Big data-based fishery resource dynamic evaluation system and method

Abstract

The application relates to the technical field of fishery resource management, and discloses a fishery resource dynamic evaluation system and method based on big data, which comprises a float, a storage tank and a submerged base respectively mounted on the upper end and the lower end of the float, and a plurality of feeding plates arranged on the periphery of the float; the plurality of feeding plates are provided with a plurality of feeding openings, and the plurality of feeding plates are connected with a floating net through a sensor; a data acquisition module comprises a breeding standard acquisition unit and a breeding data acquisition unit; the breeding standard acquisition unit is used for acquiring fish breeding standard data through a big data network; and the breeding data acquisition unit is used for acquiring various environmental data and fish school activity data of a breeding area. The plurality of feeding plates of the float are shaken to feed the breeding area with bait, the movement characteristics of the fish school after the bait is fed are acquired, and the quantity of bait fed each time is calculated in combination with the fish school activity.

Description

Technical Field

[0001] This invention relates to the field of fishery resource management technology, specifically to a dynamic assessment system and method for fishery resources based on big data. Background Technology

[0002] Fishery resources include catchable organisms, genetic resources, and product resources. Among them, organisms are the core and directly support fishery production. The reproduction and natural regeneration of organism populations replenish resources, but overfishing will destroy their self-regulation ability and lead to resource depletion.

[0003] In recent years, fishermen have responded to the national call and followed the aquaculture technical specifications issued by the Ministry of Agriculture and Rural Affairs and the aquaculture industry to raise local fish and release them into public areas such as oceans, rivers, and lakes in order to restore and replenish natural resources and improve the ecological environment.

[0004] However, in the process of individual aquaculture, most fishermen raise fish in nearby ponds or build aquaculture ponds. During the raising process, when some of the feed is not digested by the fish, it will decompose and release pollutants such as ammonia nitrogen and nitrite, which will lead to eutrophication of the water and explosive growth of algae. This will affect the fish's oxygen deficiency and death, and further deteriorate the aquaculture environment.

[0005] To address these issues, this invention proposes a dynamic assessment system and method for fishery resources based on big data. Summary of the Invention

[0006] The purpose of this invention is to provide a dynamic assessment system and method for fishery resources based on big data, in order to solve the problem that existing aquaculture technologies prioritize output while neglecting environmental impact.

[0007] The objective of this invention can be achieved through the following technical solutions:

[0008] A big data-based dynamic assessment system for fishery resources includes:

[0009] The float and the storage tanks and sinking bases respectively mounted on the upper and lower ends of the float, and the float is also provided with multiple feeding plates on its outer periphery;

[0010] The feeding boards are connected by a floating net, and a sensor is installed between the floating net and the feeding board;

[0011] The data acquisition module includes a breeding standard acquisition unit and a breeding data acquisition unit;

[0012] Aquaculture standard acquisition unit, used to acquire fish aquaculture standard data through big data networks;

[0013] The aquaculture data acquisition unit is used to acquire various environmental data and fish activity data of the aquaculture area;

[0014] The feeding metering module is used to calculate feed feeding data based on the acquired environmental data of the aquaculture area and the fish activity data.

[0015] The feeding adjustment module adjusts the feeding method based on the feeding data.

[0016] The final evaluation module is used to obtain final evaluation and analysis data based on the obtained feeding quantity and various environmental data of the breeding area.

[0017] Preferably, the fish activity data is obtained through the following method:

[0018] Trial feeding was conducted in the aquaculture area;

[0019] The movement characteristics of the fish after trial feeding were obtained, including: the time it takes for the fish to rise from the bottom to the surface, the time it spends at the surface, the time it takes to fall from the surface to the bottom, the swimming speed, and the degree of fish clustering in the feeding area.

[0020] Preferably, the feed feeding data is obtained through the following method:

[0021] The fluctuation impact data of each data point is calculated based on the obtained environmental data of the aquaculture area and the fish aquaculture standard data.

[0022] The current activity level of the fish school is calculated based on the movement characteristics of the fish school after the trial feeding.

[0023] Based on the obtained current fish activity level and the data on the impact of various fluctuations, the feed feeding data is calculated comprehensively.

[0024] Preferably, the activity level of the fish school is obtained through the following methods:

[0025] The activity level of the fish school is calculated by combining the relative frequency deviation between the fish movement characteristics and the feeding board, as well as the proportion of bait coverage area.

[0026] The average activity level of a fish school is calculated by combining the obtained fish school activity level with the number of selected fish schools. The fish school activity level is then obtained by combining the average activity level with the fish school density.

[0027] Preferably, the feeding adjustment module works as follows:

[0028] Based on the obtained bait feeding data, adjust the straight-line distance between the feeding board and the float to adjust the bait coverage area;

[0029] Adjust the shaking frequency of the feeding board to control the feeding speed.

[0030] Preferably, the final evaluation and analysis data is obtained in the following ways:

[0031] The final evaluation and analysis data are calculated based on the actual amount of feed fed each day, the amount of feed not consumed, and the daily increase in impurities in the water.

[0032] This invention also provides a method for dynamic assessment of fishery resources based on big data, comprising the following steps:

[0033] S1. Obtain fish farming standard data through big data networks;

[0034] S2. Obtain various environmental data and fish activity data of the aquaculture area;

[0035] S3. Calculate feed feeding data based on the obtained environmental data of the breeding area and fish activity data;

[0036] S4. Adjust the feeding method based on the feed feeding data;

[0037] S5. Based on the obtained feeding quantity and various environmental data of the breeding area, obtain the final evaluation and analysis data.

[0038] The beneficial effects of this invention are:

[0039] 1. This invention uses the shaking of multiple feeding plates on a float to release feed into the aquaculture area, obtains the movement characteristics of the fish after feeding, calculates the activity level of the fish within the feeding area, and adjusts the amount of feed each time accordingly based on the fish activity level and other data to ensure the healthy growth of the fish and prevent excessive eutrophication in the environment. Furthermore, based on the fish activity level, various environmental data of the aquaculture area, and the amount of feed each time, the ecological efficiency of the aquaculture feed is evaluated, reminding farmers not to ignore the environmental impact during the breeding process.

[0040] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0041] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a three-dimensional schematic diagram of the float for the dynamic assessment system and method for fishery resources based on big data according to the present invention.

[0043] Figure 2This is a system module diagram of the fishery resource dynamic assessment system and method based on big data of the present invention.

[0044] Figure 3 This is a flowchart illustrating the steps of the big data-based dynamic assessment system and method for fishery resources of this invention.

[0045] The components include: 1. Float; 2. Storage tank; 3. Submersible base; 4. Feeding plate; 5. Sensor; 6. Floating net; 7. Feeding port. Detailed Implementation

[0046] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0047] Please see Figure 1-2 As shown, this invention is a dynamic assessment system and method for fishery resources based on big data, comprising:

[0048] The float 1 and the storage tank 2 and the sinking base 3 are respectively mounted on the upper and lower ends of the float 1. Multiple feeding plates 4 are also provided on the outer periphery of the float 1.

[0049] Multiple feeding boards 4 are connected by floating nets 6, and sensors 5 are provided between the floating nets 6 and the feeding boards 4;

[0050] The float 1 has an outer shell made of polyethylene material, which has good corrosion resistance. It contains a variety of waterproof electronic components. The storage tank 2 is used to load bait and is equipped with a controller, valves and connecting pipes. The opening and closing of the valves controls the distribution of bait from the storage tank 2 to each connecting pipe. The connecting pipes are connected to each feeding plate 4. When the bait enters the pipe, the feeding plate 4 is activated, causing the feeding plate 4 to start shaking and the bait to be released into the breeding area. The feeding plate 4 is made of medical-grade silicone and glass fiber skeleton, which can simulate the movement of fish and induce the fish to gather together.

[0051] The submersible base 2 is used to acquire various data of the aquaculture area and the swimming data of the fish. The submersible base 2 is equipped with multiple sensors, including temperature sensors, vision sensors, pH sensors, dissolved oxygen sensors, etc. The vision sensors mainly observe the relevant data of the fish swimming in the water, and focus on observing the number of feeding cycles, swimming direction, and degree of gathering of the fish after trial feeding.

[0052] Sensor 5 mainly consists of a vision sensor (BK-S1S sensor) for collecting images of fish gathering and swimming in the aquaculture area, a temperature sensor (CRK-D600C model) for collecting water temperature in the aquaculture area, and a pH sensor (621 model). It can also simultaneously detect data such as conductivity, dissolved oxygen, and turbidity.

[0053] The data acquisition module includes a breeding standard acquisition unit and a breeding data acquisition unit;

[0054] Aquaculture standard acquisition unit, used to acquire fish aquaculture standard data through big data networks;

[0055] The aquaculture standard acquisition unit mainly obtains fish aquaculture standards by accessing the aquaculture technical specifications and related aquaculture knowledge issued by the Ministry of Agriculture and Rural Affairs or the aquatic industry through data networks. For example, taking silver carp as an example, in summer, when the suitable water temperature is 25 to 30 degrees Celsius, every 1,000 catties of silver carp should be fed artificial feed three to four times a day, with a total amount of 20 to 25 catties. Correspondingly, when the aquaculture environment changes, the amount of feed given each time will change accordingly.

[0056] The aquaculture data acquisition unit is used to acquire various environmental data and fish activity data of the aquaculture area;

[0057] The main environmental data for the aquaculture area include water temperature, dissolved oxygen, pH value, and impurity content.

[0058] Fish are poikilothermic animals, and the temperature of the water is extremely sensitive to them. When the water temperature rises, it will promote fish metabolism and increase their food intake; however, if the temperature exceeds the critical temperature or falls below the minimum feeding temperature, their food intake will decrease significantly or even stop.

[0059] Dissolved oxygen is a core limiting factor for fish feeding and digestion. When the oxygen content in the water is high, fish will be more active, and their appetite will increase significantly. When the oxygen content is low, the activity level of fish will decrease accordingly, and their appetite will also decrease.

[0060] The pH value of water is an important physiological adaptability indicator for fish. However, when the pH value is too high, fish will suffer from poisoning, especially causing significant damage to the gills.

[0061] Impurities in the water are mostly ammonia nitrogen and nitrite. Excessive levels of ammonium salts and nitrites can affect the fish's appetite. In such cases, water changes, oxygenation, or biological regulation techniques are necessary.

[0062] The feeding metering module is used to calculate feed feeding data based on the acquired environmental data of the aquaculture area and the fish activity data.

[0063] The feeding adjustment module adjusts the feeding method based on the feeding data.

[0064] Specifically, the feeding method is adjusted according to the amount of bait obtained. When the amount of bait increases, the shaking frequency of the feeding plate 4 is increased and the opening degree of the valve in the storage tank 2 is increased accordingly. When the amount of bait decreases, the shaking frequency of the feeding plate 4 is decreased and the opening degree of the valve in the storage tank 2 is decreased accordingly.

[0065] The final evaluation module is used to obtain final evaluation and analysis data based on the obtained feeding quantity and various environmental data of the breeding area.

[0066] The fish activity data is obtained through the following steps:

[0067] Trial feeding was conducted in the aquaculture area;

[0068] The movement characteristics of the fish after trial feeding were obtained, including: the time it takes for the fish to rise from the bottom to the surface, the time it spends at the surface, the time it takes to fall from the surface to the bottom, the swimming speed, and the degree of fish clustering in the feeding area.

[0069] Specifically, before the first feeding, a trial feeding is conducted to induce the fish to swim. After the trial feeding, underwater cameras capture the time it takes for the fish to swim from the bottom to the surface, the time they stay on the surface, the time it takes to return from the surface to the bottom, their swimming speed, the number of cycles of movement, and the degree of clustering of the fish, which are used as data to calculate the activity level of the fish.

[0070] The bait feeding data was obtained through the following methods:

[0071] The fluctuation impact data of each data point is calculated based on the obtained environmental data of the aquaculture area and the fish aquaculture standard data.

[0072] The current activity level of the fish school is calculated based on the movement characteristics of the fish school after the trial feeding.

[0073] Based on the obtained current fish activity level and the data on the impact of various fluctuations, the feed feeding data is calculated comprehensively.

[0074] Specifically, the acquired environmental data is compared with the aquaculture labeling data to obtain the fluctuation impact data, and the feed placement needs to be adjusted based on the results of the fluctuation impact data;

[0075] For example, taking silver carp as an example, when the water temperature is between 20 and 25 degrees Celsius in summer, every 1,000 catties of silver carp should be fed artificial feed three to four times a day, with a total feed amount of 20 to 25 catties. Correspondingly, when the breeding environment changes, the amount of feed given each time will change accordingly.

[0076] For example, when the fluctuating temperature is at 25 degrees Celsius, which is a comfortable environment for silver carp, but the temperature is relatively high, thus reducing the amount of feed by two percent;

[0077] When the changed temperature is 20 degrees Celsius, this temperature is not in the silver carp's comfortable environment and is relatively low compared to the comfortable environment temperature. Therefore, the feed should be reduced by 10%. Other fluctuation data should be adjusted accordingly.

[0078] When the oxygen content in the water fluctuates within a comfortable range, the amount of feed should be adjusted slightly. When the oxygen content in the water is not within a comfortable range, the amount of feed should be adjusted more significantly. If the oxygen content is high, the amount of feed should be increased, and if the oxygen content is low, the amount of feed should be decreased.

[0079] When the pH value of the water is high but within a comfortable range, the amount of feed should be increased slightly. However, when the pH value of the water is too high and exceeds the maximum comfortable range, the amount of feed should be reduced and the water quality should be improved accordingly. When the pH value of the water is low, the amount of feed should be reduced accordingly.

[0080] When the water has a high level of impurities, reduce the amount of feed given; when the water has a low level of impurities, reduce the amount of feed given.

[0081] Finally, adjust the amount of bait according to the activity level of the fish. When the activity level is high, the amount of bait can be increased accordingly, and when the activity level is low, the amount of bait should be reduced accordingly.

[0082] The activity level of the fish population was obtained through the following methods:

[0083] The activity level of the fish school is calculated by comprehensively considering the relative frequency deviation between the fish movement characteristics and the feeding board 4, as well as the proportion of bait coverage area.

[0084] The average activity level of a fish school is calculated by combining the obtained fish school activity level with the number of selected fish schools. The fish school activity level is then obtained by combining the average activity level with the fish school density.

[0085] Specifically, the feeding action cycle reflects the fish's enthusiasm for feeding. When the fish are active, their feeding desire is greater, resulting in more action cycles. Conversely, when the fish are less active, their feeding desire is less, resulting in more action cycles.

[0086] Swimming speed is a further indicator of the health of the fish. Under normal circumstances, fish in the comfortable breeding environment will swim faster when they are frightened or when it is feeding time. Conversely, they will swim slower and their swimming amplitude will also decrease accordingly.

[0087] As social creatures, fish tend to congregate and swim together in the feeding area when they are feeding together, competing for food. This makes the fish population in the feeding area more dense and thus appears more active.

[0088] The shaking frequency deviation of the feeding board can be used to judge whether the current feeding rhythm matches the activity level of the fish. This is calculated by dividing the current shaking frequency of the feeding board by the ideal frequency, with the current shaking frequency as the numerator and the ideal frequency as the denominator. The area covered by the feeding board indicates the feeding efficiency. The visual sensor inside the submerged base 2 acquires water surface images, and the feeding area is divided by the area covered by the feeding area and the area covered by the aquaculture area, with the feeding area as the numerator and the aquaculture area as the denominator. This yields the feeding ratio and the area covered by the feeding board. When the shaking frequency is too high but the area covered by the feeding board is insufficient, the activity level will decrease accordingly, prompting an adjustment to the feeding frequency. Conversely, when the coverage area is large and the frequency is moderate, the current feeding strategy can stimulate the fish's feeding enthusiasm.

[0089] The number of fish swimming to the surface is recorded to obtain the number of action cycles, swimming speed, swimming amplitude, and density of fish gathering during the trial feeding. The dwell time is used as the numerator, the ascent time plus the descent time are used as the denominator, the proportion of feeding time is multiplied by the feeding time weight coefficient, and the product of swimming speed and speed weight coefficient, the density of fish gathering and density weight coefficient, plus the frequency deviation and the coverage area of ​​the bait are added to calculate the activity level of the selected fish group. The time weight coefficient, speed weight coefficient, and density weight coefficient are added to 1. The comprehensive calculation of fish group activity level is divided by the number of selected fish group, with fish group activity level as the numerator and the recorded number of fish group as the denominator. Finally, the fish group activity level is calculated by multiplying it with the fish density in the feeding area to obtain the fish group activity level.

[0090] The current amount of feed is calculated based on the changes in fish activity, temperature fluctuations, water quality fluctuations, dissolved oxygen levels, and impurities in the water.

[0091] Based on the calculated amount of bait to be released, the oscillation frequency of the feeding board 4 and the range of the floating net 6 are adjusted accordingly.

[0092] The feeding adjustment module works as follows:

[0093] Based on the obtained bait feeding data, adjust the straight-line distance between the feeding board 4 and the float 1 to adjust the bait coverage area;

[0094] Feed is delivered from the storage tank 2 to the feeding ports 7 of each feeding plate 4;

[0095] Adjust the shaking frequency of the feeding board 4 to control the feeding speed;

[0096] Specifically, when feeding is increased, it indicates that the current environment for the fish is relatively comfortable and the fish activity level is relatively good. At this time, the opening degree of the valve in the storage tank 2 is increased, allowing the feed to enter the pipes connecting each feeding plate 4 and the storage tank 2. At the same time, the distance between the feeding plate 4 and the float 1 is appropriately adjusted. After the distance between the feeding plate 4 and the float 1 is adjusted, the water area covered by the float net 6 is wider, making the range of the thrown feed wider, thereby making the fish swim more actively, further promoting feeding efficiency, and also reducing the occurrence of oxygen deficiency caused by excessive gathering of fish.

[0097] When the amount of feed needs to be reduced, the opening degree of the valve in the storage tank 2 should be reduced, and the shaking frequency of the feeding plate 4 should be reduced accordingly, so that the feed is slowly fed to avoid the fish not being able to digest the feed in time, which would further reduce the fish's appetite and cause the feed to float on the water surface for a long time, gradually leading to negative nutrition in the aquaculture area.

[0098] Before feeding the fish a second time, it is also necessary to collect environmental data of the aquaculture area. At this time, it is important to pay attention to the amount of leftover feed from the previous feeding. Uneaten feed will gradually decompose into ammonia nitrogen, thereby increasing the eutrophication of the aquaculture area and affecting the ecological environment of the aquaculture area. Therefore, before feeding the fish a second time, it is necessary to take the amount of leftover feed from the previous feeding as a factor affecting impurities in the water, and thus reduce the amount of feed for the second feeding accordingly.

[0099] Correspondingly, based on the distribution of uneaten bait, the distance between the feeding plate 4 and the float 1 is adjusted, and the coverage of the float net 1 is adjusted to reduce the bait distribution being too widespread. In summary, before the second feeding, a trial feeding is also conducted to obtain the activity level of the fish. Based on the various data collected in the second feeding, the amount of bait for the second feeding is calculated and the feeding is carried out.

[0100] The final evaluation and analysis data were obtained through the following methods:

[0101] The final evaluation and analysis data are calculated based on the actual amount of feed fed each day, the amount of feed not consumed, and the daily increase in impurities in the water.

[0102] The actual amount of feed fed each day is obtained by summing the amounts of feed given each time. The difference between the first and last water impurity samples is the increase in water impurities. The amount of uneaten feed is used as the independent variable for the increase in water impurities, and the increase in water impurities is used as the base. The final evaluation and analysis data is obtained by using the actual amount of feed given as the numerator, the increase in water impurities, and the amount of uneaten feed as the denominator.

[0103] The final assessment and analysis data is mainly used to identify the daily feeding of fish into the aquaculture area. Undigested feed sinks into the aquaculture area, gradually affecting the ammonia nitrogen content in the water. This causes the impurities in the aquaculture area to gradually increase. This serves as a basis to remind fish farmers not to focus solely on yield while neglecting the environmental impact.

[0104] Please see Figure 3 As shown, the present invention also provides a method for dynamic assessment of fishery resources based on big data, including the following steps:

[0105] S1. Obtain fish farming standard data through big data networks;

[0106] S2. Obtain various environmental data and fish activity data of the aquaculture area;

[0107] S3. Calculate feed feeding data based on the obtained environmental data of the breeding area and fish activity data;

[0108] S4. Adjust the feeding method based on the feed feeding data;

[0109] S5. Based on the obtained feeding quantity and various environmental data of the breeding area, obtain the final evaluation and analysis data.

[0110] The method is applied to the above system and the technical effect obtained is the same as that obtained by the above system, so it will not be described in detail here.

[0111] The above description is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined in the claims, they should all fall within the protection scope of the present invention.

Claims

1. A dynamic assessment system for fishery resources based on big data, characterized in that, include: The float (1) and the storage tank (2) and the sinking base (3) respectively mounted on the upper and lower ends of the float (1) are provided. Multiple feeding plates (4) are also provided on the outer periphery of the float (1). Each of the feeding plates (4) is provided with a plurality of feeding ports (7), and the plurality of feeding plates (4) are connected to the floating net (6) through sensors (5); The data acquisition module includes a breeding standard acquisition unit and a breeding data acquisition unit; Aquaculture standard acquisition unit, used to acquire fish aquaculture standard data through big data networks; The aquaculture data acquisition unit is used to acquire various environmental data and fish activity data of the aquaculture area; The fish activity data was obtained through the following methods: Trial feeding was conducted in the aquaculture area; The movement characteristics of the fish after trial feeding were obtained, including: the time it takes for the fish to rise from the bottom to the surface, the time it spends at the surface, the time it takes to fall from the surface to the bottom, the swimming speed, and the degree of fish clustering in the feeding area. The feeding metering module is used to calculate feed feeding data based on the acquired environmental data of the aquaculture area and the fish activity data. The bait feeding data was obtained through the following methods: The fluctuation impact data of each environmental data is calculated based on the obtained environmental data of the aquaculture area and the fish aquaculture standard data. The current activity level of the fish school is calculated based on the movement characteristics of the fish school after the trial feeding. Based on the obtained data on the current fish activity level and the fluctuations in various environmental data, the feed feeding data is calculated comprehensively. The activity level of the fish population was obtained through the following methods: The activity level of the target fish is calculated by comprehensively considering the relative frequency deviation between the fish movement characteristics and the feeding board (4) and the proportion of bait coverage area. The average activity level of the target fish is calculated by combining the obtained fish activity level with the number of selected fish groups. The fish activity level is then obtained by combining the average activity level of the fish groups with the fish density. The feeding adjustment module adjusts the feeding method based on the feeding data. The feeding adjustment module works as follows: Based on the obtained bait feeding data, adjust the straight-line distance between the feeding board (4) and the float (1) to adjust the bait coverage area; Adjust the shaking frequency of the feeding board (4) to control the feeding speed; The final evaluation module is used to obtain final evaluation and analysis data based on the obtained feeding quantity and various environmental data of the breeding area; The final evaluation and analysis data were obtained through the following methods: The final evaluation and analysis data are calculated based on the actual amount of feed fed each day, the amount of feed not consumed, and the daily increase in impurities in the water.

2. A method for dynamic assessment of fishery resources based on big data, applicable to the dynamic assessment system for fishery resources based on big data as described in claim 1, characterized in that, Includes the following steps: S1. Obtain fish farming standard data through big data networks; S2. Obtain various environmental data and fish activity data of the aquaculture area; S3. Calculate feed feeding data based on the obtained environmental data of the breeding area and fish activity data; S4. Adjust the feeding method based on the feed feeding data; S5. Based on the obtained feeding quantity and various environmental data of the breeding area, obtain the final evaluation and analysis data.

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