CN206960988U - A kind of intelligence based on cloud framework is breeded fish monitoring system - Google Patents

Abstract

The utility model relates to an intelligent fish farming monitoring system based on a cloud architecture, the system includes a fish pond detection control device (1), a local monitoring device (2), a cloud processing server (3) and a monitoring terminal, the fish pond The detection and control equipment (1) is communicatively connected with the local monitoring equipment (2), and the local monitoring equipment (2) is connected to the cloud processing server (3) through the Internet network, and the monitoring terminals are provided with multiple and respectively connected to the cloud Process server (3). Compared with the prior art, the utility model has a high degree of intelligence, and at the same time, the machine learning algorithm calculation with a large amount of calculation is run on the cloud processing server (3), which is conducive to improving the efficiency of data processing operation.

Description

A cloud-based intelligent fish farming monitoring system

technical field

The utility model relates to a fish farming monitoring system, in particular to an intelligent fish farming monitoring system based on cloud architecture.

Background technique

China is a big country in aquaculture industry. With the adjustment of agricultural structure in recent years, my country's aquaculture industry is gradually changing from traditional artificial breeding to industrialized and intensive farming. In order to speed up the growth of fish, reduce the cost of aquaculture, and ensure the safety of aquaculture, it is necessary to monitor and control parameters such as water quality temperature, dissolved oxygen, and pH value in real time to improve the automation and intelligence of aquaculture. At present, aquaculture has moved from single on-site monitoring to remote distributed monitoring. However, the previous aquaculture monitoring network is not open, the communication distance is limited, the error correction ability is not strong, and the real-time performance of multi-computer communication is poor. At the same time, the aquaculture monitoring system is only a single remote monitoring of fish farming, but does not feed back sensors and fish growth status as samples to train an expert library. Big data calculations such as real-time sensor acquisition parameters, fish farming parameters and environmental parameters are not put into cloud server calculations, which limits the intelligent development of aquaculture.

Utility model content

The purpose of this utility model is to provide an intelligent fish farming monitoring system based on cloud architecture in order to overcome the above-mentioned defects in the prior art.

The purpose of this utility model can be achieved through the following technical solutions:

An intelligent fish farming monitoring system based on cloud architecture, the system includes fish pond detection and control equipment, local monitoring equipment, cloud processing server and monitoring terminal, said fish pond detection and control equipment communicates with local monitoring equipment, and said The local monitoring equipment is connected to the cloud processing server through the Internet network, and multiple monitoring terminals are provided and connected to the cloud processing server respectively.

The fish pond detection and control device includes a fish pond end processor and a sensor detection unit and a control unit respectively connected thereto, and the fish pond end processor is connected to a local monitoring device through a communication module.

The sensor detection unit includes a water temperature sensor, a dissolved oxygen sensor, a water turbidity sensor and a water pH sensor arranged in the fish pond.

The control unit includes a heater, an aerator and a light controller.

The fish pond detection and control device further includes a camera for detecting the surrounding environment of the fish pond and the water surface of the fish pond, and the camera is connected to the fish pond end processor.

The local monitoring equipment includes a local processor, an information input device for setting environmental parameters or fish farming parameters, and a display for displaying environmental parameters or fish farming parameters, and the information input device and the display are connected to the local processing The local processor is connected to the fish pond detection and control equipment through the communication module.

The monitoring terminal includes a handheld mobile terminal and a fixed terminal.

The handheld mobile terminals include mobile phones and tablet computers.

The fixed terminal includes a computer.

The communication module includes one or more combinations of routers, WIFI hotspots, ZigBee coordinators and wireless communication base stations.

Compared with the prior art, the utility model has the following advantages:

(1) This utility model proposes an intelligent fish farming monitoring system based on cloud architecture. The fish pond detection and control equipment of this system realizes real-time detection and control of fish pond parameters, and the local monitoring equipment can realize real-time monitoring of fish ponds at the remote end. Monitoring, at the same time, the cloud processing server can realize big data processing and provide corresponding control measures to the fish pond detection and control equipment through the local monitoring equipment, so as to remotely control the fish pond and improve the intelligent adjustment of fish farming parameters in the fish pond. At the same time, the monitoring terminal can It is convenient for fish farmers to monitor the situation of fish ponds in real time, and at the same time, the calculation of machine learning algorithms with a large amount of calculation is run on the cloud processing server, which is conducive to improving the efficiency of data processing and operation;

(2) The utility model can upload the growth condition of the fish and the sensor parameters to the cloud processing server, and generate an expert database system through machine learning and big data processing operations, and then the expert database can establish a more comprehensive and effective aquaculture early warning model, It can not only guide users to raise fish online, but also provide samples to the cloud processing server to use machine learning to train and optimize the early warning model, thereby improving the intelligence of the fish farming monitoring system;

(3) The utility model is provided with a camera for detecting the surrounding environment of the fish pond and the water surface condition of the fish pond, so that farmers can directly observe the environment of the fish pond at the far end, which is convenient and reliable.

Description of drawings

Fig. 1 is the structural block diagram of the intelligent fish farming monitoring system based on the cloud architecture of the present invention.

In the figure, 1 is a fish pond detection and control device, 2 is a local monitoring device, 3 is a cloud processing server, 101 is a fish pond end processor, 102 is a water temperature sensor, 103 is a dissolved oxygen sensor, 104 is a water turbidity sensor, 105 is a water pH sensor, 106 is a camera, 107 is a heater, 108 is an aerator, 109 is a light controller, 110 is a fish pond terminal communication module, 201 is a local processor, 202 is an information input device, and 203 is a display , 204 is a local terminal communication module, 401 is a hand-held mobile terminal, and 402 is a fixed terminal.

Detailed ways

The utility model will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

Example

As shown in Figure 1, an intelligent fish farming monitoring system based on cloud architecture, the system includes fish pond detection and control equipment 1, local monitoring equipment 2, cloud processing server 3 and monitoring terminal, fish pond detection and control equipment 1 and local monitoring The device 2 is connected by communication, the local monitoring device 2 is connected to the cloud processing server 3 through the Internet network, and multiple monitoring terminals are set up and connected to the cloud processing server 3 respectively.

The fish pond detection control device 1 includes a fish pond end processor 101 and a sensor detection unit and a control unit respectively connected thereto. The fish pond end processor 101 is connected to the local monitoring device 2 through the fish pond end communication module 110 . The sensor detection unit includes a water temperature sensor 102 , a dissolved oxygen sensor 103 , a water turbidity sensor 104 and a water pH sensor 105 arranged in the fish pond. The control unit includes a heater 107 , an aerator 108 and a light controller 109 . The fish pond detection and control device 1 also includes a camera 106 for detecting the surrounding environment of the fish pond and the water surface of the fish pond, and the camera 106 is connected to the processor 101 at the fish pond end. Wherein, the water temperature sensor 102 is used to detect the water temperature in the fish culture environment, the dissolved oxygen sensor 103 is used to detect the water oxygen content in the fish culture environment, and the water turbidity sensor 104 is used to detect the water turbidity in the fish culture environment, water pH The sensor 105 is used to detect the pH value of water in the fish farming environment, and correspondingly, the heater 107 is used to increase the water temperature in the fish farming environment, the aerator 108 is used to improve the oxygen content of the water in the fish farming environment, and the lighting controller 109 is used for controlling the light irradiation intensity of fish culture environment.

The local monitoring device 2 includes a local processor 201, an information input device 202 for setting environmental parameters or fish farming parameters, and a display 203 for displaying environmental parameters or fish farming parameters, and the information input device 202 and the display 203 are all connected to the local processing unit. The processor 201, the local processor 201 is connected to the fish pond detection and control device 1 through the local terminal communication module 204. Among them, the environmental parameters include temperature parameters required for fish farming, water oxygen content parameters required for fish farming, and light parameters required for fish farming; fish farming parameter settings include fish species parameters, fish growth parameters, feeding types and feeding quantity settings, Among them, the parameter setting of fish species is used to set the species of fish farming, and fish farming is carried out according to the species of fish; the setting of fish growth parameters is used to set the growth cycle of fish farming; the setting of feeding species is used to feed different types of feed according to different habits of fish farming , the feeding quantity setting is used to set the feeding quantity required for fish farming.

The fish pond communication module 110 and the local communication module 204 include one or more combinations of routers, WIFI hotspots, ZigBee coordinators and wireless communication base stations.

Monitoring terminals include handheld mobile terminals 401 and fixed terminals 402 . Handheld mobile terminals 401 include mobile phones and tablet computers. Stationary terminal 402 includes a computer.

The cloud processing server 3 uses machine learning algorithms to model and train the parameters collected by sensors, set fish farming parameters, environmental parameters, and fish growth conditions to generate an expert database system, and then store the expert database through the memory. Through the expert database, a more comprehensive, An effective aquaculture early warning model can not only guide users to raise fish online, but also provide samples to the cloud processing unit to use machine learning to train and optimize the early warning model, so as to better control the operation of each control device in the control unit of the fish pond detection and control device 1, Then fish ponds are intelligently monitored. Running the machine learning algorithm calculation with a large amount of calculation on the cloud processing server 3 is conducive to improving the efficiency of data processing operation and realizing the effective distribution of calculation load based on the cloud architecture.

Claims (10)

1. The monitoring system 1. a kind of intelligence based on cloud framework is breeded fish, it is characterised in that the system includes fish pond detection control device (1), local monitoring device (2), cloud processing server (3) and monitor terminal, described fish pond detection control device (1) and local Monitoring device (2) is communicated to connect, and described local monitoring device (2) is connected with cloud processing server (3) by Internet network Connect, the setting of described monitor terminal is multiple and is respectively connecting to cloud processing server (3).
2. The monitoring system 2. a kind of intelligence based on cloud framework according to claim 1 is breeded fish, it is characterised in that described fish Pool detection control device (1) includes fish pond end processor (101) and the sensor detection unit being attached thereto respectively and control Unit, described fish pond end processor (101) connect local monitoring device (2) by communication module.
3. The monitoring system 3. a kind of intelligence based on cloud framework according to claim 2 is breeded fish, it is characterised in that described biography The water temperature sensor (102), dissolved oxygen sensor (103), water chaotic degree that sensor detection unit includes being arranged in fish pond pass Sensor (104) and water pH sensors (105).
4. The monitoring system 4. a kind of intelligence based on cloud framework according to claim 2 is breeded fish, it is characterised in that described control Unit processed includes heater (107), automatic aerator (108) and lamp dimmer (109).
5. The monitoring system 5. a kind of intelligence based on cloud framework according to claim 2 is breeded fish, it is characterised in that described fish Pool detection control device (1) also includes being used for the camera (106) for detecting fish pond surrounding environment and fish pond situation, described The described fish pond end processor (101) of camera (106) connection.
6. The monitoring system 6. a kind of intelligence based on cloud framework according to claim 1 is breeded fish, it is characterised in that described sheet Ground monitoring device (2) includes native processor (201), for the information input device of ambient parameter or parameter setting of breeding fish (202) And it is used for ambient parameter or display (203) that parameter of breeding fish is shown, described information input device (202) and display (203) native processor (201) is connected to, described native processor (201) connects fish pond detection control by communication module Control equipment (1).
7. The monitoring system 7. a kind of intelligence based on cloud framework according to claim 1 is breeded fish, it is characterised in that described prison Control terminal includes hand held mobile terminals (401) and fixed terminal (402).
8. The monitoring system 8. a kind of intelligence based on cloud framework according to claim 7 is breeded fish, it is characterised in that described hand Holding formula mobile terminal (401) includes mobile phone and tablet personal computer.
9. The monitoring system 9. a kind of intelligence based on cloud framework according to claim 7 is breeded fish, it is characterised in that described consolidates Determining terminal (402) includes computer.
10. The monitoring system 10. a kind of intelligence based on cloud framework according to claim 2 or 6 is breeded fish, it is characterised in that described Communication module include one or more combinations in router, WIFI hot spot, ZigBee telegons and radio communication base station.