environmental information such as water temperature, dissolved oxygen, pH, salinity, turbidity, and solar radiation.

The feed monitoring module 152 is configured to monitor the amount of feed supplied to the farm, and can monitor feed information stored by the feed information storage module 114a.

The input monitoring module 153 is configured to monitor the amount of input materials other than feed supplied to the farm, and can monitor input material information stored by the input information storage module 114b.

The incidence rate calculation module 154 is configured to calculate the incidence rate by applying environment, feed, and input material information to the correlation analyzed by the disease analysis unit 121, so that the incidence rate is calculated at regular time intervals. can

The reference value comparison module 155 compares the incidence rate calculated by the incidence rate calculation module 154 with a reference value, and determines whether or not the reference value is exceeded.

The warning signal output module 156 is configured to output a warning signal when the incidence rate exceeds a reference value, and can output a warning signal informing the farm terminal 5 that there is a risk of disease.

The incidence rate control module 157 is configured to lower the incidence rate when the incidence rate exceeds a reference value, and calculates the input amount of feed or input material capable of lowering the incidence rate and provides it to the farm terminal 5.

The manager terminal 3 is a terminal of a manager who manages this system, and devices such as a PC, tablet, and smart phone connected to the management server 1 through wired or wireless communication may be applied. The manager terminal 3 can manage information such as diseases and growth conditions for a plurality of farms, and can input test information such as disease diagnosis, drug sensitivity, and residual information.

The farm terminal 5 is a terminal possessed by a site manager, farm operator, etc., and devices such as a PC, tablet, smartphone, etc. connected to the management server 1 through wired or wireless communication may be applied. The farm terminal 5 can be provided with information on disease outbreaks, information for feeding control, etc. from the management server 1, and facility management of the farm can be performed through the provided information. Feeding may be controlled automatically by interlocking with an automatic feeding facility installed in the feeder. An application capable of using this system may be installed in the farm terminal 5, through which information transmitted from the management server 1 may be displayed.

In the above, the applicant has described various embodiments of the present invention, but such embodiments are only one embodiment for implementing the technical idea of the present invention, and any changes or modifications are made according to the present invention as long as the technical idea of the present invention is implemented. should be construed as falling within the scope of

1: management server 11: field information storage unit
12: disease monitoring unit 121: disease analysis unit
122: disease suspicion unit 122a: high risk diagnosis unit
122b: Abnormal diagnosis unit 122c: Emergency diagnosis unit
123: disease determination unit 124: disease diagnosis unit
125: solution provider 126: trend analysis department
13: feeding analysis unit 14: feeding control unit
15: disease prevention department 3: manager terminal
5: farm terminal

Claims (9)

A management server that receives and stores information on farms where fish are farmed, analyzes diseases and growth conditions of farmed fish, and provides related information;
a farm terminal for receiving information on diseases and breeding analyzed from the management server;
Smart aquaculture integrated service system comprising a; manager terminal for entering the information necessary for analysis of disease and breeding. The method of claim 1, wherein the management server
a field information storage unit for receiving and storing field information of a farm where fish are cultivated; A disease monitoring unit analyzing the field information stored by the field information storage unit to monitor disease risk and providing solution information for the disease;
The disease monitoring department,
A disease judgment unit that monitors the status of fish in each farm to determine the disease, a disease diagnosis unit that analyzes the disease precisely when it is determined to be a disease outbreak, and a solution that provides solution information according to the diagnosis result of the disease Smart form integrated service system comprising a provision unit. The method of claim 2, wherein the disease diagnosis unit
A detection information receiving module for receiving information determined to be a disease from the disease determination unit, a diagnosis instruction transmission module for instructing a manager terminal to precisely diagnose a fish determined to be diseased when information determined to be a disease is received, and a manager It includes a diagnosis result input module that receives disease diagnosis information from the terminal and a diagnosis result transmission module that transmits the diagnosis result to the farm terminal,
The solution provider,
a diagnosis result loading module for calling a diagnosis result by the disease diagnosis unit; A prescription information retrieval module for retrieving prescription information for a disease according to a retrieved diagnosis result; A sensitivity information input module for receiving sensitivity information of the corresponding fish for the retrieved prescription information from a manager terminal; a prescription information determination module for determining a prescription for diseased fish in consideration of susceptibility information, and a prescription information providing module for transmitting the determined prescription information to a farm terminal; a residual information input module that receives residual information of the prescription substance for the fish after a certain period of time has elapsed after the prescription; A smart form integrated service system comprising: a correction prescription providing module for storing residual information and modifying and transmitting the prescription according to the residual information. The method of claim 2, wherein the disease monitoring unit
Includes a trend analysis unit that analyzes and provides trends for diagnosed diseases;
The trend analysis department,
A disease information collection module that collects diagnosed disease information, a pathogen classification module that classifies pathogens according to diagnosed diseases, and a farm-specific analysis module that analyzes the number of occurrences per unit period by classifying pathogens to be classified by farm, Smart aquaculture integrated service system, characterized in that it includes a regional analysis module that analyzes the number of occurrences for a unit period by classifying pathogens to be classified by region. The method of claim 2, wherein the disease monitoring unit
a disease analysis unit that analyzes the correlation between field information of each farm and disease incidence; A disease suspicion unit that calculates the incidence rate of each farm by using the correlation analyzed by the disease analysis unit, detects the risk of disease according to the calculated incidence rate, and determines the disease by the disease determination unit; and
The disease analysis department,
A farm information input module for inputting identification information for each farm, a fish species information input module for inputting information on the fish species to be analyzed, an environment information input module for inputting farm environment information, and information on the type and amount of input feed A feed information input module for inputting, an input information input module for inputting information on additional input materials such as nutrients and vaccines added in addition to feed, and an incidence information input module for inputting information on the incidence of a specific disease of the fish species , Smart aquaculture integrated service system, characterized in that it includes a correlation analysis module that analyzes the correlation between the input environment, feed, input material and incidence. The method of claim 5, wherein the heart of the disease
If the incidence rate of a specific disease continues to exceed the set value, it is determined that the disease risk is high and the disease is judged to be high risk diagnosis unit, and if the incidence rate repeatedly occurs within a certain range below the set value, the possibility of abnormal occurrence It includes an abnormality diagnosis unit that determines that there is a disease and an emergency diagnosis unit that diagnoses a disease as an urgently worsening condition when the incidence rate rises rapidly and makes a judgment about the disease,
The high-risk diagnosis unit,
An incidence rate calculation module that calculates the incidence rate at regular time intervals using the correlation analyzed by the disease analysis unit, a set value comparison module that compares the received incidence rate with a set value, and a duration when the incidence rate exceeds the set value It includes a duration calculation module that calculates and a risk determination module that determines a dangerous state if the duration exceeds the reference time,
The abnormal diagnosis unit,
A risk range detection module for detecting that the incidence rate reaches a certain range below the set value set by the set value comparison module, a risk frequency calculation module for calculating the frequency at which the risk range is detected, and a reference frequency for setting the risk frequency Including a reference frequency comparison module that compares with, and an anomaly notification module that determines and informs a state in which an abnormality is likely to occur when the reference frequency is exceeded,
The emergency diagnosis department,
A change rate calculation module that calculates the rate of change in the incidence rate, a set-up comparison module that compares the calculated rate of change with a set standard, a continuous time calculation module that calculates the continuous time at which the rate of change exceeds the set standard, and a continuous time that exceeds the standard time Smart form integrated service system, characterized in that it includes an emergency notification module that determines it as an emergency risk condition when exceeded. The method of claim 1, wherein the management server
Includes a feeding analysis unit that analyzes the correlation between environmental and feed information and growth status for fish species in each farm, and a feeding control unit that adjusts feeding according to the information analyzed by the feeding analysis unit,
The feeding analysis unit,
A farm information loading module for loading information on each farm, a fish species information loading module for loading information on fish species cultivated in each farm, and an environment for loading environmental information such as water temperature, dissolved oxygen, pH, salinity, turbidity, solar radiation, etc. at each farm An information loading module, a breeding information loading module that retrieves information such as feed, other vaccines, and nutrients used in each farm, a growth information loading module that retrieves information on the status of each fish species, and quantifying the growth status of each fish It includes a growth index calculation module and a correlation analysis module that analyzes the correlation between the environment and breeding information and the growth index,
The feed control unit,
A farm information receiving module for receiving farm information to adjust feeding, a fish species information receiving module for receiving fish species information, an environment information receiving module for receiving environment information for the relevant farm, and the correlation analyzed by the correlation analysis module. A smart aquaculture integrated service system comprising a feeding information calculation module that calculates feed and input material information that maximizes the growth index using relationships and a feeding information providing module that transmits the calculated information to the farm terminal . The method of claim 7, wherein the growth index calculation module
A smart aquaculture integrated service system characterized in that the growth rate for the size of the fish is multiplied by the survival rate and multiplied by the reciprocal of the incidence rate to calculate the growth index. The method of claim 5, wherein the management server
A disease prevention unit that lowers the incidence rate by adjusting feed and input materials based on the incidence rate calculated through the correlation analyzed by the disease analysis unit,
The disease prevention department,
An environment monitoring module that monitors environmental information of each farm, a feed monitoring module that monitors feed information, an input monitoring module that monitors information such as nutrients and vaccines input other than feed, and monitoring environment, feed, and input materials An incidence rate calculation module that calculates an incidence rate according to the correlation analyzed by the disease analysis unit using information, a reference value comparison module that compares the calculated incidence rate with a set reference value, and generates a warning signal when the incidence rate exceeds the reference value Smart aquaculture integrated service system, characterized in that it includes a warning signal output module that causes, and an incidence control module that provides information on feed or input materials that can reduce the incidence rate.

Images