An intelligent livestock electronic feeding system based on the Internet of Things and its working method

Abstract

The present invention provides an intelligent livestock electronic feeding system based on the Internet of Things and its working method. The cloud server platform is respectively connected to a third-party database, an operation terminal and an Internet of Things intelligent gateway. The Internet of Things electronic ear tag recognition terminal is connected to the cloud server. The Internet of Things intelligent gateway is connected to the electronic feeder host. The electronic feeder host is connected to the electronic feeder slave. The Internet of Things electronic ear tag recognition terminal is connected to the electronic ear tag. By binding the individual identity information of livestock with the IDs of the electronic feeder hosts and slaves in the farm, and using the cloud server platform, the Internet of Things intelligent gateway, the electronic feeder host and the corresponding electronic feeder slaves, the feeding plan is stored in the cloud server platform and the feeding plan is sent to each electronic feeder host, realizing intelligent feeding control. And the feeding parameters collected later are combined with artificial intelligence algorithms to update the feeding plan in a timely manner.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent breeding, and particularly relates to an intelligent livestock electronic feeding system based on the Internet of Things and its working method. Background Art

[0002] As an important part of the national economy, pig breeding occupies a dominant position in domestic livestock breeding. In pig breeding, breeding sows have extremely high economic added value. The feeding management level during the gestation stage of sows will have a great impact on lactating sows, newborn piglets, weaned piglets, and the continuous production capacity of sows; overfeeding in the early stage of sow pregnancy will affect the development of the sow's mammary glands, which is also an important reason for the decrease in sow milk production and the small weaning weight of piglets; inaccurate feeding of pregnant sows in the later stage results in relatively small birth weights of piglets.

[0003] The key to feeding management during the breeding stage is "strictly limiting feeding during gestation and allowing full intake during lactation". The purpose of strictly limiting feeding of pregnant sows is also to increase the feed intake of lactating sows, so that the total daily nutritional intake of lactating sows reaches the basic requirements for milk production; sows are kept in gestation stalls during both the gestation and lactation stages. Each stall in the gestation stall has only one feeding trough and a feeding trough, and the feeding amount of each sow may vary.

[0004] In existing large-scale farms (sheds), during the feeding process of sows, the identity of each sow individual is identified through an electronic ear tag. Each sow individual is information-bound to the farm (shed) and the stall through the electronic ear tag. In most existing large-scale pig farms (sheds), at the set feeding time, the sow feed is conveyed into the feeding trough (cup) through the feed line and water line. The scale band and food volume regulator of the trough (cup) can be manually adjusted by the breeder for each stall (each sow in the gestation stall) to adjust the feeding amount; during the period when a single sow is in the stall, the feeding amount is different at different feeding time points within a day; during the entire feeding cycle of a single sow in the stall, the feeding amount changes with the date; there are differences among individual sows, and the feeding amount should be different at different feeding time points within a day; during the entire feeding cycle of each sow in the stall, with the change of date, the feeding amount that should be fed to each sow is also different.

[0005] However, most breeders determine the feeding amount based on traditional breeding experience, lacking scientific feeding data and unable to optimally control: 1. The feeding amount of each sow at different feeding time points during single-day feeding; 2. The daily feeding amount of each sow throughout the entire feeding cycle in the pen. Moreover, it is very difficult for breeders to accurately collect and count the feeding amount and actual food intake of each sow. Due to the difference between the actual food intake and feeding amount of pigs, the feed that has entered the feed trough may not be eaten by the pigs in time, which may cause the feed to ferment and deteriorate and be eaten by the pigs during the next feeding, affecting the health of the pigs. The health of pigs is extremely vulnerable to external germs.

[0006] A small number of large-scale pig farms (pens) have used electronic pig feeders, most of which are wired connections (such as serial connections or Ethernet connections) and are networked and controlled through repeaters and signal amplifiers. In the specific implementation of this kind of electronic pig feeder in purebred sow farms (with a scale of thousands or tens of thousands of heads), a large number of repeaters and signal amplifiers are required to network all pig feeding devices, resulting in too high usage costs. And during the installation process, a large number of power lines and communication lines are needed. Due to rodent damage or the aging of connection wires during long-term use, dangerous situations such as fires are likely to occur, bringing potential safety hazards to long-term livestock breeding work. Summary of the Invention

[0007] In view of the technical problems involved in the above background art, the present invention proposes an Internet of Things-based intelligent livestock electronic feeding system and its working method, which are used to achieve low-cost customization of the feeding curve for each sow individual throughout the in-pen cycle and realize scientific and precise feeding of each sow in large-scale livestock farms (pens).

[0008] To achieve the above object, the technical solution of the present invention is realized as follows:

[0009] An Internet of Things-based intelligent livestock electronic feeder system includes a cloud server platform, a third-party database, an operation terminal, an Internet of Things intelligent gateway, and an Internet of Things electronic ear tag identification terminal. The cloud server platform is respectively connected to the third-party database, the operation terminal, and the Internet of Things intelligent gateway. The Internet of Things electronic ear tag identification terminal is connected to the cloud server platform or the third-party database or the Internet of Things intelligent gateway. The Internet of Things intelligent gateway is connected to the electronic feeder host, the electronic feeder host is connected to the electronic feeder slave, and the Internet of Things electronic ear tag identification terminal is connected to the electronic ear tag.

[0010] Preferably, both the electronic feeder host and the electronic feeder slave include a control terminal and an execution device, and a human-computer interaction system is provided in the electronic feeder host. The control terminal is connected to the execution device, and the control terminal in the electronic feeder host is respectively connected to the human-computer interaction system, the Internet of Things intelligent gateway, and the control terminal in the electronic feeder slave.

[0011] Preferably, the control terminal includes a microprocessor, a storage unit, a wireless signal transmission unit, a control switch unit, and an analog-to-digital acquisition unit. The microprocessor is respectively connected to the storage unit, the wireless signal transmission unit, the control switch unit, the analog-to-digital acquisition unit, and the human-computer interaction system; the execution device includes a motor, a solenoid valve, a current sensor, a voltage sensor, a level sensor, a water temperature sensor, and a liquid level sensor. The motor and the solenoid valve are both connected to the control switch unit, and the current sensor, the voltage sensor, the level sensor, the water temperature sensor, and the liquid level sensor are all connected to the analog-to-digital acquisition unit.

[0012] A working method of an intelligent livestock electronic feeding system based on the Internet of Things includes the following steps:

[0013] Step 1: First, register each electronic feeder host and electronic feeder slave on the cloud server platform through the human-computer interaction system. Use the electronic ear tag identification terminal to scan the electronic ear tags worn on the ears of each livestock, identify the identity of the livestock through the electronic ear tag identification terminal, and then directly transmit the livestock identity information to the cloud server platform through the electronic ear tag identification terminal or transfer it to the cloud server through a third-party database or an Internet of Things intelligent gateway;

[0014] Step 2: Subsequently, use the operation terminal and the electronic ear tag identification terminal to bind the device IDs of each electronic feeder host and electronic feeder slave that have been registered and managed in the cloud server with the identity IDs of each livestock that have been entered, group the electronic feeder hosts and electronic feeder slaves, and form a control mode in which one electronic feeder host manages several electronic feeder slaves;

[0015] Step 3: The feeding expert formulates a feeding plan according to the biological indicators of each livestock in the positioning pen. Through the operation terminal, bind the biological indicators, the feeding plan, the electronic feeder host device ID, the electronic feeder slave device ID in Step 2, and the identity ID of the livestock in the positioning pen, and input the binding relationship into the cloud server platform;

[0016] Step 4: The cloud server platform maps the feeding plan of each livestock in the positioning pen to the corresponding electronic feeder hosts and electronic feeder slaves according to the binding relationship between the feeding plan and the feeding device ID stored in the cloud server platform in Step 3 and the identity ID of the livestock in the positioning pen, transmits the above mapping content to the Internet of Things intelligent gateway through wireless signals, and stores it in the Internet of Things intelligent gateway;

[0017] Step 5: The Internet of Things intelligent gateway performs wireless networking with each electronic feeder host in the system under the host channel, and distributes the feeding plans of each livestock in the pen corresponding to each electronic feeder host and its corresponding electronic feeder sub-machine, and stores them in the storage unit of each electronic feeder host;

[0018] Step 6: Each electronic feeder host intelligently allocates and manages the wireless communication channels of its corresponding electronic feeder sub-machines and establishes communication. The electronic feeder host distributes the feeding plans of each livestock in the pen corresponding to each feeder to each electronic feeder sub-machine, and the feeding plans are stored in the storage unit of the electronic feeder sub-machine;

[0019] Step 7: According to the feeding plans of each livestock in the pen formulated for each electronic feeder host and electronic feeder sub-machine in Step S6, control commands are formed. Each electronic feeder controls the feeding equipment to execute the feeding plan according to the control commands, detects the feeding status and equipment status through various sensors, and feeds back to each electronic feeder sub-machine. The electronic feeder sub-machine transmits the feedback information to the corresponding electronic feeder host;

[0020] Step 8: Each electronic feeder host transmits the feeding status and equipment status of the feeders managed by itself and each electronic feeder sub-machine it manages to the Internet of Things intelligent gateway;

[0021] Step 9: The Internet of Things intelligent gateway uploads the feeding status and equipment status of each feeder in the entire Internet of Things feeding system to the cloud server platform and stores them in the cloud server platform;

[0022] Step 10: The cloud server platform obtains the historical feeding parameters of each livestock in the pen according to the data stored in Steps 3 and 9, learns and trains the above parameters through the artificial intelligence algorithm implanted in the cloud server platform, obtains the optimal feeding plan parameters of each livestock in the pen, and returns to Step 3 to update the formulated feeding plan, and repeats the execution in a loop.

[0023] Preferably, the feeding parameters in Step 10 include feeding time, feeding curve, maximum feeding amount, minimum feeding amount, feeding status, actual feed intake, and remaining feed amount. The cloud server platform and the operation terminal set the feeding time, feeding curve, maximum feeding amount, and minimum feeding amount of each electronic feeder host and its corresponding electronic feeder sub-machine, and view the current feeding status and equipment status through the operation terminal.

[0024] Preferably, the cloud server platform includes a data server, a Web server, and a Socket server. The operation terminal includes a PC terminal and a mobile terminal. The PC terminal and the mobile terminal establish a data connection with the data server through the standard API of the cloud server platform. The data server establishes a data connection with a third-party database through an open data interface.

[0025] Preferably, the human-computer interaction system includes a touch display screen. The feeding time, feeding curve, maximum feeding amount, and minimum feeding amount of each electronic feeder host and the corresponding electronic feeder slave are set through the touch display screen, and the current feeding status and device status are viewed through the touch display screen.

[0026] Preferably, in step 1, a common host channel is shared between each electronic feeder host and the Internet of Things intelligent gateway to establish wireless communication. The Internet of Things intelligent gateway and each electronic feeder host jointly schedule and allocate the wireless communication channels between the electronic feeder slaves managed by each electronic feeder host.

[0027] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0028] The intelligent livestock electronic feeder based on multi-channel wireless networking of the Internet of Things of the present invention relates to the Internet of Things, artificial intelligence, big data, and radio multi-channel technologies. Through the electronic ear tag identification terminal, electronic ear tags, the Internet, and the cloud service platform, the individual identity information of livestock is bound one-to-one with the main and slave machines of each Internet of Things intelligent livestock feeder in the farm (shed) and breeding equipment. Through the cloud service platform, server, Internet of Things intelligent gateway, Internet of Things intelligent livestock electronic feeder host and slave machine group, the feeding plans and parameters of each livestock in the farm (shed) can be remotely and intelligently managed, and the feeding history curve, parameters, and biological information such as the actual historical feed intake, health status, litter size, and birth health information of the young (cubs) of livestock are stored in the cloud database. After subsequent artificial intelligence analysis, a more scientific, healthy, and efficient feeding strategy can be proposed for livestock, and a research data basis is provided for the livestock breeding discipline to promote the scientific development of the discipline. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0030] Figure 1 It is a block diagram of the working principle of the present invention.

[0031] Figure 2 It is a block diagram of the structure of the electronic feeder host in the present invention.

[0032] Figure 3 It is a block diagram of the function of the human-computer interaction system in the present invention.

[0033] Figure 4 This is the workflow diagram of the present invention.

[0034] In the figure, 1 is the cloud server platform, 2 is the operation terminal, 3 is the third-party database, 4 is the Internet of Things intelligent gateway, 5 is the host of the electronic feeder, 51 is the microprocessor, 52 is the wireless signal transmission unit, 53 is the human-computer interaction system, 54 is the storage unit, 55 is the control switch unit, 56 is the digital-to-analog acquisition unit, 6 is the Internet of Things electronic ear tag identification terminal, and 61 is the electronic ear tag. Specific embodiments

[0035] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0036] Embodiment 1: As Figure 1 shown, an intelligent livestock electronic feeding system based on the Internet of Things includes a cloud server platform 1, a third-party database 3, an operation terminal 2, an Internet of Things intelligent gateway 4, and an Internet of Things electronic ear tag identification terminal 6. The cloud service platform, according to the feeding parameters of each livestock fed back by the device within one or more production cycles and feeding periods, such as: feeding time, feeding curve, feeding and drinking water temperature, actual feed intake of livestock, remaining feed amount; growth parameters of livestock, such as: backfat, weight, case, number of litters, total weight of born piglets, cases of born piglets; through artificial intelligence and big data calculation, intelligently plans the optimal feeding parameters for each livestock. The artificial intelligence algorithms for the cloud service platform to intelligently plan the optimal feeding parameters for each livestock include the Long Short-Term Memory algorithm and the Gate Recurrent Unit algorithm. The LSTM algorithm is a time-recurrent neural network, which is specifically designed to solve the long-term dependence problem existing in the general Recurrent Neural Network (RNN). In the embodiments of the present invention, this algorithm is transplanted into the planning of the optimal feeding parameters of livestock. LSTM is suitable for the training and prediction of the optimal feeding parameters in a long cycle; the GRU algorithm is similar to the LSTM algorithm and is also proposed to solve problems such as long-term memory and gradients in backpropagation. In the embodiments of the present invention, this algorithm is also transplanted into the planning of the optimal feeding parameters of livestock; GRU is easier to train and is suitable for the short-term training and prediction of the optimal feeding parameters.

[0037] The cloud server platform 1 is connected to the third-party database 3, the operation terminal 2 and the IoT smart gateway 4 respectively. The cloud server platform 1 includes a data server, a Web server and a Socket server. The feeding equipment management module in the cloud service platform can set the feeding time, monitor and update the feeding curve for each electronic feeding device mounted and registered in the intelligent livestock electronic feeding system of the IoT multi-channel wireless networking. The IoT edge computing smart gateway can be transmitted to the cloud service platform through standard protocols such as WebSocket, MQTT, Modbus_TCP or other open interfaces.

[0038] The operating terminal 2 includes a PC terminal and a mobile terminal. The mobile terminal can be a mobile phone, tablet computer or smart screen, etc. The PC terminal and the mobile terminal are equipped with APP, which establishes a data connection with the data server through the cloud server platform standard API, and the data server establishes a data connection with the third-party database 3 through an open data interface.

[0039] The Internet of Things electronic ear tag identification terminal 6 is connected to the electronic ear tag 61. The Internet of Things electronic ear tag identification terminal is an Internet of Things electronic ear tag PDA, i.e., a handheld computer. The electronic ear tag has a built-in RFID chip and is installed on the ear of the sow. Through the Internet of Things electronic ear tag PDA, the content in the electronic ear tag RFID can be read to record the identity information of the sow. The identity information includes the name of the company to which the pig belongs; the name and number of the pig house in the pig farm; the pen number and other information; the total information generally does not exceed 1k Bytes. The Internet of Things electronic ear tag PDA and the electronic ear tag communicate wirelessly through the passive RFID 125Khz / 13.56Mhz / 840-960Mhz channel.

[0040] The Internet of Things electronic ear tag recognition terminal 6 is connected to the cloud server platform 1 or the third-party database 3 or the Internet of Things intelligent gateway 4, and establishes data connection with the third-party Internet of Things platform supported by the Internet of Things electronic ear tag PDA through the Internet. Then the cloud server platform of this system can establish data connection from the database of the third-party Internet of Things platform through an open data interface; the cloud server platform of this system can establish an Internet API interface directly connected to the electronic ear tag PDA according to the SDK provided by the Internet of Things electronic ear tag PDA for data connection; if the Internet of Things electronic ear tag PDA is a local area network access handheld device such as Bluetooth or WiFi, the Internet of Things intelligent gateway in this system can establish data connection between the two according to the SDK provided by the Internet of Things electronic ear tag PDA.

[0041] The Internet of Things intelligent gateway 4 is connected to the electronic feeder host 5. The Internet of Things intelligent gateway can establish wireless communication with the Internet of Things intelligent livestock electronic feeder host via the 470 - 510Mhz frequency band in the Sub-1Ghz wireless network through standard protocols such as MQTT, Modbus_RTU, or LoRaWAN, and transmit the feeding time, feeding curve, and monitoring device operation status of each electronic feeder host and slave set by the above cloud server platform. The electronic feeder host 5 is connected to the electronic feeder slave. The electronic feeder host communicates and performs task scheduling with the group of Internet of Things electronic feeder slaves under its jurisdiction via the 470 - 510Mhz frequency band of the Sub-1G network through standard protocols such as MQTT, Modbus_RTU, or LoRaWAN, including: channel allocation, feeding time setting, feeding curve monitoring and updating, and monitoring device operation status.

[0042] Both the electronic feeder host 5 and the electronic feeder slave include a control terminal and an execution device, and a human-computer interaction system 53 is set in the electronic feeder host. The human-computer interaction system is a 5-inch / 7-inch touch screen display. The touch screen monitors the working status of each slave in the group of Internet of Things intelligent livestock electronic feeder slaves working in the managed channels, and modifies the feeding time, feeding times, maximum and minimum feeding amount boundaries, feeding curve parameters, and other customized parameters of each slave, and can freely mount and register a certain number of downstream groups of Internet of Things intelligent livestock electronic feeder slaves, with no more than 500 electronic feeder slaves in one group; intelligently allocate the wireless communication channels between the host and the slave group; can monitor and set the feeding time and feeding curve of all slaves in the group of networked intelligent livestock electronic feeder slaves, and feedback the device status of all slaves. The device status includes: whether the device is offline, whether the execution motor and solenoid valve of the device are faulty. The control terminal is connected to the execution device, and the control terminal in the electronic feeder host 5 is respectively connected to the human-computer interaction system 53, the Internet of Things intelligent gateway 4, and the control terminal in the electronic feeder slave.

[0043] Such as Figure 3As shown in the figure, the human-computer interaction system mainly includes three functional modules: device management, parameter management, and query. Device management includes: local settings, device registration, and communication settings. In this embodiment: 1. Enter the local settings, and the super administrator can set parameters such as the communication IP address, hardware ID, wireless communication center frequency, bandwidth, communication rate, etc. of this Internet of Things environment control terminal, as well as the time parameters of the time clock. 2. Enter the device registration, and the super administrator can register and mount up to 500 sub-devices with any number on the Internet of Things intelligent livestock electronic feeder host by inputting the unique hardware ID of each Internet of Things intelligent livestock electronic feeder sub-device controlled by this host, and name the software ID of each sub-device as the software ID name identifier displayed on the cloud service platform. 3. Enter the communication settings, and the super administrator can set parameters such as the wireless communication channel, bandwidth, communication rate, etc. of the above-mentioned Internet of Things intelligent livestock electronic feeder host and the sub-device group it manages and controls.

[0044] Parameter management includes: feeding time, feeding parameters. In this embodiment: 1. Enter the feeding time settings, and the user can set the feeding times and feeding time of each sub-device in the Internet of Things intelligent livestock electronic feeder host and the sub-device group it manages and controls. 2. Enter the feeding parameter settings, and the user can set the feeding curve, maximum feeding amount, and minimum feeding amount of each sub-device in the Internet of Things intelligent livestock electronic feeder host and the sub-device group it manages and controls.

[0045] Query includes: feeding status query, alarm log. In this embodiment: 1. Enter the feeding status query, and the user can query parameters such as the feeding plan, number of times fed, amount fed, current feeding operation status, actual feed intake, and remaining feed amount of each sub-device in the Internet of Things intelligent livestock electronic feeder host and the sub-device group it manages and controls. 2. Enter the alarm log, and the user can query the alarm information of each sub-device in the Internet of Things intelligent livestock electronic feeder host and the sub-device group it manages and controls, including: device offline, device execution motor, solenoid valve failure, feeding amount exceeding the maximum value, feeding amount below the minimum value, water temperature too high, water temperature too low, actual feed intake below the warning value, remaining feed amount above the warning value, etc.

[0046] Such as Figure 2As shown in the figure, the control terminal includes a microprocessor 51, a storage unit 54, a wireless signal transmission unit 52, a control switch unit 55, and an analog-to-digital acquisition unit 56. The microprocessor 51 is respectively connected to the storage unit 54, the wireless signal transmission unit 52, the control switch unit 55, the analog-to-digital acquisition unit 56, and the human-computer interaction system 53. The microprocessor is an ARM Cortex-M4 high-performance processor, embedded with an independently developed and designed Internet of Things real-time operating system, which performs task management, data information management, and device control scheduling for the Internet of Things intelligent livestock electronic feeder host and slave machines; the storage unit is an on-board Flash chip, which is used to store the feeding parameters of all slave machines in the Internet of Things intelligent livestock electronic feeder host and the group of Internet of Things intelligent livestock electronic feeder slave machines managed by this host, such as: feeding time, feeding curve, maximum feeding amount, minimum value, feeding status, actual feed intake, remaining feed amount, etc.;

[0047] The wireless signal transmission unit is a Sub-1G wireless radio frequency unit. The Sub-1G wireless radio frequency unit can be optionally equipped with radio frequency chip modules such as HW3000, A7139, SI4432, CC1310 / 1312, SX1278 / 1268 / 1301, etc. that support hot plugging. It is a radio frequency unit of LoRa, FSK, OOK, MSK protocols with a center carrier frequency of 433MHz / 868MHz / 915MHz, etc. In this embodiment, it is an SX1278 radio frequency chip module, with a LoRa network physical protocol in the 470-510MHz frequency band, and optionally equipped with Modbus_RTU or LoraWAN communication protocols.

[0048] The execution device includes a motor, a solenoid valve, a current sensor, a voltage sensor, a level sensor, a water temperature sensor, and a liquid level sensor connected to each other. The motor and the solenoid valve are both connected to the control switch unit 55. The control switch unit is a relay IO node. By controlling the start / stop of the motor and through a transmission structure, the feed discharge amount of the feeder is controlled. The current sensor, voltage sensor, level sensor, water temperature sensor, and liquid level sensor are all connected to the analog-digital acquisition unit 56. The analog-digital acquisition unit is used to collect the numerical values of the sensing transmitters such as the motor current parameter, water temperature, and liquid level to monitor whether the motor is started or blocked, and to collect the water temperature, liquid level, and level data. The intelligent livestock electronic feeder based on multi-channel wireless networking of the Internet of Things of the present invention relates to the Internet of Things, artificial intelligence, big data, and radio multi-channel technologies. Through the electronic ear tag PDA, electronic ear tag, Internet, and cloud service platform, the individual identity information of livestock is bound one-to-one with the main and slave machines of each Internet of Things intelligent livestock feeder in the farm building and breeding equipment. Through the cloud service platform, server, Internet of Things intelligent gateway, and the host and slave machine group of the Internet of Things intelligent livestock electronic feeder, the remote and intelligent management of the feeding plan and parameters of each livestock in the farm building can be realized, and the feeding history curve, parameters, and biological information such as the actual historical feed intake, health status, litter size, and birth health information of the cubs of the livestock are stored in the cloud database. After subsequent artificial intelligence analysis, a more scientific, healthier, and more efficient feeding strategy can be proposed for the livestock, and a research data basis can be provided for the livestock breeding discipline to promote the scientific development of the discipline.

[0049] Embodiment 2: As Figure 4 shown, a working method of an intelligent livestock electronic feeding system based on the Internet of Things includes the following steps:

[0050] Step 1: First, register each electronic feeder host 5 and the electronic feeder slave units on the cloud server platform 1 through the human-computer interaction system 53. The human-computer interaction system 53 includes a touch display screen. Set the feeding time, feeding curve, maximum feeding amount, and minimum feeding amount of each electronic feeder host 5 and the corresponding electronic feeder slave units through the touch display screen. View the current feeding status and device status through the touch display screen. Set parameters such as the wireless communication center frequency, bandwidth, and communication rate between each Internet of Things intelligent livestock electronic feeder host and slave unit groups, between each Internet of Things intelligent livestock electronic feeder host and the Internet of Things intelligent gateway on the visual graphic human-computer interaction system on the touch display screen. Each electronic feeder host 5 and the Internet of Things intelligent gateway 4 share a host channel to establish wireless communication. The Internet of Things intelligent gateway 4 and each electronic feeder host 5 jointly schedule and allocate the wireless communication channels between the electronic feeder slave units managed by each electronic feeder host to achieve multi-channel wireless networking of the Internet of Things intelligent livestock electronic feeding system of the present invention to avoid concurrent wireless signal interference between different groups;

[0051] Use the Internet of Things electronic ear tag identification terminal 6 to scan the electronic ear tag 61 worn on the ear of each livestock, and identify the identity of the livestock through the Internet of Things electronic ear tag identification terminal 6. For example: belonging to a certain company, a certain livestock farm, a certain livestock house, a certain pen, etc. Subsequently, directly transmit the livestock identity information to the cloud server platform 1 through the Internet of Things electronic ear tag identification terminal 6 or transfer it to the cloud server platform 1 through the third-party database 3 or the Internet of Things intelligent gateway 4. Via the cloud service platform, bind the device ID of each Internet of Things intelligent livestock electronic feeder in the feeding system, including each host and each slave unit in the slave unit group, with the identity ID of each livestock, so as to realize customized feeding rules for each livestock and conduct targeted feeding for each livestock, thereby achieving precise feeding for individual livestock;

[0052] Step 2: Subsequently, use the operation terminal 2 and the Internet of Things electronic ear tag identification terminal 6 to bind the device ID of each electronic feeder host 5 and the electronic feeder slave units that have been registered and managed in the cloud server with the identity ID of each livestock that has been entered. For example: the Internet of Things intelligent livestock electronic feeder device in a certain pen in a certain pig house in a certain farm of a certain company is bound to a pig with a certain ear tag number. Group the electronic feeder host 5 and the electronic feeder slave units to form a control mode in which one electronic feeder host manages several electronic feeder slave units;

[0053] Step 3: The feeding expert formulates a feeding plan based on the biological indicators of each livestock in the positioning pen. The biological indicators include, for example, daily / weekly age, livestock weight, livestock pregnancy history, livestock pregnancy and litter records, livestock medical records, livestock drug use history, etc. The specific targeted feeding plan formulated includes: feeding frequency, feeding time, feeding curve, maximum and minimum boundary values of the feeding amount, etc. Through the operation terminal 2, the biological indicators, feeding plan, and the corresponding bindings of the equipment ID of the electronic feeder host 5, the equipment ID of the electronic feeder slave, and the identity ID of the livestock in the positioning pen in Step 2 are bound, and the binding relationship is input into the cloud server platform 1;

[0054] Step 4: Based on the binding relationship between the feeding plan and the feeding equipment ID of each livestock in the cloud server platform stored in Step 3 and the identity ID of the livestock in the positioning pen, the cloud server platform 1 maps the feeding plan of each livestock in the pen to the corresponding electronic feeder host 5 and electronic feeder slave, and transmits the above mapping content to the Internet of Things intelligent gateway 4 through a wireless signal and stores it in the Internet of Things intelligent gateway 4;

[0055] Step 5: The Internet of Things intelligent gateway 4 performs wireless networking with each electronic feeder host 5 in the system under the host channel, and distributes and stores the feeding plan of each livestock in the pen for each electronic feeder host 5 and the corresponding electronic feeder slave in the storage unit 54 of each electronic feeder host 5;

[0056] Step 6: Each electronic feeder host 5 intelligently allocates and manages the wireless communication channels of the corresponding electronic feeder slaves and establishes communication. The electronic feeder host 5 distributes the feeding plan of each livestock corresponding to each feeder to each electronic feeder slave, and the feeding plan is stored in the storage unit 54 of the electronic feeder slave;

[0057] Step 7: According to the feeding plan corresponding to each livestock formulated for each electronic feeder host 5 and electronic feeder slave in Step S6, a control command is formed. Each electronic feeder controls the feeding equipment to execute the feeding plan according to the control command, and feeds back the feeding status and equipment status through various sensors and internal detection circuits. The feeding status includes status parameters such as the number of times fed, the amount fed, the current feeding operation status, the actual feed intake, the remaining feed amount, etc. The equipment status includes whether the equipment is offline, whether the equipment execution motor and solenoid valve are faulty, and feeds back to each electronic feeder slave. The electronic feeder slave transmits the feedback information to the corresponding electronic feeder host 5;

[0058] Step 8: Each electronic feeder host 5 transmits the feeding status and equipment status of the feeders managed by itself and the electronic feeder slaves it manages to the Internet of Things intelligent gateway 4;

[0059] Step 9: The Internet of Things intelligent gateway 4 uploads the feeding status and device status of each feeder in the entire Internet of Things feeding system to the cloud server platform 1 and stores them in the cloud server platform 1;

[0060] Step 10: The cloud server platform 1 obtains the historical feeding parameters of each livestock in the pen according to the data stored in Steps 3 and 9. The feeding parameters include feeding time, feeding curve, maximum feeding amount, minimum feeding amount, feeding status, actual feed intake, and remaining feed amount. The cloud server platform and the operation terminal set the feeding time, feeding curve, maximum feeding amount, and minimum feeding amount of each electronic feeder host and the corresponding electronic feeder slave. The current feeding status and device status are viewed through the operation terminal. The above parameters are learned and trained through the LSTM algorithm and GRU algorithm implanted in the cloud server platform 1 to obtain the optimal feeding plan parameters for each livestock in the pen, and then feedback back to Step 3 to update the formulated feeding plan. Steps 3 to 10 are repeated. The present invention is not only applicable to the breeding of pigs, but also applicable to the breeding of large livestock such as cattle and sheep.

[0061] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A working method of an intelligent livestock electronic feeding system based on the Internet of Things, characterized in that It includes the following steps: Step 1: First, register each electronic feeder host and electronic feeder slave on the cloud server platform through the human-computer interaction system. Use the Internet of Things electronic ear tag identification terminal to scan the electronic ear tags worn on the ears of each livestock, identify the identity of the livestock through the Internet of Things electronic ear tag identification terminal, and then directly transmit the livestock identity information to the cloud server platform through the Internet of Things electronic ear tag identification terminal or transfer it to the cloud server platform through a third-party database or the Internet of Things intelligent gateway; Step 2: Subsequently, use the operation terminal and the Internet of Things electronic ear tag identification terminal to bind the device IDs of each electronic feeder host and electronic feeder slave that have been registered and managed in the cloud server with the identity IDs of each livestock that have been entered, and group the electronic feeder hosts and electronic feeder slaves to form a control mode in which one electronic feeder host manages several electronic feeder slaves; Step 3: The feeding expert formulates a feeding plan according to the biological indicators of each livestock in the positioning pen, and through the operation terminal, correspondingly binds the biological indicators, feeding plan, the electronic feeder host device ID and the electronic feeder slave device ID in Step 2, and the identity ID of the livestock in the positioning pen, and inputs the binding relationship into the cloud server platform; Step 4: According to the binding relationship between the feeding plan and the feeding device ID of each livestock in the pen stored in the cloud server platform in Step 3 and the identity ID of the livestock in the positioning pen, map the feeding plan of each livestock in the pen to the corresponding electronic feeder hosts and electronic feeder slaves, and transmit the above mapping content to the Internet of Things intelligent gateway through a wireless signal and store it in the Internet of Things intelligent gateway; Step 5: The Internet of Things intelligent gateway performs wireless networking with each electronic feeder host in the system under the host channel, and distributes and stores the feeding plan of each livestock in the pen for the corresponding electronic feeder hosts and electronic feeder slaves in the storage unit of each electronic feeder host; Step 6: Each electronic feeder host intelligently allocates and manages the wireless communication channels of the corresponding electronic feeder slaves and establishes communication. The electronic feeder host distributes the feeding plan of each livestock corresponding to each feeder to each electronic feeder slave, and the feeding plan is stored in the storage unit of the electronic feeder slave; Step 7: According to the feeding plan for each livestock in the pen formulated for each electronic feeder host and electronic feeder slave in Step S6, form a control command. Each electronic feeder controls the feeding device to execute the feeding plan according to the control command, detects the feeding state and device state through each sensor, and feeds back to each electronic feeder slave. The electronic feeder slave transmits the feedback information to the corresponding electronic feeder host.

2. The working method of the intelligent livestock electronic feeding system based on the Internet of Things according to claim 1, characterized in that, It also includes the following steps: Step 8: Each electronic feeder host transmits the feeding state and device state of the feeders managed by itself and the electronic feeder slaves it manages to the Internet of Things intelligent gateway; Step 9: The Internet of Things intelligent gateway uploads the feeding state and device state of each feeder in the entire Internet of Things feeding system to the cloud server platform and stores them in the cloud server platform; Step 10: The cloud server platform obtains the historical feeding parameters of each livestock in the pen based on the data stored in Step 3 and Step 9, learns and trains the above parameters through the artificial intelligence algorithm implanted in the cloud server platform to obtain the optimal feeding plan parameters for each livestock in the pen, and then returns to Step 3 to update the formulated feeding plan, and repeats the execution in a loop.

3. The working method of the intelligent livestock electronic feeding system based on the Internet of Things according to claim 2, characterized in that, The feeding parameters in Step 10 include feeding time, feeding curve, maximum feeding amount, minimum feeding amount, feeding status, actual feed intake, and remaining feed amount. The cloud server platform and the operation terminal set the feeding time, feeding curve, maximum feeding amount, and minimum feeding amount of each electronic feeder host and the corresponding electronic feeder sub-machine, and view the current feeding status and device status through the operation terminal.

4. The working method of the intelligent livestock electronic feeding system based on the Internet of Things according to any one of claims 1-3, characterized in that, In Step 1, a host channel is shared between each electronic feeder host and the Internet of Things intelligent gateway to establish wireless communication. The Internet of Things intelligent gateway and each electronic feeder host jointly schedule and allocate the wireless communication channels between the electronic feeder sub-machines managed by each electronic feeder host.

5. The working method of the intelligent livestock electronic feeding system based on the Internet of Things according to claim 4, characterized in that, The intelligent livestock electronic feeding system includes a cloud server platform, a third-party database, an operation terminal, an Internet of Things intelligent gateway, and an Internet of Things electronic ear tag identification terminal. The cloud server platform is respectively connected to the third-party database, the operation terminal, and the Internet of Things intelligent gateway. The Internet of Things electronic ear tag identification terminal is connected to the cloud server platform, or the third-party database, or the Internet of Things intelligent gateway. The Internet of Things intelligent gateway is connected to the electronic feeder host, the electronic feeder host is connected to the electronic feeder sub-machine, and the Internet of Things electronic ear tag identification terminal is connected to the electronic ear tag.

6. The working method of the intelligent livestock electronic feeding system based on the Internet of Things according to claim 5, characterized in that, Both the electronic feeder host and the electronic feeder sub-machine include a control terminal and an execution device, and a human-computer interaction system is set in the electronic feeder host. The control terminal is connected to the execution device, and the control terminal in the electronic feeder host is respectively connected to the human-computer interaction system, the Internet of Things intelligent gateway, and the control terminal in the electronic feeder sub-machine.

7. The working method of the intelligent livestock electronic feeding system based on the Internet of Things according to claim 6, characterized in that, The control terminal includes a microprocessor, a storage unit, a wireless signal transmission unit, a control switch unit, and an analog-to-digital acquisition unit. The microprocessor is respectively connected to the storage unit, the wireless signal transmission unit, the control switch unit, the analog-to-digital acquisition unit, and the human-computer interaction system. The execution device includes a motor, a solenoid valve, a current sensor, a voltage sensor, a level sensor, a water temperature sensor, and a liquid level sensor, which are connected. The motor and the solenoid valve are both connected to the control switch unit, and the current sensor, the voltage sensor, the level sensor, the water temperature sensor, and the liquid level sensor are all connected to the analog-to-digital acquisition unit.

8. The working method of the intelligent livestock electronic feeding system based on the Internet of Things according to claim 6 or 7, characterized in that, The cloud server platform includes a data server, a Web server, and a Socket server. The operation terminal includes a PC terminal and a mobile terminal. The PC terminal and the mobile terminal establish a data connection with the data server through the standard API of the cloud server platform. The data server establishes a data connection with the third-party database through an open data interface.

9. The working method of the intelligent livestock electronic feeding system based on the Internet of Things according to claim 8, characterized in that, The human-machine interaction system includes a touch display screen. The feeding time, feeding curve, maximum feeding amount, and minimum feeding amount of each electronic feeder host and the corresponding electronic feeder slave are set through the touch display screen. The current feeding status and device status are viewed through the touch display screen.

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