A remote video monitoring system for aquaculture farms

Abstract

The invention discloses a remote video monitoring system for an aquaculture farm, and specifically relates to the technical field of remote video monitoring in the aquaculture industry. The invention is used to solve the problem that in the remote video monitoring system for an aquaculture farm, a large amount of data brought by a fixed monitoring cycle causes an excessive load on a central server, thereby affecting the performance and stability of the system, etc. In addition, if the same monitoring cycle is maintained for all breeding areas, it will lead to an increase in costs. The remote video monitoring system for an aquaculture farm also includes a monitoring module, a data processing module, a central server and an adjustment module. The invention evaluates the regional status of the divided areas, compares the regional status evaluation coefficient with a preset regional status threshold, and adjusts the monitoring cycle of the monitoring area based on the comparison result and in combination with the load condition of the central server.

Description

Technical Field

[0001] The present invention relates to the technical field of remote video monitoring, and more specifically, to a remote video monitoring system for an aquaculture farm. Background Art

[0002] With the continuous development of the aquaculture industry, more and more people are entering this industry. Although aquaculture can bring lucrative profits, it may also bring severe challenges. Because aquaculture farms are generally built in sparsely populated areas and far away from cities, while ensuring a good breeding environment for the farms, it also brings troubles to the people who manage the farms. Since the management regulations of farms are relatively strict, it is particularly important to establish a remote video monitoring system for aquaculture farms, which is also more convenient for managers to supervise and manage farms.

[0003] The prior art has the following deficiencies:

[0004] For aquaculture, most of them are mainly farmed at sea. It is very important for farmers to increase the output of aquaculture. With the continuous development of automation technology in aquaculture, remote video monitoring technology is also developing continuously. All-day monitoring and the increase of breeding area will lead to higher cost and more complicated operation, which is not suitable for general aquaculture farmers. Therefore, it is necessary to judge whether to adjust the monitoring cycle of the area according to the regional status of the monitoring area. Summary of the invention

[0005] The purpose of the present invention is to provide a remote video monitoring system for an aquaculture farm to solve the shortcomings of the background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The system includes a monitoring module, a data processing module, and a central control terminal;

[0008] The monitoring module is used to obtain some monitoring parameters, including personnel fatigue index, fish growth cycle deviation index, microbial concentration and some data of hardware equipment, and these acquired data will be sent to the data processing module;

[0009] The data processing module is used to receive the data sent by the monitoring module, and then process the data, including formulating analysis and adjusting the regional status assessment coefficient, and sending the processing results to the central server;

[0010] The central server is used to receive the processing results obtained by the data processing module after analysis, and store the data in the central server for comparison with the next data, and send instructions according to the processing results;

[0011] In a preferred embodiment, the monitoring module collects multiple parameters including personnel fatigue index, aquatic product growth cycle deviation index, and microbial concentration, and sends the data to the data processing module.

[0012] In a preferred embodiment, the data processing module mainly receives data sent by the monitoring module, including the personnel fatigue index, the aquatic product growth cycle deviation index, and the microbial concentration, and obtains the regional status assessment coefficient by weighted summation of these parameters, and the calculation expression is:

[0013]

[0014] In the formula, is the evaluation coefficient, is the personnel fatigue index, It is the deviation index of aquatic product growth cycle, is the microbial concentration, , , They are respectively the personnel fatigue index, the aquatic product growth cycle deviation index, and the preset proportional coefficient of microbial concentration, and , proportionality coefficient , , The specific value of is set by those skilled in the art according to specific circumstances and is not limited here.

[0015] In a preferred embodiment, the data processing module is also used to sort the divided monitoring areas from large to small according to the regional status assessment coefficients, generate a sorting table, and send the generated sorting table to the central server. The central server inspects the aquaculture areas in turn according to the sorting table.

[0016] In a preferred embodiment, the data processing module is further used to compare the regional status evaluation coefficient with a preset standard regional status first threshold and a second threshold:

[0017] If the regional status assessment coefficient Less than the standard area status threshold , then the regional status of the area is good, and the monitoring and management cycle of the area can be appropriately extended;

[0018] If the regional status assessment coefficient Greater than or equal to the standard area status threshold , and less than , it means that the regional status of the area is moderate and there is no need to adjust the monitoring cycle of the area;

[0019] If the region status is greater than or equal to the standard region status threshold , it means that the regional status of the area is poor and the management of the breeding area does not meet the requirements. It is necessary to shorten the monitoring and management cycle of the area. By shortening the monitoring and management cycle, the area can be closely monitored and managed to improve the breeding efficiency of the aquaculture farm.

[0020] In a preferred embodiment, the data processing module places the areas where the monitoring cycle needs to be extended or shortened in the same set, for example, {A1, A2, A3, ..., B1, B2, B3, ...}, A1, A2, A3 represent the area where the monitoring cycle needs to be extended, and B1, B2, B3 represent the area where the monitoring cycle needs to be shortened, and then calculates the time for extending or shortening the monitoring cycle. The following is a calculation method for adjusting the monitoring cycle.

[0021] The method to extend the monitoring cycle is as follows. The time parameters for extending the monitoring cycle are: , mark the monitoring period as t, t is a time period, and its upper and lower limits are and , set the upper and lower limits to ,Right now , then the expression of the corrected monitoring period is:

[0022]

[0023] The adjusted monitoring period is .

[0024] The method to shorten the monitoring cycle is as follows: the time parameter of shortening the monitoring cycle is , mark the monitoring period as t, t is a time period, and its upper and lower limits are and , set the upper and lower limits to ,Right now , then the expression of the corrected monitoring period is:

[0025]

[0026] The adjusted monitoring period is .

[0027] In a preferred embodiment, the data processing module also records the time difference of extending or shortening the monitoring cycle of each area, adds all the time differences of the recorded areas, and calibrates the time parameter of extending the monitoring cycle and the time parameter of shortening the monitoring cycle respectively as , , the parameters can be combined to establish an average adjustment monitoring cycle , its calculation expression is:

[0028]

[0029] In the formula, is the average adjustment monitoring period quantity, It is the parameter to extend the monitoring cycle time. It is a parameter that shortens the detection cycle time. , are the number of regions with extended monitoring periods and the number of regions with shortened monitoring periods, respectively, and , .

[0030] In a preferred embodiment, the data processing module sets the average monitoring cycle number threshold ,Then the average number of detection cycles is compared with the average number of detection cycles threshold;

[0031] like , indicating that the adjusted monitoring cycle is more in line with reality and no measures are needed;

[0032] like , indicating that there is a problem with the monitoring period of the adjustment, which needs further consideration.

[0033] In a preferred embodiment, the monitoring module is also used to collect load parameters inside the central server, including request response time, error rate, memory usage and the average number of adjusted monitoring cycles obtained in Example 1, and send the collected data to the data processing module.

[0034] In a preferred embodiment, the data collection module uses the collected load parameters to establish an evaluation coefficient of the central server load. The specific expression is as follows:

[0035]

[0036] In the formula, is the evaluation coefficient of the central server load, is the request response time, is the error rate, is the number of concurrent connections, is the average amount of data in the adjusted monitoring period, , , , They are request response time, error rate, number of concurrent connections, and preset proportional coefficient of average adjustment monitoring cycle data volume, and , proportionality coefficient , , , The specific value of is set by those skilled in the art according to specific circumstances and is not limited here.

[0037] The evaluation coefficient of the central server load and threshold For comparison:

[0038] like , the early warning module will send an early warning signal;

[0039] like , and the early warning module refuses to send early warning signals.

[0040] Technical effects and advantages of the present invention:

[0041] 1. The present invention divides a large area into several small areas for separate monitoring. The personnel fatigue index, aquatic product growth cycle deviation index, and microbial concentration collected by the monitoring module are weighted and summed by the data processing module to obtain the regional state evaluation coefficient. The obtained evaluation coefficients are sorted from large to small to generate a sorting table. The sorted regional state evaluation coefficients are compared with the preset regional state thresholds, and adjustments are made according to the comparison results.

[0042] 2. The present invention continues to collect the load parameters of the internal servers of the system through the monitoring module to establish the evaluation coefficient of the central server load, and establishes the average adjustment monitoring cycle through the data processing module. The adjustment module adjusts the monitoring cycle of each divided aquaculture area according to the average adjustment monitoring cycle, thereby avoiding network congestion caused by a large amount of data generated at the same time. By adjusting the monitoring cycle, problems and abnormal situations in aquaculture can be discovered more timely, helping aquaculture managers and decision makers to more accurately analyze the changing trends of aquaculture areas and the growth of aquatic products. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0044] Figure 1 This is a schematic diagram of the structure of Embodiment 1 of the present invention;

[0045] Figure 2 This is a schematic diagram of the structure of Embodiment 2 of the present invention; DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] Example 1: Please refer to Figure 1As shown, this embodiment is a remote video monitoring system for an aquaculture farm, including a monitoring module, a data processing module, and a central control terminal;

[0048] The monitoring module is used to obtain some monitoring parameters, including personnel fatigue index, fish growth cycle deviation index, microbial concentration and some data of hardware equipment, and these acquired data will be sent to the central processing module;

[0049] The data processing module is used to receive the data sent by the monitoring module, and then process the data, including formulating analysis to adjust the monitoring cycle duration evaluation coefficient, and send the processing results to the central control end;

[0050] The central control terminal is used to receive the processing results obtained by the data processing module after analysis, and store the data in the central control terminal for comparison with the next data, and send adjustment instructions according to the processing results;

[0051] The method steps are as follows:

[0052] The water plant farm is divided into several areas, areas N1, N2, N3..., and the divided N areas are monitored and managed separately. After the regional monitoring and management, the monitoring module will collect multiple parameters obtained from different areas, including personnel management status parameters and equipment monitoring parameters, establish regional status evaluation coefficients according to the parameters, sort the regional status evaluation coefficients obtained from different areas from large to small, generate a sorting table, compare the evaluation coefficient with the preset regional status threshold, and send the comparison result to the central control end. The central control end determines the regional status of different areas based on the comparison result. After the determination, the monitoring cycle will be appropriately shortened for the area with poor status, and the monitoring cycle will be appropriately extended for the area with good status. This is conducive to managers to focus more on areas with poor aquaculture, and at the same time, it can also improve the breeding efficiency of aquaculture farms.

[0053] In this embodiment, in order to better illustrate that the water plant farm is divided into several areas, and the divided areas are monitored and managed separately, we give the following example:

[0054] Assume that there is an aquaculture farm, which divides the breeding area into several areas, namely area N1, area N2, area N3..., the types of aquatic products cultured in several areas are the same, and the quantities are roughly the same at the beginning. The several areas are monitored and managed separately, and they are initially controlled by the management center to ensure that the monitoring and management cycles of the several breeding areas are the same. After a period of time, the quantities of aquatic products cultured in several areas differ. Therefore, frequent monitoring and management are required for areas with less aquatic products to find the reasons for the decrease in the number of aquatic products. However, before adjusting the monitoring and management cycle of each area, it is necessary to record the personnel management status parameters and equipment monitoring parameters to establish the regional status assessment coefficient.

[0055] It should be noted that for the divided aquaculture areas, an initial monitoring period is preset, for example, one week.

[0056] Personnel management status parameters include manager fatigue index, equipment monitoring parameters include aquatic product growth cycle deviation index and microbial concentration. The personnel fatigue index, aquatic product growth cycle deviation index and microbial concentration are respectively , , , the regional status assessment coefficient is calculated by the formula , the specific formula is:

[0057]

[0058] In the formula, is the evaluation coefficient, including the first threshold and the second threshold , , , are the preset proportional coefficients of personnel fatigue index, aquatic product growth cycle, and microbial concentration, respectively, and , proportionality coefficient , , The specific value of is set by those skilled in the art according to specific circumstances and is not limited here.

[0059] The calculation expression of personnel fatigue index is: ,in, Indicates the continuous working time of personnel. It represents the body's own health index BMI (an indicator for comprehensively assessing human health status. It is usually based on multiple aspects of health indicators and data, including physiological, psychological and social factors). The longer the personnel work continuously, the shorter the actual sleep time will be, and the personnel fatigue index will increase, resulting in a decrease in the management ability in the aquaculture area, the failure of timely management and monitoring of aquatic products, and the increase in the probability of accidents.

[0060] The aquatic product growth cycle deviation index is an indicator used to evaluate whether the growth cycle of aquatic products deviates from the standard cycle. It can be used to measure the growth and development of aquatic products and possible influencing factors. The index is usually calculated based on actual observation data, including a comparison of the growth cycle of aquatic products and the standard cycle. The standard cycle refers to the time required for the aquatic product to complete the growth process under specific conditions. For example, for a certain fish, the standard cycle may be 100 days.

[0061] The method of calculating the growth cycle deviation index of aquatic products can vary depending on the situation. The following is a common calculation method:

[0062] Deviation index = (actual growth period - standard period) / standard period;

[0063] The larger the deviation index is, the further the growth cycle of the aquatic product deviates from the standard cycle.

[0064] By monitoring and calculating the deviation index of aquatic product growth cycle, we can evaluate the growth status of aquatic products and promptly discover abnormal conditions that do not conform to the standard cycle, so as to take corresponding measures for adjustment and management. This helps to improve the production efficiency and quality of aquatic products.

[0065] According to the scale and layout of the farm, select some representative sampling points to monitor the concentration of microorganisms. At each sampling point, use sterile containers (such as sampling bottles or closed bags) to collect water samples. Make sure the sampling containers are clean and disinfected to avoid the influence of external contamination on the samples. Send the collected water samples to the laboratory or use appropriate testing equipment for microbial analysis. Commonly used methods include culture method, PCR method, flow cytometer, etc. These methods can detect and count the number and types of microorganisms. During the operation, strictly abide by the laboratory safety operation specifications, and seek guidance and support from professionals as needed.

[0066] After the data is processed to obtain the regional status assessment coefficient, the assessment coefficient of each divided area will be sorted from large to small to generate a sorting table, which will then be sent to the central server, which will conduct inspections in turn according to the sorting table.

[0067] The data processing module also converts the regional status assessment coefficient The first threshold value of the preset standard area status and the second threshold Make a comparison , determine whether to adjust the monitoring time of the area;

[0068] If the regional status assessment coefficient Less than the standard area status threshold , then the regional status of the area is good, and the monitoring period of the area can be appropriately extended;

[0069] If the regional status assessment coefficient Greater than or equal to the standard area status threshold , and less than , it means that the regional status of the area is moderate and there is no need to adjust the monitoring period of the area;

[0070] If the region status is greater than or equal to the standard region status threshold , it means that the regional status of the area is poor and the management of the breeding area does not meet the requirements. It is necessary to shorten the monitoring period of the area. By shortening the monitoring period, the area can be closely monitored and managed to improve the breeding efficiency of the aquaculture farm.

[0071] After talking about the above comparison results, the data processing module will put the areas that need to extend or shorten the monitoring cycle in the same set, for example, {A1, A2, A3, ..., B1, B2, B3, ...}, A1, A2, A3 represent the extended monitoring cycle area, B1, B2, B3 represent the shortened monitoring cycle area, and then calculate the extension or shortening of the monitoring cycle time. The following is a calculation method for adjusting the monitoring cycle.

[0072] The method to extend the monitoring cycle is as follows. The time parameters for extending the monitoring cycle are: , mark the monitoring period as t, t is a time period, and its upper and lower limits are and , set the upper and lower limits to ,Right now , then the expression of the corrected monitoring period is:

[0073]

[0074] The adjusted monitoring period is .

[0075] The method to shorten the monitoring cycle is as follows: the time parameter of shortening the monitoring cycle is , mark the monitoring period as t, t is a time period, and its upper and lower limits are and , set the upper and lower limits to ,Right now , then the expression of the corrected monitoring period is:

[0076]

[0077] The adjusted monitoring period is .

[0078] It should be noted here that The value of varies with different regions.

[0079] According to the above results, for some areas that need to adjust the monitoring cycle, there are only two adjustment results, one is to extend the monitoring cycle, and the other is to shorten the monitoring cycle. The data processing module also records the time difference of extending or shortening the monitoring cycle of each area, and adds all the time differences of the recorded areas. The time parameters of extending the monitoring cycle and shortening the monitoring cycle are calibrated as , , the parameters can be combined to establish an average adjustment monitoring cycle , its calculation expression is:

[0080] In the formula, is the average adjustment monitoring period quantity, It is the parameter to extend the monitoring cycle time. It is a parameter that shortens the detection cycle time. , are the number of regions with extended monitoring periods and the number of regions with shortened monitoring periods, respectively, and , .

[0081] This embodiment collects personnel management status parameters and equipment monitoring parameters, which include personnel fatigue index, aquatic product growth cycle deviation index and microbial concentration, and establishes a regional status assessment coefficient based on the personnel fatigue index, aquatic product growth cycle deviation index and microbial concentration. A ranking table is generated based on the regional status assessment coefficient, and the assessment coefficient is compared with a preset standard regional status threshold. According to the comparison result, a judgment is made as to whether to adjust the monitoring cycle of the region.

[0082] Example 2: In the above-mentioned Example 1, a method is introduced in which a field survey of the area is conducted according to a ranking table, and at the same time, according to the comparison result of the regional status evaluation coefficient and the preset regional status threshold, a period adjustment evaluation coefficient is established to make a corresponding judgment on the monitoring period duration, and then the monitoring period is adjusted. However, the adjustment of the monitoring period duration also needs to take into account the load of the central server, that is, the greater the workload or load borne by the central server, the greater the utilization of its system resources. Increasing or shortening the monitoring period duration will further increase the workload of the central server, overload the central server, and lead to a decrease in the performance of the central server and a weakening of the responsiveness. This embodiment will provide an optimization solution, which specifically includes the following steps:

[0083] The monitoring module is also used to collect the load parameters inside the central server, including request response time, error rate, memory usage rate and the average adjustment monitoring cycle obtained in Example 1, and establish the evaluation coefficient of the central server load with the collected load parameters. The specific expression is as follows:

[0084]

[0085] In the formula, is the evaluation coefficient of the central server load, is the request response time, is the error rate, is the number of concurrent connections, is the average amount of data in the adjusted monitoring period, , , , They are request response time, error rate, number of concurrent connections, and preset proportional coefficient of average adjustment monitoring cycle data volume, and , proportionality coefficient , , , The specific value of is set by those skilled in the art according to specific circumstances and is not limited here.

[0086] The evaluation coefficient of the central server load reflects the index or value of the current load status of the server and is positively correlated with the load parameter. The evaluation coefficient of the central server load increases as the load parameter increases.

[0087] Request response time: refers to the complete time interval from the request sender to the request receiver, or the time from the client sending the request to the server completing the response. If the response time is significantly extended, it may be a manifestation of server overload.

[0088] Error rate: Error rate refers to the proportion or frequency of errors that occur when the server processes requests. It can be used to measure the stability and reliability of the server system. A higher error rate may indicate that the server has problems or anomalies when processing requests. The higher the error rate, the more serious the load on the central server will be.

[0089] Concurrent connections: Concurrent connections refer to the number of users or clients connected to the server at the same time. When the number of concurrent connections exceeds the processing capacity of the server, it may cause server overload.

[0090] Evaluation coefficient based on the central server load To set a standard central server load threshold , and then the evaluation coefficient of the central server load and threshold For comparison:

[0091] like , indicating that the central server is overloaded and has insufficient performance, making it impossible to adjust the monitoring cycle. The early warning module will send an early warning signal to notify the staff to optimize the data;

[0092] like , it means that the server load is light and can meet the adjustment of the monitoring cycle length. At the same time, the early warning module refuses to send an early warning signal.

[0093] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0094] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0095] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0096] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0097] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0098] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0099] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0100] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0101] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A remote video monitoring system for an aquaculture farm, characterized in that: Including monitoring module, data processing module, and central control terminal; The monitoring module is used to obtain the fatigue index of monitoring personnel, the deviation index of fish growth cycle, the concentration of microorganisms and the data of hardware equipment, and send the obtained data to the data processing module; The data processing module is used to receive the data sent by the monitoring module, perform a formula analysis on the data to obtain the regional status assessment coefficient, and send the processing results to the central server; The central server is used to receive the processing results obtained by the data processing module after analysis, store the data in the central server, and send instructions according to the processing results; After the data processing module receives the data sent by the monitoring module, including the personnel fatigue index, the aquatic product growth cycle deviation index, and the microbial concentration, it obtains the regional status assessment coefficient through weighted summation. The calculation expression is: In the formula, is the evaluation coefficient, is the personnel fatigue index, It is the deviation index of aquatic product growth cycle, is the microbial concentration, , , They are respectively the personnel fatigue index, the aquatic product growth cycle deviation index, and the preset proportional coefficient of microbial concentration, and ; The calculation expression of personnel fatigue index is: ,in, Indicates the continuous working time of personnel. Indicates the body's own health index BMI; Deviation of aquatic product growth cycle = (actual growth cycle - standard cycle) / standard cycle; The data processing module is also used to compare the regional state evaluation coefficient with the preset standard regional state first threshold value and standard area status second threshold For comparison: If the regional status assessment coefficient Less than the first threshold of standard area status , then the regional status of the area is good, and the monitoring and management cycle of the area will be extended; If the regional status assessment coefficient Greater than or equal to the first threshold of standard area status , and is less than the second threshold of the standard area status , it means that the regional status of the area is moderate and there is no need to adjust the monitoring cycle of the area; If the area status is greater than or equal to the standard area status second threshold , it means that the regional status of the area is poor and the management of the breeding area does not meet the requirements. It is necessary to shorten the monitoring and management cycle of the area. By shortening the monitoring and management cycle, the area can be closely monitored and managed to improve the breeding efficiency of the aquaculture farm.

2. The remote video monitoring system for aquaculture farms according to claim 1, characterized in that: The data processing module is also used to sort the divided monitoring areas from large to small according to the regional status assessment coefficients, generate a sorting table, and send the generated sorting table to the central server. The central server inspects the aquaculture areas in turn according to the sorting table.

3. The remote video monitoring system for aquaculture farms according to claim 2, characterized in that: The data processing module places the areas that need to extend or shorten the monitoring cycle in the set {A1, A2, A3, ..., B1, B2, B3, ...}, where A1, A2, A3 represent the areas where the monitoring cycle is extended, and B1, B2, B3 represent the areas where the monitoring cycle is shortened, and calculates the time for extending or shortening the monitoring cycle. The specific method is as follows: The method to extend the monitoring cycle is as follows: Extend the monitoring cycle time parameter , mark the monitoring period as t, t is a time period, and its upper and lower limits are and , set the upper and lower limits to ,Right now , then the expression of the corrected monitoring period is: The adjusted monitoring period is , The value of varies with different regions; The method to shorten the monitoring cycle is as follows: shorten the monitoring cycle time parameter to , mark the monitoring period as t, t is a time period, and its upper and lower limits are and , set the upper and lower limits to ,Right now , then the expression of the corrected monitoring period is: The adjusted monitoring period is .

4. The remote video monitoring system for aquaculture farms according to claim 3, characterized in that: The data processing module also records the time difference of extending or shortening the monitoring cycle in each area, adds up all the time differences in the recorded areas, and calibrates the time parameters of extending the monitoring cycle and shortening the monitoring cycle as , , the parameters can be combined to establish an average adjustment monitoring cycle , its calculation expression is: In the formula, is the average adjustment monitoring period quantity, It is the parameter to extend the monitoring cycle time. It is a parameter that shortens the detection cycle time. , are the number of regions with extended monitoring periods and the number of regions with shortened monitoring periods, respectively, and , .

5. The remote video monitoring system for aquaculture farms according to claim 4, characterized in that: The monitoring module is also used to collect the load parameters inside the central server, including request response time, error rate, number of concurrent connections and average adjustment monitoring cycle, and send the collected data to the data processing module.

6. The remote video monitoring system for aquaculture farms according to claim 5, characterized in that: The data collection module establishes the request response time, error rate, number of concurrent connections and average adjustment monitoring cycle according to the collected parameters, and uses the collected load parameters to establish the evaluation coefficient of the central server load. The specific expression is as follows: In the formula, is the evaluation coefficient of the central server load, is the request response time, is the error rate, is the number of concurrent connections, is the average amount of data in the adjusted monitoring period, , , , They are request response time, error rate, number of concurrent connections, and preset proportional coefficient of average adjustment monitoring cycle data volume, and ; The evaluation coefficient of the central server load and threshold For comparison: like , the early warning module will send an early warning signal; like , the early warning module refuses to send the early warning signal.

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