Large-scale aquaculture monitoring system based on ad hoc network and working method thereof

Abstract

The invention discloses a large-scale aquaculture monitoring system based on an ad hoc network and a working method thereof. The system comprises a sensor in a pond, an acquisition terminal, a power device and a control terminal, various types of intelligent gateways placed on the bank of the pond; the system comprises eight parts including an Internet of Things cloud server, a mobile terminal and a local monitoring center. The requirements of different-scale aquaculture scenes on the monitoring system in the age of Internet of Things can be met, and the intelligent requirement of large-scale aquaculture is effectively improved. Moreover, the monitoring system based on the ad hoc network and the working method can also be extended to the fields of agriculture, building monitoring, marine environment monitoring, smart home and the like, and large-scale intelligent control and monitoring requirements are met. Therefore, the large-scale aquaculture monitoring system based on the ad hoc network and the working method of the large-scale aquaculture monitoring system have wide application prospects.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet of Things, and in particular to a scale aquaculture monitoring system based on ad hoc network and a working method thereof. BACKGROUND

[0002] Mobile communication technology has iterated rapidly from 2G to 5G, driving the explosive growth of Internet of Things technology, and the application fields are continuously expanding, such as environmental monitoring, logistics transportation, smart home, smart city, and smart agriculture. As part of smart agriculture, the intelligent monitoring system of aquaculture has emerged, which can not only accurately perceive and detect the environmental information of the pond, but also control the feeding, oxygenation and other equipment, reduce the participation of personnel, and avoid the problems of food waste and environmental pollution caused by excessive feeding due to insufficient personnel aquaculture experience, and insufficient feeding leading to insufficient feeding of fish.

[0003] In recent years, there have been many patents on various aquaculture monitoring systems, but most of them are mainly focused on the monitoring of a single pond environment or a single aquaculture area, and there are few monitoring systems suitable for scale aquaculture. The invention patent with the application number "201810612981.3" proposes an environmental regulation system and regulation method for scale aquaculture. The invention patent provides an environmental regulation system for three different scale scenarios of 1-3 ponds, 4-7 ponds, and more than 8 ponds, respectively, including wireless acquisition controllers, field monitoring terminals and execution devices; wireless collectors, wireless acquisition controllers, wireless controllers, wireless gateways, wireless repeaters, local monitoring terminals and execution devices; wireless collectors, wireless acquisition controllers, wireless controllers, wireless gateways, wireless repeaters, local monitoring terminals and remote monitoring centers, etc. Three types of devices are composed. The main feature is that for large-scale aquaculture, such as more than 4 ponds, an ad hoc network is formed between the ponds, and then communicates with the wireless gateway on the shore, and after passing through the wireless repeater, base station and other devices, the information is transmitted to the dedicated cloud server platform, and the monitoring terminal obtains the relevant information through the dedicated cloud server platform. This monitoring system has many devices in the network, which is relatively complex, may cause unstable or lost data information transmission, and has high cost, which is not conducive to large-scale promotion in scale aquaculture. SUMMARY

[0004] In order to overcome the shortcomings of various existing aquaculture monitoring systems, the present application proposes a scale aquaculture monitoring system based on ad hoc network and a working method thereof. The technical problem of low intelligence of the monitoring system in the prior art for scale aquaculture is solved.

[0005] To achieve the above purpose, the present application is implemented by the following technical scheme: a scale aquaculture monitoring system based on ad hoc network, comprising: Sensors are used to acquire various environmental parameters in a pond. These sensors include temperature sensors, humidity sensors, dissolved oxygen sensors, pH sensors, chlorophyll sensors, and ammonia nitrogen sensors. The data acquisition terminal connects to the sensor via a data interface and communicates with the main smart gateway via an ad hoc network to transmit the parameter data detected by the sensor to the main smart gateway. The main smart gateway also communicates with the cameras, enabling the video information from the cameras to be collected into the smart gateway. The main smart gateway summarizes the environmental parameter information of each pond and the video information acquired by the cameras, and connects to the IoT cloud server through WiFi or 4G / 5G network, thereby summarizing the acquired environmental parameter information and video information to the IoT cloud server. IoT cloud servers are used to store environmental parameter information and video information; The mobile terminal is wirelessly connected to the IoT cloud server, enabling the mobile terminal to communicate with the smart gateway through the IoT cloud server to extract environmental parameter information and video information. Then, based on the extracted information, it issues control commands to the main smart gateway. The control terminal communicates with the main intelligent gateway via an ad-hoc network and is used to control the operation of the power unit. The power unit, located in the pond, is used to execute control commands issued by the control terminal; Local monitoring center; connected to the smart gateway via data cable, used to monitor the operating status of each device.

[0006] Furthermore, this system also includes several slave smart gateways; when there are a large number of ponds, several slave smart gateways are added, with one slave smart gateway corresponding to multiple ponds. Each group of ponds communicates with its slave smart gateway through a self-organizing network, and each slave smart gateway communicates with the main smart gateway through a self-organizing network.

[0007] Furthermore, the acquisition terminal includes a data interface, an MCU microcontroller unit, a self-organizing network module, and an antenna. The MCU microcontroller unit is connected and communicates with the data interface and the self-organizing network module, and the self-organizing network module is connected with the antenna 7.

[0008] Furthermore, the control terminal includes a relay interface, an MCU microcontroller self-organizing network module, and an antenna. The MCU microcontroller is connected and communicates with the relay interface and the self-organizing network module. The self-organizing network module is connected with the antenna 7, and the relay interface is connected with the power unit.

[0009] Furthermore, the smart gateway includes an antenna, a self-organizing network module, an ARM microprocessor, a display screen, a WiFi module, and a 4G / 5G module, with the ARM microprocessor connected to the antenna, the self-organizing network module, the display screen, the WiFi module, and the 4G / 5G module.

[0010] To implement the working method of this self-organizing network-based large-scale aquaculture monitoring system, the method specifically includes the following steps: Step 1: Sensors in the pond acquire various environmental parameters and transmit them to the data acquisition terminal via a data interface according to the agreed protocol. Step 2: In step 1, the data entering the acquisition terminal through the data interface enters the MCU microcontroller unit. According to the corresponding sensor protocol, it parses and obtains the information of each type of sensor. Then, according to the data packet pass-through requirements of the self-organizing network module, it packages the information of each type of sensor into a data packet that meets the requirements and transmits it to the self-organizing network module. Step 3: The data packets transmitted to the self-organizing network module in step 2 are wirelessly transmitted to the antenna in the main smart gateway via the self-organizing network module's adaptively set operating frequency and its connected antenna. After being wirelessly received, they enter the self-organizing network module in the main smart gateway. Step 4: In step 3, the wireless signal entering the self-organizing network module of the main smart gateway is recovered by the self-organizing network module and the transparent data packet is sent to the ARM microprocessor. The ARM microprocessor parses the data packet, decomposes it into various environmental parameter information that is the same as in step 1, and then packages the data according to the IoT MQTT protocol. Step 5: In this process, data packets conforming to the MQTT protocol are transmitted by the ARM microprocessor to the WiFi module and the 4G / 5G module respectively according to different data interfaces. The video stream information captured by the camera placed near the main smart gateway is also transmitted to the WiFi module. Step 6: In step 5, the video stream information transmitted to the WiFi module is transmitted to the IoT cloud server via the WiFi wireless network and the antenna in the main smart gateway, according to the RTSP protocol. Simultaneously, the data packets transmitted to the WiFi module and the 4G / 5G module in step 4, conforming to the MQTT protocol, are transmitted to the IoT cloud server via the WiFi wireless network and the 4G / 5G wireless network, respectively, and the antenna in the main smart gateway. Step 7: In step 6, the data packet information and video stream information transmitted to the IoT cloud server are connected to the mobile terminal via WiFi or 4G / 5G network. The mobile terminal extracts various environmental parameter information corresponding to step 1 and video stream information collected by the camera corresponding to step 5 according to the MQTT and RTSP protocols mentioned in step 6, thereby realizing remote monitoring of the information of each pond in step 1. In addition, the local monitoring center can also access the ARM microprocessor in the main smart gateway via wired connection to extract the same information as the mobile terminal. Step 8: In step 7, after the mobile terminal or local monitoring center obtains the environmental parameter information of each pond, it issues control commands according to the pond management needs. The control commands issued by the mobile terminal according to the MQTT protocol are transmitted through the IoT cloud server to the WiFi module and the 4G / 5G module respectively, and then enter the ARM microprocessor in the main smart gateway. Alternatively, the local monitoring center can also send control commands to the ARM microprocessor in the main smart gateway via a wired connection, just like the mobile terminal. Step 9: In step 8, the control instruction information of the ARM microprocessor is transmitted to the antennas and self-organizing network modules of each pond control terminal through the self-organizing network module and antenna, and then transmitted to the relay interface through the data interface with the MCU microcontroller unit; Step 10: The control command information transmitted to the relay interface in step 9 is then transmitted to the power unit for management operations.

[0011] Furthermore, the method for adaptively setting the operating frequency in step 3 is as follows: S1. Determine whether the first working frequency adaptive setting has ended; S2. If the first working frequency adaptive setting has ended, the self-organizing network module in the main intelligent gateway sets the current working frequency to 430MHz. The self-organizing network module receives the signal of setting the working frequency in the field environment and detects the power value. If the current power value is less than -100dBm, set the working frequency of the self-organizing network module in the main smart gateway to the current set frequency, and then set the working frequency of the self-organizing network module in the acquisition terminal and control terminal to the current set frequency; If the current power value is greater than -100dBm, the current operating frequency is increased by 0.2MHz. If the current operating frequency after the frequency increase is less than or equal to 435MHz, the process ends. If the current operating frequency after the frequency increase is greater than 435MHz, the self-organizing network module will re-receive the signal set at the operating frequency in the field environment and re-detect the power value. Furthermore, if the first adaptive setting of the operating frequency in S1 has not ended, the self-organizing network module in the main intelligent gateway sets the current operating frequency to 470MHz. The self-organizing network module receives the signal of the set operating frequency in the field environment and detects the power value. If the current power value is less than -100dBm, the operating frequency of the self-organizing network module in the main intelligent gateway is set to the currently set frequency, and then the operating frequency of the self-organizing network module in the acquisition terminal and control terminal is set to the currently set frequency. If the current power value is greater than -100dBm, the current operating frequency is increased by 0.2MHz. If the current operating frequency is greater than 510MHz after the frequency increase, the first operating frequency adaptive setting ends and the second operating frequency setting begins. If the current operating frequency is less than or equal to 510MHz after the frequency increase, the self-organizing network module will re-receive the signal of the operating frequency set in the field environment and re-detect the power value. Beneficial effects

[0012] This invention provides a large-scale aquaculture monitoring system based on a self-organizing network and its operating method. Compared with the prior art, it has the following advantages: This invention provides a large-scale aquaculture monitoring system and its operating method based on ad hoc networks. It can meet the monitoring system requirements of different scale aquaculture scenarios in the Internet of Things era, effectively improving the intelligent needs of large-scale aquaculture. Furthermore, the ad hoc network-based monitoring system and its operating method can be extended to agriculture, building monitoring, marine environmental monitoring, smart homes, and other fields to achieve large-scale intelligent control and monitoring needs. Therefore, the large-scale aquaculture monitoring system and its operating method proposed in this invention have broad application prospects. Attached Figure Description

[0013] Figure 1 This is a schematic diagram of the system of the present invention; Figure 2 This is a monitoring network diagram of the system of the present invention; Figure 3 This is a logic diagram of the working method of the system of the present invention; Figure 4 This is a logic block diagram showing how the self-organizing network module of the present invention adaptively sets its operating frequency.

[0014] The reference numerals in the accompanying drawings include: 1. Sensor, 2. Data interface, 3. MCU microcontroller unit, 4. Self-organizing network module, 5. Relay interface, 6. Power unit, 7. Antenna, 8. Display screen, 9. ARM microprocessor, 10. Camera, 11. WiFi module, 12. 4G / 5G module, 13. Local monitoring center, 14. IoT cloud server, 15. Mobile terminal, 16. Pond, 21. Data acquisition terminal, 22. Control terminal, 31. Main smart gateway, 32. Slave smart gateway. Detailed Implementation

[0015] 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.

[0016] Please see Figure 1 and Figure 2 This application provides a large-scale aquaculture monitoring system based on a self-organizing network, comprising: Sensor 1 is used to acquire various environmental parameters in pond 16. Sensor 1 includes temperature detection sensor 1, humidity detection sensor 1, dissolved oxygen detection sensor 1, pH value detection sensor 1, chlorophyll detection sensor 1, and ammonia nitrogen detection sensor 1. The data acquisition terminal 21 is connected to the sensor 1 via the data interface 2. The data acquisition terminal 21 communicates with the main intelligent gateway 31 via an ad hoc network and is used to transmit the parameter data detected by the sensor 1 to the main intelligent gateway 31. The main smart gateway 31 also communicates with the camera 10, so that the video information of the camera 10 is collected into the smart gateway. The main smart gateway 31 summarizes the environmental parameter information of each pond 16 and the video information obtained by the camera 10, and connects to the IoT cloud server 14 through WiFi or 4G / 5G network, and then summarizes the acquired environmental parameter information and video information to the IoT cloud server 14. IoT cloud server 14 is used to store environmental parameter information and video information; Mobile terminal 15 is wirelessly connected to IoT cloud server 14, enabling mobile terminal 15 to communicate with smart gateway through IoT cloud server 14 to extract environmental parameter information and video information, and then issue control commands to main smart gateway 31 based on the extracted information. The control terminal 22 communicates with the main intelligent gateway 31 via an ad-hoc network and is used to control the operation of the power unit 6. The power unit 6 is installed in the pond 16 and is used to execute control commands issued by the control terminal 22; Local monitoring center 13; connected to the smart gateway via a data cable, used to monitor the operating status of each device.

[0017] The system also includes several slave smart gateways 32; when there are a large number of ponds 16, several slave smart gateways 32 are added. One slave smart gateway 32 corresponds to multiple ponds 16. Each group of ponds 16 communicates with its slave smart gateway 32 through a self-organizing network. Each slave smart gateway 32 communicates with the main smart gateway 31 through a self-organizing network.

[0018] The sensor 1 and the data acquisition terminal 21 are connected by a wired connection, the power unit 6 and the control terminal 22 are connected by a wired connection, and the data acquisition terminal 21, the control terminal 22 and the smart gateway are connected by a self-organizing network. The self-organizing network operating frequency can adapt to the monitoring frequency and frequency hopping according to the field environment to reduce interference. A single smart gateway has the ability to manage scale and can simultaneously support the connection of no less than 50 data acquisition terminals 21 and control terminals 22 based on a self-organizing network; The smart gateway can be set as a main smart gateway 31 or a slave smart gateway 32 via the software on the display screen 8. Information from multiple slave smart gateways 32 can be managed through the main smart gateway 31. The main smart gateway 31 or slave smart gateway 32 can be wired to various types of cameras 10. The main smart gateway 31 can simultaneously transmit the message information from the camera 10 and from the acquisition terminal 21 and the control terminal 22 to the IoT cloud server 14. The mobile terminal 15 can remotely obtain information from the main smart gateway 31 from the IoT cloud server 14 via a 4G / 5G network or a WiFi network. The local monitoring center 13 obtains information from the main smart gateway 31 via a wired Ethernet network.

[0019] The data acquisition terminal 21 includes a data interface 2, an MCU microcontroller unit 3 (microcontroller unit, also known as a single-chip microcomputer), a self-organizing network module 4, and an antenna 7. The MCU microcontroller unit 3 is connected and communicates with the data interface 2 and the self-organizing network module 4, and the self-organizing network module 4 is connected with the antenna 77.

[0020] The control terminal 22 includes a relay interface 5, an MCU microcontroller unit 3, a self-organizing network module 4, and an antenna 7. The MCU microcontroller unit 3 is connected to the relay interface 5 and the self-organizing network module 4 for communication. The self-organizing network module 4 is connected to the antenna 77. The relay interface 5 is connected to the power unit 6.

[0021] The smart gateway includes an antenna 7, a self-organizing network module 4, an ARM microprocessor 9 (processor), a display screen 8, a WiFi module 11, and a 4G / 5G module 12. The ARM microprocessor 9 is connected to the antenna 7, the self-organizing network module 4, the display screen 8, the WiFi module 11, and the 4G / 5G module 12.

[0022] For small-scale scenarios, such as when the number of ponds 16 is less than 50, only one main smart gateway 31 is needed. Sensors 1, placed in each pond 16, detect various environmental parameters and transmit them to the data acquisition terminal 21. Then, through ad-hoc network communication, the environmental parameter information of each pond 16 is transmitted to the main smart gateway 31. Simultaneously, video information acquired by cameras 10 is also transmitted to the main smart gateway 31. After the environmental parameter information and video information are aggregated, they are connected to the IoT cloud server 14 via WiFi or 4G / 5G network. Mobile terminals 15 wirelessly connect to the IoT cloud server 14, extract the environmental parameter information and video information, and then, based on the extracted information, issue control commands to the main smart gateway 31. These commands are then transmitted to the control terminal 22 in each pond 16 via ad-hoc network communication, thereby controlling the power unit 6. Similarly, the local monitoring center 1313 can also be directly connected to the main smart gateway 31 via a wired connection, achieving the same function as the mobile terminal 15. For large-scale scenarios, such as when the number of ponds 16 exceeds 50, the smart gateways can be configured as a master smart gateway 31 and slave smart gateways 32. Each group of ponds 16 communicates with its respective slave smart gateway 32 via a self-organizing network to transmit parameter information and control commands. Each slave smart gateway 32 communicates with the master smart gateway 31 via a self-organizing network to transmit video information, other parameter information, and control commands. The local monitoring center 13 is connected to the master smart gateway 31 via a wired connection, and the mobile terminal 15 is connected to the master smart gateway 31 via an IoT cloud server 14 to achieve various information transmissions. Through this networking architecture, a monitoring system for large-scale aquaculture scenarios is formed.

[0023] See Figure 3 and Figure 4 This application provides a working method for a large-scale aquaculture monitoring system based on ad hoc networks. Step 1: Sensor 1 in pond 16 acquires various environmental parameter information in pond 16 and enters the data acquisition terminal 21 through data interface 2 according to the agreed protocol.

[0024] In practical implementation, sensor 1 includes multiple sets of sensors of different types, such as temperature sensor 1, humidity sensor 1, dissolved oxygen sensor 1, pH sensor 1, chlorophyll sensor 1, ammonia nitrogen sensor 1, etc. Data interface 2 is RS485 or RS232, or high / low level data, or analog voltage data, etc.

[0025] Step 2: In step 1, the data entering the acquisition terminal 21 through the data interface 2 enters the MCU microcontroller unit 3. According to the agreed protocol of the corresponding sensor 1, the information of each type of sensor 1 is parsed and obtained. Then, according to the data packet pass-through requirements of the self-organizing network module 4, the information of each type of sensor 1 is packaged into a data packet that meets the requirements and transmitted to the self-organizing network module 4.

[0026] In practice, the MCU microcontroller unit 3 is a low-cost single-chip microcomputer such as the STM32 series, the sensor 1 uses the Modbus or other proprietary protocols, and the self-organizing network module 4 is a wireless transceiver module that operates at a specific frequency and uses FSK modulation, or it can be other wireless transceiver modules such as Lora or Zigbee.

[0027] Step 3: The data packets transmitted to the self-organizing network module 4 in step 2 are transmitted wirelessly to the antenna 7 connected to it via the adaptively set operating frequency of the self-organizing network module 4. After being wirelessly received, they enter the self-organizing network module 4 in the main intelligent gateway 31.

[0028] In practical implementation, antenna 7 can be an omnidirectional adhesive rod antenna 7, a PCB patch antenna 7, or other types of omnidirectional antenna 7. The self-organizing network module 4 adaptively sets its operating frequency range to 430MHz–435MHz and 470MHz–510MHz. The specific setting method is as follows. S1. Determine whether the first working frequency adaptive setting has ended; S2. If the first working frequency adaptive setting has ended, the self-organizing network module 4 in the main intelligent gateway 31 sets the current working frequency to 430MHz. The self-organizing network module 4 receives the signal of setting the working frequency in the field environment and detects the power value. If the current power value is less than -100dBm, set the working frequency of the self-organizing network module 4 in the main intelligent gateway 31 to the current set frequency, and then set the working frequency of the self-organizing network module 4 in the acquisition terminal 21 and the control terminal 22 to the current set frequency. If the current power value is greater than -100dBm, the current operating frequency is increased by 0.2MHz. If the current operating frequency is less than or equal to 435MHz after the frequency is increased, the process ends. If the current operating frequency is greater than 435MHz after the frequency is increased, the self-organizing network module 4 will receive the signal set at the operating frequency in the field environment again and re-detect the power value.

[0029] If the first adaptive setting of the working frequency in S1 has not ended, the self-organizing network module 4 in the main intelligent gateway 31 sets the current working frequency to 470MHz. The self-organizing network module 4 receives the signal of the set working frequency in the field environment and detects the power value. If the current power value is less than -100dBm, the working frequency of the self-organizing network module 4 in the main intelligent gateway 31 is set to the currently set frequency. Subsequently, the working frequencies of the self-organizing network module 4 in the acquisition terminal 21 and the control terminal 22 are set to the currently set frequency. If the current power value is greater than -100dBm, the current operating frequency is increased by 0.2MHz. If the current operating frequency is greater than 510MHz after the frequency is increased, the first operating frequency adaptive setting ends and the second operating frequency setting begins. If the current operating frequency is less than or equal to 510MHz after the frequency is increased, the self-organizing network module 4 will receive the signal of the operating frequency set in the field environment again and re-detect the power value.

[0030] Step 4: In step 3, the wireless signal entering the self-organizing network module 4 of the main smart gateway 31 is restored by the self-organizing network module 4 to transmit the data packet. The data packet enters the ARM microprocessor 9. After parsing the data packet, the ARM microprocessor 9 decomposes it into various environmental parameter information that is the same as in step 1, and then packages the data according to the IoT MQTT protocol.

[0031] In practice, the ARM microprocessor 9 can be a higher-performance microcontroller chip, such as the F4xx in the STM32 series, or it can be a DSP or GPU, etc.

[0032] Step 5: In step 4, data packets conforming to the MQTT protocol are transmitted by the ARM microprocessor 99 to the WiFi module 11 and the 4G / 5G module 12 respectively via different data interfaces 2. The camera 10, placed near the main smart gateway 31, also transmits the captured video stream information to the WiFi module 11.

[0033] In practice, the WiFi module 11 can be a dedicated module such as Espressif's ESP series, or it can be a WiFi module 11 from other companies. The 4G / 5G module 12 is a 4G / 5G modem module, such as Quectel's product series. The camera 10 is a conventional high-definition surveillance camera 10.

[0034] Step 6: In step 5, the video stream information transmitted to the WiFi module 11 is transmitted to the IoT cloud server 14 via the WiFi wireless network and antenna 7 in the main smart gateway 31, according to the RTSP protocol. Simultaneously, the data packets compliant with the MQTT protocol transmitted to the WiFi module 11 and the 4G / 5G module 12 in step 4 are transmitted to the IoT cloud server 14 via the WiFi wireless network and the 4G / 5G wireless network, respectively, and antenna 77 in the main smart gateway 31.

[0035] In practice, the IoT cloud server 14 is an MQTT and RTSP server deployed on Tencent Cloud, or it can be a cloud server deployed by other companies, such as Alibaba Cloud or Huawei Cloud.

[0036] Step 7: In step 6, the data packet information and video stream information transmitted to the IoT cloud server 14 are connected to the mobile terminal 15 via WiFi or 4G / 5G network. The mobile terminal 15 extracts various environmental parameter information corresponding to step 1 and video stream information collected by the camera 10 corresponding to step 5 according to the MQTT and RTSP protocols mentioned in step 6, thereby realizing remote monitoring of the information of each pond 16 in step 1. In addition, the local monitoring center 13 can also access the ARM microprocessor 9 in the main smart gateway 31 via wired connection to extract the same information as the mobile terminal 15.

[0037] In practice, mobile terminal 15 can be a mobile phone, or other mobile terminal 15, etc. Local monitoring center 13 is a regular desktop computer, and the wired connection commonly uses an Ethernet network with an RJ45 interface, but other connections such as USB can also be used.

[0038] Step 8: In step 7, after the mobile terminal 15 or the local monitoring center 13 obtains the environmental parameter information of each pond 16, it issues control commands according to the management needs of the pond 16. The control commands issued by the mobile terminal 15, according to the MQTT protocol, are transmitted via the IoT cloud server 14 through WiFi and 4G / 5G networks to the WiFi module 11 and 4G / 5G module 12 respectively, and then enter the ARM microprocessor 99 in the main smart gateway 31. Alternatively, the local monitoring center 13 can also send control commands to the ARM microprocessor 9 in the main smart gateway 31 via a wired connection, similar to the mobile terminal 15.

[0039] In practice, the management of pond 16 refers to oxygenation, water exchange, feeding, etc., while the control commands refer to the switches or relays of the corresponding power devices 6.

[0040] Step 9: In step 8, the control instruction information of the ARM microprocessor 9 is transmitted to the antenna 7 and self-organizing network module 4 of each pond 16 control terminal 22 through the self-organizing network module 4 and antenna 7, and then transmitted to the relay interface 5 through the data interface 2 of the MCU microcontroller unit 3.

[0041] In practice, relay interface 5 can be an RS485 interface, a voltage control interface, etc.

[0042] Step 10: In step 9, the control command information transmitted to the relay interface 5 is transmitted to the power unit 6 for management operations.

[0043] In practice, the power unit 6 is an aerator, water pump, or feeder, etc., and the management and operation include the instant switching, timed switching, and speed control of each motor of the power unit 6.

[0044] Through steps 1 to 10, the entire workflow of the small-scale aquaculture monitoring system was realized.

[0045] Furthermore, any content not described in detail in this specification is existing technology known to those skilled in the art.

[0046] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A self-organizing network based scale aquaculture monitoring system, characterized in that, Comprise: Sensor for obtaining various environmental parameters in the pond, the sensor includes temperature detection sensor, humidity detection sensor, dissolved oxygen detection sensor, PH value detection sensor, chlorophyll detection sensor, ammonia nitrogen detection sensor; Collecting terminal, connected with the sensor through the data interface, the collecting terminal is communicated with the main intelligent gateway through the ad hoc network, used for transmitting the parameter data detected by the sensor to the main intelligent gateway; The main intelligent gateway also communicates with the camera, so that the video information of the camera is collected into the intelligent gateway, the main intelligent gateway collects the environmental parameter information of each pond and the video information obtained by the camera, and is connected with the Internet of Things cloud server through WiFi or 4G / 5G network, and then the obtained environmental parameter information and video information are summarized to the Internet of Things cloud server; The Internet of Things cloud server is used for storing environmental parameter information and video information; Mobile terminal, wirelessly connected with the Internet of Things cloud server, so that the mobile terminal communicates with the intelligent gateway through the Internet of Things cloud server, used for extracting environmental parameter information and video information, and then according to the extracted information, control instructions are issued to the main intelligent gateway; Control terminal, ad hoc network communication with the main intelligent gateway, used for controlling the work of the power device; Power device, arranged in the pond, used for executing the control instruction issued by the control terminal; Local monitoring center; connected with the intelligent gateway through the data line, used for monitoring the running state of each device.

2. The self-organizing network based large-scale aquaculture monitoring system according to claim 1, wherein, Still include several from intelligent gateway; when the number of ponds is large, several from intelligent gateways are added, one from intelligent gateway corresponds to multiple ponds, each group of ponds communicates with its belonging from intelligent gateway through ad hoc network, and each from intelligent gateway communicates with the main intelligent gateway through ad hoc network.

3. The self-organizing network based large-scale aquaculture monitoring system according to claim 1, wherein, The collecting terminal includes a data interface, an MCU micro control unit, an ad hoc network module and an antenna, the MCU micro control unit is connected with the data interface and the ad hoc network module in communication, and the ad hoc network module is connected with the antenna 7.

4. The self-organizing network based large-scale aquaculture monitoring system according to claim 1, wherein, The control terminal includes a relay interface, an MCU micro control unit, an ad hoc network module and an antenna, the MCU micro control unit is connected with the relay interface and the ad hoc network module in communication, the ad hoc network module is connected with the antenna 7, and the relay interface is connected with the power device.

5. The self-organizing network based large-scale aquaculture monitoring system according to claim 1, wherein, The intelligent gateway includes an antenna, an ad hoc network module, an ARM microprocessor, a display screen, a WiFi module and a 4G / 5G module, and the ARM microprocessor is connected with the antenna, the ad hoc network module, the display screen, the WiFi module and the 4G / 5G module.

6. A method of operating a self-organizing network based scale aquaculture monitoring system according to any one of claims 1-5, characterized in that, The method specifically includes the following steps: Step 1: The sensor in the pond obtains various environmental parameter information in the pond, enters the collecting terminal through the data interface according to the agreed protocol; Step 2: The data entering the collecting terminal through the data interface in step 1 enters the MCU micro control unit, the sensor information of each type is obtained by analyzing according to the corresponding sensor agreed protocol, then the sensor information of each type is packaged according to the transmission requirement of the data packet of the ad hoc network module, becomes a data packet meeting the requirement, and is transmitted to the ad hoc network module; Step 3: The data packet transmitted to the ad hoc network module in step 2 is transmitted wirelessly by the antenna connected to the ad hoc network module at the adaptive set working frequency to the antenna in the main intelligent gateway, and enters the ad hoc network module in the main intelligent gateway after wireless reception; Step 4: The wireless signal entering the ad hoc network module in the main intelligent gateway in step 3 is recovered into the transparent data packet by the ad hoc network module, the data packet enters the ARM microprocessor, and the ARM microprocessor decomposes the same types of environmental parameter information as in step 1 after analyzing the data packet, and then packs the data according to the Internet of Things MQTT protocol; Step 5: The data packet in step 5 that meets the MQTT protocol is transmitted to the WiFi module and the 4G / 5G module by the ARM microprocessor according to different data interfaces, and the video stream information collected by the camera placed near the main intelligent gateway is also transmitted to the WiFi module; Step 6: The video stream information transmitted to the WiFi module in step 5 is transmitted to the Internet of Things cloud server by the antenna in the main intelligent gateway according to the RTSP protocol through the WiFi wireless network; at the same time, the data packet in step 4 that meets the MQTT protocol is transmitted to the Internet of Things cloud server by the antenna in the main intelligent gateway through the WiFi wireless network and the 4G / 5G wireless network respectively; Step 7: The data packet information and the video stream information transmitted to the Internet of Things cloud server in step 6 are connected to the mobile terminal through the WiFi or 4G / 5G network, and the mobile terminal extracts the types of environmental parameter information corresponding to step 1 and the video stream information collected by the camera corresponding to step 5 according to the MQTT protocol and the RTSP protocol mentioned in step 6, so as to realize the remote monitoring of the water pond information in step 1. In addition, the local monitoring center can also access the ARM microprocessor in the main intelligent gateway through a wired way to extract the same types of information as the mobile terminal; Step 8: After the mobile terminal or the local monitoring center obtains the water pond environmental parameter information in step 7, according to the water pond management needs, the mobile terminal transmits the control command to the WiFi module and the 4G / 5G module through the Internet of Things cloud server according to the MQTT protocol through the WiFi and 4G / 5G networks respectively, and then enters the ARM microprocessor in the main intelligent gateway; in addition, the local monitoring center can also send the control command to the ARM microprocessor in the main intelligent gateway through a wired way like the mobile terminal; Step 9: The control command information entering the ARM microprocessor in step 8 is transmitted to the antenna and the ad hoc network module of the water pond control terminal through the ad hoc network module and the antenna, and is transmitted to the relay interface through the MCU micro control unit data interface; Step 10: The control command information transmitted to the relay interface in step 9 is transmitted to the power device to manage and operate the power device.

7. The method of operating a self organizing network based scale aquaculture monitoring system according to claim 6, wherein, The method for adaptively setting the working frequency in step 3 is as follows: S1. Determine whether the first working frequency adaptive setting is finished; S2. If the first adaptive setting of working frequency has ended, the ad hoc module in the main intelligent gateway sets the current working frequency to 430MHz, the ad hoc module receives the signal of setting working frequency in the field environment and detects the power value; If the current power value is less than -100dBm, the ad hoc module in the main intelligent gateway is set to work at the current setting frequency, and then the ad hoc modules in the collection terminal and the control terminal are set to work at the current setting frequency; If the current power value is greater than -100dBm, the current working frequency is increased by 0.2MHz, and if the current working frequency is less than or equal to 435MHz after the increase, the process ends; if the current working frequency is greater than 435MHz after the increase, the ad hoc module receives the signal of setting working frequency in the field environment again and detects the power value.

8. The method of operating a self organizing network based, large scale, aquaculture monitoring system according to claim 6, wherein, If the first adaptive setting of working frequency has not ended in S1, the ad hoc module in the main intelligent gateway sets the current working frequency to 470MHz, the ad hoc module receives the signal of setting working frequency in the field environment and detects the power value; if the current power value is less than -100dBm, the ad hoc module in the main intelligent gateway is set to work at the current setting frequency, and then the ad hoc modules in the collection terminal and the control terminal are set to work at the current setting frequency; If the current power value is greater than -100dBm, the current working frequency is increased by 0.2MHz, and if the current working frequency is greater than 510MHz after the increase, the first adaptive setting of working frequency ends and the second working frequency setting is entered; if the current working frequency is less than or equal to 510MHz after the increase, the ad hoc module receives the signal of setting working frequency in the field environment again and detects the power value.

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