Monitoring method of intelligent culture fishery based on unmanned aerial vehicle

Abstract

The invention discloses an unmanned aerial vehicle-based intelligent aquaculture fishery monitoring method, which comprises an aquaculture fishery and a shore-based system, and is characterized in that the aquaculture fishery is provided with an unmanned aerial vehicle, a temperature sensor, a humidity sensor, a smoke alarm and a light sensor, and the unmanned aerial vehicle is internally provided with a communication module; the shore-based system comprises a computer for monitoring and a computer for flight control, the computer for monitoring is internally provided with an automatic monitoring APP, the automatic monitoring APP is connected with a cloud platform, and the cloud platform comprises a cloud storage; the temperature sensor, the humidity sensor, the smoke alarm and the light sensor form a sensing network, and the overall state data of the fishing ground is acquired through the sensing network and uploaded to the cloud memory through the communication module; and the shore-based system monitors the comprehensive environment of the fishing ground through the automatic monitoring APP. The technical scheme is low in cost, small in pollution, low in human resource consumption, efficient, flexible and good in practicability.

Description

Technical Field

[0001] The present invention relates to the technical field of fish farm monitoring, and in particular to a monitoring method for a smart fish farm based on an unmanned aerial vehicle. Background Art

[0002] my country has a vast territory, a long coastline, vast territorial waters and exclusive economic zones. At the same time, it also has many rivers and lakes inland, vast waters and rich aquatic resources, which provide favorable conditions for the development of fisheries. Fisheries can not only expand food sources, meet national food needs, and enrich the variety of food on the table, but also adjust the agricultural structure and promote rural economic development. Therefore, fisheries play an important role in the national economy. Fishing grounds usually have a large water area, which requires more manpower in management and monitoring, making refined management difficult to implement.

[0003] At present, many small and medium-sized farmers are still using traditional farming models. The main problems of traditional farming models are as follows: 1. Traditional manual monitoring and backward infrastructure cannot guarantee the timeliness of monitoring. The outdated monitoring instruments are not sensitive and monitoring errors occur frequently. 2. During the fish farming process, the ecosystem may become unbalanced due to the influence of factors such as oxygen supply and microorganisms. If this trend is not discovered in time, it will cause eutrophication of the water body, slow growth of the farmed objects, serious bacterial diseases, and reduced quality of aquatic products; 3. The vast water surface is divided by floating objects, which makes the operation by boating difficult and dangerous; Therefore, it is of great significance to design an intelligent farming system for fisheries based on unmanned aerial vehicles. Summary of the invention

[0004] In view of the shortcomings of the prior art, the purpose of the present invention is to provide a monitoring method for a smart aquaculture farm based on an unmanned aerial vehicle, which has low cost, low pollution, low human resource consumption, high efficiency, flexibility and good practicality.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a monitoring method for a smart aquaculture farm based on an unmanned aerial vehicle, comprising an aquaculture farm and a shore-based system, wherein the aquaculture farm is provided with an unmanned aerial vehicle, a temperature sensor, a humidity sensor, a smoke alarm and a light sensor, the unmanned aerial vehicle is provided with a communication module, the shore-based system comprises a monitoring computer and a flight control computer, the monitoring computer is provided with an automatic monitoring APP, the automatic monitoring APP is connected to a cloud platform, and the cloud platform comprises cloud storage; The temperature sensor, humidity sensor, smoke alarm and light sensor constitute a perception network, through which the overall status data of the fishery is obtained, and the overall status data of the fishery is uploaded to the cloud storage through the communication module; the shore-based system monitors the comprehensive environment of the fishery through the automatic monitoring APP.

[0006] As a preferred embodiment: the monitoring computer is connected to the Internet, and after running the automatic monitoring APP, it communicates wirelessly with the cloud storage, and the automatic monitoring APP displays various status data of various sensors in the fishing ground.

[0007] As a preferred embodiment: the drone collects the overall status data of the fishery and transmits it to the cloud platform, and the monitoring computer of the shore-based system quickly reflects the changes in the status of the fishery through cloud data communication with the cloud platform, providing data support for various decisions of the fishery managers.

[0008] Preferably, the humidity sensor is used to measure the air humidity above the local water surface in the fish farm, and the smoke alarm is used to measure the air quality in the fish farm; the light sensor uses a photoresistor as a core component, and the photoresistor can respond to changes in ambient light and monitor sunlight intensity and light changes.

[0009] As a preferred embodiment: the UAV accesses the temperature sensor, humidity sensor, smoke alarm and light sensor one by one by means of timed polling. When approaching the temperature sensor, humidity sensor, smoke alarm or light sensor, the communication module automatically establishes a wireless connection with the communication device in the temperature sensor, humidity sensor, smoke alarm or light sensor to obtain data collected by the temperature sensor, humidity sensor, smoke alarm and light sensor. The polling path of the UAV is preset in the flight control computer of the UAV system through a program.

[0010] Preferably, the UAV uses a Beidou / GPS module for positioning to accurately locate the flight route, and the flight control uses a computer to detect the flight route offset and automatically correct it, while setting an offset warning to ensure the safety of the fish farm and the UAV.

[0011] As a preferred embodiment: the automatic monitoring APP collects and integrates data collected by temperature sensors, humidity sensors, smoke alarms and light sensors, and uploads each data to cloud storage, thereby realizing the functions of rapid remote data transmission and monitoring.

[0012] The beneficial effects of the present invention are as follows: compared with the prior art, the present invention is provided with a temperature sensor, a humidity sensor, a smoke alarm and a light sensor to form a perception network, through which the overall status data of the fishery is obtained, and the overall status data of the fishery is uploaded to the cloud storage through the communication module; the shore-based system monitors the comprehensive environment of the fishery through the automatic monitoring APP. The use of drones can achieve the movement capability that is not constrained by the floating object grid, improve the efficiency of data collection, and with the background support of the cloud platform's cloud data, the automatic monitoring APP can quickly display various status data of the fishery sensor, quickly reflect the changes in the status of the fishery, and provide data support for various decisions of the fishery managers. Low cost, low pollution, low human resource consumption, high efficiency, flexibility and good practicality.

[0013] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 A schematic diagram of the system structure of an embodiment of the present invention; Figure 2 Schematic diagram of the relationship between the monitoring system modules according to an embodiment of the present invention. DETAILED DESCRIPTION

[0015] In the description of this embodiment, it should be noted that, if the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", "front", "back", etc. appear, the orientation or position relationship indicated is based on the orientation or position relationship shown in the accompanying drawings, which is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore, cannot be understood as limiting the present invention. In addition, if the terms "first", "second", and "third" appear, they are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0016] See also Figure 1 and Figure 2 The present invention discloses a monitoring method for a smart aquaculture farm based on an unmanned aerial vehicle, comprising a aquaculture farm 9 and a shore-based system, wherein the aquaculture farm 9 is provided with an unmanned aerial vehicle 1, a temperature sensor 11, a humidity sensor 12, a smoke alarm 13 and a light sensor 14, wherein the unmanned aerial vehicle 1 is provided with a communication module 3, wherein the shore-based system comprises an onshore base 6, a monitoring computer 8 and a flight control computer 4, wherein the monitoring computer 8 is provided with an automatic monitoring APP 7, wherein the automatic monitoring APP 7 is connected to a cloud platform 5, wherein the cloud platform 5 comprises a cloud storage; The temperature sensor 11, humidity sensor 12, smoke alarm 13 and light sensor 14 constitute a perception network 10, through which the overall status data of the fishery is obtained and uploaded to the cloud storage through the communication module 3; the shore-based system monitors the comprehensive environment of the fishery through the automatic monitoring APP7.

[0017] Preferably, the overall status data of the fishery includes temperature, humidity, water surface sunshine intensity and air quality data above the water body. The sensor arrangement of the sensing network 10 is determined according to the area, shape and distribution of the floating grid of the fishery. Since the data is collected by drone polling, the wiring workload is greatly reduced. These different types of sensor data can be comprehensively analyzed to help manage and optimize the breeding environment.

[0018] The monitoring computer 8 is connected to the Internet, and after running the automatic monitoring APP 7, it communicates wirelessly with the cloud storage, and the automatic monitoring APP 7 displays various status data of various sensors in the fishing field. As a preferred embodiment, with the background support of the cloud platform's cloud data, the automatic monitoring APP 7 can quickly display various status data of the fishing field sensors.

[0019] The drone 1 collects the overall status data of the fishery and transmits it to the cloud platform 5. The monitoring computer 8 of the shore-based system quickly reflects the changes in the status of the fishery through cloud data communication with the cloud platform 5, providing data support for various decisions of the fishery managers.

[0020] The humidity sensor 12 is used to measure the air humidity above the local water surface of the fish farm. The air humidity data will affect the oxygen content in the air, and then affect the dissolved oxygen level in the water. Appropriate humidity helps to maintain sufficient oxygen in the water, which is beneficial to the survival of fish.

[0021] The smoke alarm 13 is used to measure the air quality of the fish farm. The function and accuracy of the smoke alarm 13 are relatively limited, but its cost is low and economical, making it possible to lay it on a large scale. It is not sensitive to conventional air quality changes (such as slight increase in PM2.5, greenhouse gases, etc.), but it usually detects and issues an alarm for events such as a sharp increase in particulate matter in the air (such as barbecue smoke, burning substances, etc.), which is more suitable for the needs of fish farms.

[0022] The optical sensor 14 uses a photoresistor as a core component, which can respond to changes in ambient light and monitor sunlight intensity and light changes. By monitoring sunlight intensity, the fish farm can optimize the breeding environment and improve the health and growth rate of fish.

[0023] The drone 1 accesses the temperature sensor 11, humidity sensor 12, smoke alarm 13 and light sensor 14 one by one by means of timed polling. When approaching the temperature sensor 11, humidity sensor 12, smoke alarm 13 or light sensor 14, the communication module 3 automatically wirelessly connects with the communication device in the temperature sensor 11, humidity sensor 12, smoke alarm 13 or light sensor 14 to obtain the data collected by the temperature sensor 11, humidity sensor 12, smoke alarm 13 and light sensor 14; the polling path of the drone 1 is preset in the flight control computer of the drone system through a program. As a preferred embodiment, the polling path of the drone 1 can be changed by modifying the program to change the preset path.

[0024] The UAV 1 uses the Beidou / GPS module 2 for positioning, accurately locates the flight route, and the flight control computer 4 detects the flight route deviation and automatically corrects it, and sets a deviation warning, thereby ensuring the safety of the fish farm and the UAV.

[0025] The automatic monitoring APP 7 collects and integrates the data collected by the temperature sensor 11, the humidity sensor 12, the smoke alarm 13 and the light sensor 14, and uploads each data to the cloud storage, thereby realizing the functions of rapid remote data transmission and monitoring.

[0026] In actual application, the temperature sensor 11, humidity sensor 12, smoke alarm 13 and light sensor 14 form a perception network, through which the overall status data of the fishery is obtained, and the overall status data of the fishery is uploaded to the cloud storage through the communication module 3; the shore-based system monitors the comprehensive environment of the fishery through the automatic monitoring APP7. The use of drones can achieve the movement ability that is not constrained by the floating object grid, improve the efficiency of data collection, and with the background support of the cloud platform's cloud data, the automatic monitoring APP7 can quickly display various status data of the fishery sensor, quickly reflect the changes in the status of the fishery, and provide data support for various decisions of the fishery managers. Low cost, low pollution, low human resource consumption, high efficiency, flexibility and good practicality.

[0027] The specific description of the present invention in the above embodiments is only used to further illustrate the present invention and cannot be understood as limiting the scope of protection of the present invention. Technical engineers in this field may make some non-essential improvements and adjustments to the present invention based on the contents of the above invention, which fall within the scope of protection of the present invention.

Claims

1. A method for monitoring a smart aquaculture farm based on an unmanned aerial vehicle, comprising a aquaculture farm (9) and a shore-based system, characterized in that: The fish farm (9) is provided with a drone (1), a temperature sensor (11), a humidity sensor (12), a smoke alarm (13) and a light sensor (14); the drone (1) is provided with a communication module (3); the shore-based system comprises a shore base (6), a monitoring computer (13) and a flight control computer (4); the monitoring computer (8) is provided with an automatic monitoring APP (7); the automatic monitoring APP (7) is connected to a cloud platform (5); and the cloud platform (5) comprises a cloud storage; The temperature sensor (11), humidity sensor (12), smoke alarm (13) and light sensor (14) constitute a sensing network (10), and the overall status data of the fishing ground is obtained through the sensing network (10), and the overall status data of the fishing ground is uploaded to the cloud storage through the communication module (3); the shore-based system monitors the comprehensive environment of the fishing ground through the automatic monitoring APP (7).

2. The monitoring method of a smart aquaculture fishery based on an unmanned aerial vehicle according to claim 1 is characterized in that: The monitoring computer (8) is connected to the Internet and communicates with the cloud storage wirelessly after running the automatic monitoring APP (7). The automatic monitoring APP (7) displays various status data of various sensors in the fishing ground.

3. The monitoring method of a smart fish farm based on an unmanned aerial vehicle according to claim 2 is characterized in that: The drone (1) collects the overall status data of the fishery and transmits it to the cloud platform (5), and the monitoring computer (8) of the shore-based system quickly reflects the changes in the status of the fishery through cloud data communication with the cloud platform (5), thereby providing data support for various decisions of the fishery management personnel.

4. The monitoring method of a smart fish farm based on an unmanned aerial vehicle according to claim 3 is characterized by: The humidity sensor (12) is used to measure the air humidity above the local water surface of the fish farm, and the smoke alarm is used to measure the air quality of the fish farm; the light sensor uses a photoresistor as a core component, and the photoresistor can respond to changes in ambient light and monitor sunlight intensity and light changes.

5. The monitoring method of a smart aquaculture fishery based on an unmanned aerial vehicle according to claim 4 is characterized in that: The drone (1) accesses the temperature sensor (11), humidity sensor (12), smoke alarm (13) and light sensor (14) one by one in a timed polling manner; when approaching the temperature sensor (11), humidity sensor (12), smoke alarm (13) or light sensor (14), the communication module (3) automatically establishes a wireless connection with the communication device in the temperature sensor (11), humidity sensor (12), smoke alarm (13) or light sensor (14) to obtain data collected by the temperature sensor (11), humidity sensor (12), smoke alarm (13) and light sensor (14); the polling path of the drone (1) is preset in the flight control computer of the drone system through a program.

6. The monitoring method of a smart fish farm based on an unmanned aerial vehicle according to claim 5 is characterized by: The drone (1) uses a Beidou / GPS module (2) for positioning, accurately positioning the flight route, and the flight control computer (4) detects the flight route deviation and automatically corrects it, while setting a deviation warning, thereby ensuring the safety of the fish farm and the drone.

7. The monitoring method of a smart fish farm based on an unmanned aerial vehicle according to claim 6 is characterized by: The automatic monitoring APP (7) collects and integrates data collected by the temperature sensor (11), the humidity sensor (12), the smoke alarm (13) and the light sensor (14), and uploads each data to cloud storage, thereby realizing the functions of rapid remote data transmission and monitoring.

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