KR102202857B1 - System for feed management and ordering for feed bin with feed residue analysis function construction based on big data collection and powered by solar energy, and method thereof - Google Patents

Abstract

The present invention relates to a feed management order system and a feed management ordering method for establishing a feed residual range analysis function based on big data collection and a feed bean powered by solar energy, and more specifically, storing feed for feed feeding Based on big data collection to measure the remaining amount of feed stored in the feed bin and the condition of the feed storage environment (temperature/humidity) using the feed bin monitoring IoT unit with a laser sensor and a temperature/humidity measurement sensor attached to the feed bin. It relates to the construction of the feed residual range analysis function and the feed management order system for feed bins powered by solar energy, and the feed management order method.

Description

System for feed management and ordering for feed bin with feed residue analysis function construction based on big data collection-based feed residue analysis function construction based on big data data collection and powered by solar energy, and method thereof}

The present invention relates to a feed management order system and a feed management ordering method for establishing a feed residual range analysis function based on big data collection and a feed bean powered by solar energy, and more specifically, storing feed for feed feeding Based on big data collection to measure the remaining amount of feed stored in the feed bin and the condition of the feed storage environment (temperature/humidity) using the feed bin monitoring IoT unit with a laser sensor and a temperature/humidity measurement sensor attached to the feed bin. It relates to the construction of the feed residual range analysis function and the feed management order system for feed bins powered by solar energy, and the feed management order method.

Agricultural innovation through the convergence of new ICT technologies is expanding and developing into a high value-added industry. In addition, it is evaluated that the ICT convergence of the domestic agricultural and livestock industry is a rudimentary step compared to other industries, and there is a limit in improving the utilization, despite the grafting of various advanced technologies. Informatization in the agricultural and livestock food sector has been promoted in four areas: expanding ICT convergence, strengthening information linkage, establishing a stable supply chain, and expanding information utilization.

Major overseas countries are expanding their strategies for national agricultural and livestock innovation based on ICT convergence.

Accordingly, it can be said that the feed industry, which imports most of the grain, produces and supplies feed, is the largest base industry among the related industries in the whole livestock industry, and at the same time has an interdependent relationship that has an absolute influence on the price competitiveness of various livestock products and the income of farm households have. In the case of broilers and pigs, the ratio of feed cost to the total production cost is high at 63.0% and 54.0%, respectively, so the ratio of the relative feed cost to the total production cost is an important factor in the profit structure of livestock farms. In addition, in order to maximize the efficiency of sales, payback, and farmhouse services under the high cost structure due to the complicated distribution channels of domestic feed, it is necessary to switch to a more efficient distribution system, and various distribution bases that are currently operated redundantly by each company. It is necessary to expand the volume of direct transactions by reducing additional logistics costs through joint use plans for subsidiaries and subsidiaries.

Accordingly, the livestock feed supply chain management service using IoT technology designed to simplify and automate the process that occurs between livestock farmers and feed suppliers reduces production, distribution, and supply costs while providing beneficial data to both suppliers and consumers. There is a need for technology development to be able to receive it.

Korean Patent Registration 10-1632574 (2016.06.16.)

The present invention is to solve the above problems, and the residual amount of feed being stored in the feed bin using a feed bin monitoring IoT unit in which a laser sensor and a temperature/humidity measurement sensor are attached to a feed bin that stores feed for feed feeding. To provide feed management ordering system and feed management ordering method for feed bins based on big data collection to measure the condition of food storage environment (temperature/humidity) and feed bins powered by solar energy will be.

In addition, in the present invention, the measured data is periodically collected using wired (power line communication: PLC) and wireless (Zigbee communication), but the power for feed bin monitoring uses the existing AC power as a regular power source, and A photovoltaic panel is installed to enable the use of stored energy as power, so that data from feed bins can be collected even in the event of a power outage to complement the integrity of the data. It is to provide a feed management ordering system and a feed management ordering method of a feed bean powered by.

In addition, in the present invention, the data collected through the IoT unit installed in each feed bin is transmitted to a supply chain network management service server (SCM Server) using a network such as the Internet, but to the supply chain network management service server (SCM Server). The transmitted data can be used to predict production, supply, and stock acquisition based on automatic ordering and inventory measurement, based on big data, to establish a feed residual level analysis function based on big data collection and power solar energy. It is to provide a feed management ordering system and a feed management ordering method for one feed bean.

In addition, the present invention can predict the supply schedule according to the change in the amount of feed consumed for each farm, and can bring a beneficial change in the establishment of the delivery schedule according to the automatic order, so that both livestock farms and feed suppliers can use time and manpower. Establishment of a feed residual content analysis function based on big data collection to enable reduction in factors and ultimately to reduce economic costs, and feed management ordering system and feed management ordering method for feed beans powered by solar energy It is to provide.

However, the objects of the present invention are not limited to the above-mentioned objects, and other objects that are not mentioned will be clearly understood by those skilled in the art from the following description.

In order to achieve the above object, the feed management order system of feed bins based on big data collection based on feed residual range analysis function and solar energy as a power source according to an embodiment of the present invention includes a plurality of feed bins 100, In the feed management order system including the IoT detection unit 200 formed in each feed bin 100, the photovoltaic device 200a, the IoT smart gateway device 300, and the feed management server 400, solar power generation The device 200a stores solar energy in the battery 210a through solar power generation.
The feed management unit 410 of the feed management server 400 receives sensing information from the IoT smart gateway device 300, and the IoT smart gateway device 300 corresponding to the sensing information, the IoT detection unit 200, and the feed bin The information of (100) is matched, the matched sensing information is stored in the sensing information DB (404), and the stored sensing information is managed, but when the sensing information is received, the feed bin (100) corresponding to the remaining amount of feed of the sensing information Compare the preset reference amount for the product, and if the remaining amount of feed is less than the standard amount, it is determined that the feed is insufficient and an online order is required, and an online order is ordered and settled by referring to the feed manufacturer information. When the deadline arrives, the farmers are charged for feed ordered online, and the feed order cost is settled to the feed manufacturer from the feed price of the farmer, and livestock farmers corresponding to multiple DBs for management of livestock farms, gateways, and feed. DB (401), gateway DB (402), feed bin DB (403), sensing information DB (404), feed manufacturer DB (405), feed information DB (406), billing DB (407), order DB (408) It manages and registers the information of livestock farms registered as a member (such as the terminal number of the mobile device 700) and stores it in the livestock farm DB 401, and the feed management unit 410 is an IoT smart gateway device installed for each livestock farm. When the information of 300 is registered and stored in the gateway DB 402, the gateway information is mapped to the terminal number and farmhouse information of the mobile device 700 and 1:1, and the IoT smart gateway device 300 and the mobile device 700 When the information of the feed bean 100 managed by) is registered and stored in the feed bean DB 403, the information of the IoT smart gateway device 300 / mobile device 700 and the feed bean 100 is 1:n( n is a natural number of 2 or more), and IoT smart gateway device 300, mobile device 700, I When receiving sensing information including information of the oT detection unit 200 and the feed bin 100 and storing it in the sensing information DB 404, the information of the IoT detection unit 200 and the feed bin 100 is 1:1. When the information of the feed manufacturer is registered and stored in the feed manufacturer DB 405, the feed manufacturer is 1 to the feed of the feed bin 100: m (m is 2 equal to or different from n). Above natural number), and when feed information including livestock type, age, and use of feed sold by feed manufacturers is registered and stored in feed information DB 406, the feed bin 100 and feed are 1:1. In the case of a mixed feed of L (L is a natural number equal to or different from n, m) products, the feed bin 100 and feed are mapped to 1: L, and the feed manufacturer's basic or event charging applied from the feed manufacturer The information is registered and stored in the billing DB 407, it is determined that the remaining amount of feed is insufficient, and order information is generated and stored in the order DB 408 whenever an online order is placed.

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According to an embodiment of the present invention, the feed residual level analysis function construction based on big data collection and the feed management ordering system and the feed management ordering method of a feed bin powered by solar energy include: a feed bin that stores feed for feed feeding. By using the feed bin monitoring IoT unit with a laser sensor and a temperature/humidity measurement sensor attached to it, the effect of measuring the residual amount of feed stored in the feed bin and the condition of the feed storage environment (temperature/humidity) can be provided.

In addition, according to another embodiment of the present invention, the feed management ordering system and the feed management ordering method of a feed bin using solar energy as a power source and the construction of a feed residual level analysis function based on big data collection, periodically wire the measured data. It is collected using (power line communication: PLC) and wireless (Zigbee communication), but the power for feed bean monitoring uses the existing AC power as a regular power source, and the stored energy is used as power by installing a photovoltaic panel. It provides the effect of supplementing the integrity of the data by collecting the data of the feed bean even in the event of a power outage.

In addition, according to another embodiment of the present invention, the feed management ordering system and feed management ordering method of a feed bin using solar energy as a power source and building a feed residual level analysis function based on big data collection is an IoT unit installed in each feed bin. The data collected through the network is transmitted to the supply chain network management service server (SCM Server) using a network such as the Internet, but the data transmitted to the supply chain network management service server (SCM Server) is automatically ordered and stocked based on big data. It can provide an effect that can be used to predict production, supply, and inventory acquisition according to measurement.

In addition, according to another embodiment of the present invention, the feed residual level analysis function construction based on big data collection and the feed management ordering system and feed management ordering method of a feed bean powered by solar energy, include the amount of feed consumed per farm. It is possible to predict the supply schedule according to the change trend of the country and bring a beneficial change in the establishment of the delivery schedule according to the automatic order, so both livestock farmers and feed suppliers can save on factors such as time and manpower input, resulting in economic cost reduction. Can provide an effect.

1 is a diagram illustrating a feed management order system 1 for feed bins using solar energy as a power source and building a feed residual range analysis function based on big data collection according to an embodiment of the present invention.
FIG. 2 is a block diagram showing in detail the components of the feed management order system 1 of a feed bin using solar energy as a power source and building a feed residual range analysis function based on big data collection of FIG. 1.
3 to 6 are diagrams for explaining the IoT detection unit 200 of the feed management order system 1 of the feed bean feed bin using the big data collection-based feed residual range analysis function construction and solar energy of FIG. 1 to be.
7 and 8 are for explaining the IoT smart gateway device 300 in the feed management order system 1 of the feed bean feed management order system (1) building a feed residual range analysis function based on big data collection of FIG. 1 and solar energy as power It is a drawing.
9 is a view of the function providing unit 420 of the feed management server 400 of the feed management order system 1 of the feed bin using solar energy as a power source and building a feed residual range analysis function based on big data collection of FIG. It is a diagram showing the components.
10 to 13 are views for explaining the functions provided by the function providing unit 420 of the feed management server 400 of the feed management order system 1 of FIG. 1.
14 is a flowchart illustrating a method of ordering feed management based on a feed management order system for a feed bean using solar energy and building a feed residual level analysis function based on big data collection according to an embodiment of the present invention.

Hereinafter, a detailed description of a preferred embodiment of the present invention will be described with reference to the accompanying drawings. In the following description of the present invention, if it is determined that a detailed description of a related known function or configuration may unnecessarily obscure the subject matter of the present invention, a detailed description thereof will be omitted.

In the present specification, when one component'transmits' data or a signal to another component, the component can directly transmit the data or signal to another component, and through at least one other component It means that data or signals can be transmitted to other components.

1 is a diagram illustrating a feed management order system 1 for feed bins using solar energy as a power source and building a feed residual range analysis function based on big data collection according to an embodiment of the present invention. FIG. 2 is a block diagram showing in detail the components of the feed management order system 1 of a feed bin using solar energy as a power source and building a feed residual range analysis function based on big data collection of FIG. 1.

3 to 6 are diagrams for explaining the IoT detection unit 200 of the feed management order system 1 of the feed bean feed bin using the big data collection-based feed residual range analysis function construction and solar energy of FIG. 1 to be.

7 and 8 are for explaining the IoT smart gateway device 300 in the feed management order system 1 of the feed bean feed management order system (1) building a feed residual range analysis function based on big data collection of FIG. 1 and solar energy as power It is a drawing.

9 is a view of the function providing unit 420 of the feed management server 400 of the feed management order system 1 of the feed bin using solar energy as a power source and building a feed residual range analysis function based on big data collection of FIG. It is a diagram showing the components.

First, referring to FIG. 1, the feed management order system 1 (hereinafter, the feed management order system) of a feed bin using solar energy as a power source and establishment of a feed residual range analysis function based on big data collection is a feed bin 100 ), IoT detection unit 200, solar power generation device 200a, IoT smart gateway device 300, feed management server 400, network 500, big data server 600, mobile device 700 Can include.

The feed bin 100 is a feed storage tank that stores feed, which serves as food for livestock in a farm. Each farm has at least one feed bin 100 depending on the number of livestock. Feed bin 100 receives feed through an inlet corresponding to the top cover 101, and stores feed therein. A feed outlet is formed at the lower end of the feed bin 100. The IoT sensing unit 200 is installed on the inner surface of the cover 101 to measure the distance between the IoT sensing unit 200 and the feed inside the feed bin 100, and measure the temperature and humidity of the inner feed space. do.

The IoT detection unit 200 corresponds to the measurement unit of the feed management ordering system 1 provided by the present invention. The IoT sensing unit 200 is a device that measures the amount of feed remaining (distance) and storage environment (temperature and humidity) inside the feed bin 100, which is an important factor in raising livestock in farms. The IoT sensing unit 200 includes a plurality of sensors, and transmits data sensed through the sensors through power line communication (PLC) or wired or wireless communication.

Here, in the case of power line communication, the IoT sensing unit 200 may transmit sensing data to the IoT smart gateway device 300 as an electrical signal. A PLC modem for power line communication is installed in each of the transmitting-side IoT sensing unit 200 and the receiving-side IoT smart gateway device 300. In addition, in the case of wired and wireless communication, the IoT sensing unit 200 may become an IoT device and transmit sensing data to the IoT smart gateway device 300 through IoT communication. Hereinafter, it is assumed that power line communication is for convenience of description.

The IoT smart gateway device 300 corresponds to the gateway unit of the feed management ordering system 1 provided by the present invention. The IoT smart gateway device 300 is a computer device that is installed for each individual farm and receives sensing data from the IoT sensing unit 200. The IoT smart gateway device 300 receives sensing data transmitted by the at least one IoT sensing unit 200 of the farm based on power line communication. The IoT smart gateway device 300 calculates distance data of the output sensing data as a feed remaining amount, and converts the received sensing data signal into information of temperature and humidity. In addition, the IoT smart gateway device 300 transmits the feed remaining amount, temperature, and humidity as sensing information to the feed management server 400.

In this case, the photovoltaic device 200a may provide a wired/wireless communication feed bin remaining amount and an internal environment monitoring IoT system capable of using solar energy as a power source on the feed management order system 1. That is, the photovoltaic device 200a can supply photovoltaic energy to the IoT sensing unit 200 and the IoT smart gateway device 300 corresponding to the remaining amount of the feed bin and the internal environment monitoring IoT unit for both solar energy and constant power. have.

On the other hand, the IoT detection unit 200 is a wired communication (PLC) and wireless communication (Zigbee/WiFi) for both wired communication (PLC) and wireless communication (Zigbee) for monitoring the remaining amount of feed bin and internal environment. ) To perform data transmission.

To this end, the photovoltaic device 200a must be equipped with a charging circuit to use the power charged in the battery 210a by photovoltaic power generation, so that the photovoltaic power generation through the photovoltaic inverter module 220a By converting the DC 12V voltage charged in the battery 210a into AC 220V, the IoT detection unit 200 and the IoT smart gateway device 300 corresponding to the devices using AC 220V around the feed bin 100 in case of an emergency in a livestock farm Make it available for use on the back.

That is, the IoT detection unit 200 and the IoT smart gateway device 300 basically use AC power, which is a constant power, so if the AC power, which is the constant power, is short-circuited, the battery 210a stored as an emergency power solar power generation ) A photovoltaic inverter module 220a, which is a module that is automatically switched to use power (DC power), may perform a function.

On the other hand, the data communication protocol between the IoT detection unit 200 and the IoT smart gateway device 300 is not divided into wired communication (PLC) or wireless communication (Zigbee), but can be used in combination, and the protocol is different depending on the communication method. It is desirable to avoid confusion in transmission/reception schemes by using one protocol without needing to be changed.

To this end, the IoT smart gateway device 300 has a 2-1 communication unit 320 as a PLC/Zigbee communication conversion module, so that it is designed to use AC power, which is basically a constant power source, and is relatively stable wired communication (PLC) in communication. Can be applied to use, and when the AC power, which is the constant power, is short-circuited, since wired communication (PLC) cannot be used, the second control unit 310 can automatically switch to wireless communication (Zigbee). .

By using the Zigbee mode for wireless communication (Zigbee) between the first communication unit 230 of the IoT sensing unit 200 and the 2-1 communication unit 320 of the IoT smart gateway device 300, point-to-point peer-to-point It provides fast and stable communication in peer, multipoint/star configurations configuration, and can easily realize strong end point connection.

The IoT sensing unit 200 with the enclosure designed as shown in FIG. 3 uses a laser sensor included in the sensor unit 220 to measure the amount of feed inside the feed bin 100.

In the measurement method for measuring the remaining amount of feed inside the feed bin 100 using a laser sensor, unlike the difference between the error rate of distance measurement data appearing large when using the ultrasonic sensor for the feed bin 100 in which the food stagnation phenomenon occurs, the laser sensor When using, by scanning the feed surface in a 2D method and calculating the remaining amount of feed using the average value, it is possible to accurately measure the remaining amount of feed even if the feed stagnation phenomenon occurs inside the feed bin 100.

That is, unlike the use of the ultrasonic sensor as shown in FIG. 4A, when using the laser sensor, the scan rotation angle of the laser sensor is calculated and operated according to the height and diameter of the feed bin 100, so that the feed bin 100 of various sizes It has an advantage that can cope with it.

To this end, the first control unit 210 of the IoT detection unit 200 equipped with a laser sensor is attached to the inner center of the feed bin manhole, and measures the position value (distance) while rotating the sensor at the center position inside the feed bin to feed feed. When calculating the remaining amount (%) through the surface scan method, it is possible to calculate through "the height of the feed bin-the average value of the feed surface scan data".

The advantage of such a laser sensor is that it can be measured irrespective of the stagnation phenomenon of feed and the curved shape of the surface, and it is possible to judge the severity of the stagnation phenomenon, and the maximum measuring distance is up to 20m compared to 7m in the case of ultrasonic sensor. It can provide a scalable effect.

In the 2D scanning method of the feed bin 100 inner feed surface using a laser sensor, the first control unit 210 calculates the 2D scan range of the feed bin 100 inner feed surface through the height and diameter as shown in FIG. It may be formed inside the feed bin 100 to be able to.

Further, the detailed components of the IoT sensing unit 200 may be expressed in a block diagram as shown in FIG. 6, and a servo motor for rotating the laser sensor must be provided.

On the other hand, the IoT detection unit 200 includes a temperature and humidity sensor in addition to a laser sensor as the sensor unit 220 to measure the distance to the feed, temperature and humidity, etc. The smart gateway device 300 may receive distance data from at least one IoT sensing unit 200 to calculate the remaining feed amount, and transmit sensing information such as the remaining feed amount, temperature, and humidity to the feed management server 400.

In addition, the detailed components of the IoT smart gateway device 300 can be expressed in a block diagram as shown in FIG. 7, and by being formed as a Wired & Wireless (Wi-Fi) Embedded System, the feed management server 400 corresponding to the SCM Cloud Server And, the communication with the big data server 600 is possible for both Wired (Ethernet) & Wireless (Wi-Fi), and the Android platform can be applied.

Accordingly, the IoT smart gateway device 300 first checks whether wired communication (Ethernet) is possible with the feed management server 400 and the big data server 600 through the network 400, and when wired communication (Ethernet) is not possible , It can be implemented and applied to automatically switch to wireless communication (Wi-Fi). On the other hand, in another embodiment of the present invention, the IoT smart gateway device 300 checks whether communication is possible for the mobile device 700 through a mobile network connected to the network 400, and if communication is not possible, wireless communication (Wi -Fi) can be implemented and applied automatically.

The IoT smart gateway device 300 may provide an environment setting and monitoring program GUI to the livestock farm through data transmission to the feed management server 400 and the mobile device 700 through the network 400 as shown in FIG. have.

Feed management server 400 corresponds to the server portion of the feed management order system 1 provided by the present invention. Feed management server 400 may be built as a cloud server. The feed management server 400 stores and manages the sensing information received from the IoT smart gateway device 300 in a DB. The feed management server 300 orders feed online when the remaining amount of feed received is less than a preset reference amount.

Accordingly, the feed management server 400 receives the sensing information from the IoT smart gateway device 300 and feeds the feed for the feed bin 100 matched with the IoT detection unit 200 corresponding to the reference amount or less. You can order.

Next, referring to FIG. 2, the IoT detection unit 200 includes a first control unit 210 that controls an operation function including data sensing of the sensor unit 220 and communication of the sensing data of the first communication unit 230, It may be configured to include a sensor unit 220 for sensing the distance, temperature, and humidity of the feed bin 100 and a first communication unit 230 for transmitting sensing data to the IoT smart gateway device 300.

In addition, the IoT smart gateway device 300 according to an embodiment of the present invention controls operation functions including reception of sensing data from the 2-1 communication unit 320 and transmission of the sensing data from the 2-2 communication unit 330 The second control unit 310 to perform processing, the 2-1 communication unit 320 to receive sensing data from the IoT detection unit 200, and a second to process the received sensing data into sensing information and transmit it to the feed management server 400. It is configured to include a 2-2 communication unit 330.

The first control unit 210 of the IoT detection unit 200 transmits sensing data of the distance, temperature, and humidity detected through the sensor unit 220 to the IoT smart gateway device 300 through the first communication unit 230. It controls the whole operation.

Here, when communication with the IoT smart gateway device 300 is connected, the first control unit 210 controls the sensing data of the sensor unit 220 to be transmitted through the first communication unit 230. If communication between the IoT sensing unit 200 and the IoT smart gateway device 300 is not connected, the data sensed by the sensor unit 220 is temporarily stored in a memory. And when communication is resumed, sensing data stored in the memory is transmitted to the IoT smart gateway device 300. For example, if the memory is EEPROM (ellectrically erasable programmable read only memory), the EEPROM memory is suitable for storing temporary data because it can store data for a long period of time when the power supply is cut off.

The sensor unit 220 includes a laser sensor for distance measurement, a temperature sensor for temperature measurement, and a humidity sensor for humidity measurement, and each sensor senses a corresponding distance, temperature, and humidity. The laser sensor is located on the inner surface of the cover 101 and senses the distance between the sensor and the feed through transmission and reception of a laser signal. The temperature sensor and the humidity sensor respectively sense the temperature and humidity of the inner space of the feed bin 100 to manage the storage and deterioration of feed.

The first communication unit 230 transmits the sensing data sensed by the sensor unit 220 in real time or periodically to the IoT smart gateway device 300 using power line communication. If the IoT detection unit 200 and the IoT smart gateway device 300 are converted from a communication incapable state to a communication enabled state, the first communication unit 230 transmits the sensing data previously stored in the EEPROM memory and then detects the real time. Transmit sensing data.

The second control unit 310 of the IoT smart gateway device 300 controls communication functions of the 2-1 communication unit 320 and the 2-2 communication unit 330. The second control unit 310 converts and processes the received sensing data signal into sensing information of distance, temperature, and humidity.

In an embodiment of the present invention, when the distance between the laser sensor and the surface of the feed is subtracted from the preset height 200 of the feed bin 100, the height of the remaining feed is calculated. The second control unit 310 may query the remaining amount of feed (eg, weight or volume) with respect to the calculated height of feed with reference to the standard table of the feed bin 100. When the remaining amount of feed is obtained in units of weight or volume, whether feed is insufficient and the number of days of feed remaining may be predicted according to the daily feed consumption of the feed bin 100. Of course, order processing of feed may be involved based on predictions.

The 2-1 communication unit 320 receives sensing data including distance, temperature, and humidity transmitted from the IoT sensing unit 200 based on power line communication.

Then, when the second control unit 310 calculates the remaining amount of feed, the 2-2 communication unit 330 transmits the sensing information converted by the second control unit 310 to the feed management server through the wired/wireless network 500. Transfer to 400.

Meanwhile, the feed management unit 410 of the feed management server 400 receives sensing information from the IoT smart gateway device 300, and the IoT smart gateway device 300, IoT detection unit 200, and feed corresponding to the sensing information The information of the bin 100 is matched, the matched sensing information is stored in the sensing information DB 404, and the stored sensing information is managed.

Here, when the sensing information is received, the feed management unit 410 compares a preset reference amount for the feed bin 100 corresponding to the remaining amount of feed in the sensing information, and when the remaining amount of feed is less than the reference amount, the feed is insufficient. It judges that online ordering of feed is required. The feed management unit 410 processes an online order by referring to the feed manufacturer information. In addition, when the settlement date arrives, the feed management unit 410 charges the feed price of the online order to the farm, and calculates the feed order cost from the feed price of the farm to the feed manufacturer.

Meanwhile, the feed management unit 410 includes a livestock farm DB 401, a gateway DB 402, a feed bean DB 403, and a sensing information DB 404 corresponding to a plurality of DBs for management of livestock farms, gateways, and feed. ), feed manufacturer DB 405, feed information DB 406, billing DB 407, and order DB 408.

The feed management unit 410 registers information of livestock farmers registered as a member (such as the terminal number of the mobile device 700) and stores it in the livestock farm DB 401. The feed management unit 410 registers the information of the IoT smart gateway device 300 installed for each livestock farm and stores it in the gateway DB 402. The gateway information is mapped to the terminal number and farmhouse information of the mobile device 700 as 1:1.

The feed management unit 410 registers the information of the feed bean 100 managed by the IoT smart gateway device 300 and the mobile device 700 and stores the information in the feed bean DB 403. The information of the IoT smart gateway device 300/mobile device 700 and the feed bean 100 is mapped to 1:n (n is a natural number of 2 or more).

The feed management unit 410 receives sensing information including information of the IoT smart gateway device 300, the mobile device 700, the IoT detection unit 200, and the feed bean 100, and stores the sensing information in the sensing information DB 404. do. At this time, the information of the IoT detection unit 200 and the feed bin 100 is mapped to 1:1 so that mutual identification is possible.

The feed management unit 410 registers the information of the feed manufacturer and stores it in the feed manufacturer DB 405. The feed manufacturer is mapped to the feed of the feed bin 100 and 1: m (m is a natural number equal to or different from n). The feed management unit 410 registers feed information including livestock type, age, and use of feed sold by feed manufacturers and stores it in feed information DB 406. The feed bin 100 and feed are mapped 1:1. If L (L is a natural number equal to or different from n and m) of two or more products, feed bin 100 and feed are mapped to 1: L. The feed management unit 410 registers the basic or event-applied billing information of the feed manufacturer from the feed manufacturer and stores it in the billing DB 407. The feed management unit 410 determines that the remaining amount of feed is insufficient, generates order information each time an online order is placed, and stores it in the order DB 408.

Meanwhile, referring to FIG. 9, the function providing unit 420 provides a big data collection/analysis module 421, a rental system management module 422, an independent system management module 423, a member company providing module 424 and a customer. A module 425 may be provided.

Big data collection/analysis module 421 includes livestock farm DB 401, gateway DB 402, feed bean DB 403, sensing information DB 404, feed manufacturer DB 405, corresponding to a plurality of DBs. Data collected by the feed information DB 406, the billing DB 407, and the order DB 408 may be classified and provided to the big data server 600 through the network 500 so that the collected data can be refined into statistical data.

Accordingly, the big data server 600 automatically classifies the data collected in the DB of the feed management server 400 according to criteria such as region, date, and livestock type, and the classified data generates statistics to be the basis of the analysis function. It can be used as data, and analysis data can be provided back to the feed management server 400 according to order, delivery, and inventory analysis algorithms, and the network 500 is also provided to customers for which an independent system is established. Through transmission to the mobile device 700 may be provided.

The rental system management module 422 may provide a service authentication function for the analysis data between the big data collection/analysis module 421 and the big data server 600.

In other words, the rental system management module 422 provides a function for obtaining authentication of use of additional services for big data collection and analysis in a company with an independent system, but corresponding to each system administrator so that system authentication can be periodically received. A notification function (SMS, e-mail, etc.) to the mobile device 700 and an authentication function capable of preventing illegal use through system authentication may be provided.

The standalone system management module 423 provides functions necessary for the standalone system to the mobile device 700 through the network 500, but provides an administrator management function, an authority group and menu authority designation management function, schedule management function, and code Can provide management functions.
The above-described "independent system" (member with an independent system, a company with an independent system) managed by such an independent system management module 423 is a dictionary meaning "other computers or time-sharing" in the field of information and communication. Means a microcomputer software development system" (source: NAVER dictionary) executed on a microcomputer that is not connected to the system.
Expanding in this sense, based on the term “operation system” in the information and communication field in a dictionary sense as “independent system that processes information to support or control communication network management functions” (source: NAVER dictionary) , The "independent system" described in the present invention is specifically provided by the rental system management module 422, the independent system management module 423 through the network 500, such as a desktop or notebook PC, tablet PC, smart phone, etc. It should be noted that it is meant to mean a terminal (illustrated by the mobile device 700 of this embodiment) equipped with a "operation system" capable of receiving and processing data for each function.

In addition, the independent system management module 423 has a member authentication function for using analysis data for the mobile device 700 through the network 500, a system authentication function for receiving analysis data transmission, and a manager contact for periodic authentication renewal. Information registration function can be provided.

The member company-provided module 424 provides an automation function for dispatch and schedule to the feed manufacturer terminal through the network 700, but provides a delivery and dispatch automation function based on analysis data, and automatically sets the dispatch schedule. Provides a notification function so that feed manufacturers and customers corresponding to member companies can check the schedule regularly/irregularly, and provides a function to inquire location information in real time using the delivery engineer's mobile phone or PDA, etc. The location information can be converted into and provided information such as maps and addresses that are easy for member companies to recognize.

In addition, the member company providing module 424 provides a feed product inventory management function, provides an information management function for inventory status and delivery/receipt, and may provide statistics and inventory prediction information based on analysis data.

The customer providing module 425 provides a delivery information inquiry function to the mobile device 700 through the network 700, but provides a function to search location information in real time using a mobile phone or PDA of the delivery driver. , The collected location information may be converted into information such as a map, address, and expected arrival time, which are convenient for users to recognize, and provide a function that can be provided.

In addition, the customer providing module 425 provides an inventory information management function to the mobile device 700 through the network 700, but may provide statistics and prediction information based on inventory status and analysis data.

Meanwhile, FIGS. 10 to 13 are views for explaining functions provided by the function providing unit 420 of the feed management server 400 in the feed management order system 1 of FIG. 1.

Hereinafter, functions of the function providing unit 420 will be described in detail with reference to FIGS. 10 to 13. The big data collection/analysis module 421 may provide an analysis function based on collection data (big data) of the residual amount of feed.

First, the big data collection/analysis module 421 performs a method of utilizing big data to increase productivity by improving the feed demand rate, and the feed demand rate (FCR) determines how many kg of feed to supply to increase the weight by 1 kg. It means the ratio to do, and the feed demand rate is calculated by dividing the total amount of feed by the total weight of shipment.

In general, farmers determine the level of productivity by calculating the feed demand rate by calculating the data on the amount of feed received from the farm and the total number of heads and weight shipped from the farm. Based on the same feed amount, the total weight of shipment should be high, but the number of shipments should increase and the weight of shipment should be high. Conversely, if the total weight of shipment is the same, the feed demand rate is improved only when the amount of feed is small.

In order to reduce feed cost, feed demand rate must be improved, and clear target indicators must be set and managed for each livestock farm.

To this end, the big data collection/analysis module 421 may implement a function to provide salary information that is a standard for realizing a low feed demand rate through data collection based on farm households using the smart feed bean service. This is a function that is possible through exemplary case extraction through big data collection and analysis, and the system implements to provide meaningful data to livestock farmers and feed companies through measurement of breeding distribution by age and consumption per day. That is, FIG. 10A shows the daily consumption status screen for each farm, and the farm/daily consumption screen is data showing how much feed supplied to the farm is consumed in the corresponding daily age section, and the consumption by day. To this end, it provides information on the amount of change in feed that is constantly being collected through the IoT measurement unit in the farm.

FIG. 10B simply provides daily consumption data as consumption data for each growth stage, but when the above information is combined with information on the number of animals by age that are currently reared for each farm, it is possible to convert the consumption by each growth stage. The shipping time is different for each farm, but it is necessary to provide information to consider shipping by converting the optimal profit-breaking point.

FIG. 10C is a screen showing the breeding distribution by day and age by farm household, and the distribution by day and age by farm house can be viewed as shown in the pie chart above. As shown in the screen of FIG. 10C, it is possible to measure the feed demand rate by calculating the change in consumption amount for feed per farm per day, and calculating the result (total weight) of the products shipped according to the consumption amount of feed consumed by the farm. If such data is collected and the information can be referred to each other in member farms, it will be possible to enjoy the effect of saving livestock feed and improving productivity.

Next, the big data collection/analysis module 421 may provide a demand prediction management function based on the collected big data.

That is, the big data collection/analysis module 421 analyzes the patterns of feed consumption, such as the above-described breeding distribution for each farm and the daily feed consumption data for each farm, so that the feed company can predict and manage the demand. You can use the big data collected from

The demand of individual farms is based on the amount of feed consumed by the farm with the highest priority, but the average of the consumption of feed collected by other farms can also be used as reference. To make this possible, the demand information of farm households is composed as follows. First of all, it is implemented to predict the arrival date and age of livestock currently raised, the current feed amount and the available feed date for the feed amount, and calculate the expected order date and order amount in advance. This is not only useful information at the farming site, but also from the perspective of the member companies that supply the feed, it provides a lot of help in securing the optimal feed stock so that fresh feed can always be supplied to the silo containing feed at the right time.

Currently, this system is already included in the automatic ordering algorithm that informs the ordering by considering the remaining amount of feed bins and the number of breeding heads at an appropriate time, but the manager or feed company that supplies the service also provides a tool for simulation.

Meanwhile, FIG. 11A shows a feed demand prediction management screen, and the ultimate big data analysis service provided by the system provides the above result, and among the farms, farmers who have achieved the optimum feed demand rate will appear. The daily feed amount until shipment is recorded in the information on the arrival date, number of heads, weight, shipping date, number of shipments, and shipments for each farm household, and the total consumption is automatically summed up at the time of final shipment, and feed consumption per head is provided. Therefore, based on these, the feed demand rate is calculated and information on the feed demand rate is presented at a glance.

11B shows feed demand rate output data, and a farm using this service selects an appropriate model and receives optimal standard daily wage model information through the log of the farm. Although not shown in this report, logs such as feed standard, daily feed amount, temperature and humidity can be provided as back data.

Next, the member company providing module 424 provides an automated method and function of the smart feed bean service, but when a feed order occurs in the farm, the reception is in progress, followed by dispatching and dispatch instruction work. If this part is automated by the member company providing module 424, time, manpower, and cost can be saved. This function is not completely automatic, but a step-by-step automation that can be proceeded through a minimum status determination was implemented so that it can escape the cumbersome work. For dispatching, the existing order receipts were checked and empty tolerance schedules were searched and placed. This part was automated to provide the person in charge of the task with an automatic dispatch proposal rather than a manual inquiry of the delivery vehicle, thereby reducing the difficulty of work. I did.

12A is a dispatch management screen. As shown in FIG. 12A, information on an order received on the left can be checked on the right. The system searches for a delivery schedule based on this information and proposes the most appropriate dispatch target. The criteria are determined based on the preferred delivery schedule and region, and records of frequent delivery of the region or farm in the past.

Figure 12b is a delivery status inquiry screen, as shown in Figure 12b, is a screen implemented so that the current location of the vehicle that has received the delivery instruction can be inquired, and the delivery driver installs an app for inquiry and completion confirmation of the ordered delivery. A function may be implemented so that the current location can be identified through the app.

Meanwhile, the functions of the member company providing module 424 described in FIGS. 12A and 12B may be equally provided to the farming household by the customer providing module 425.

Meanwhile, the function providing unit 420 may provide a smart feed bean app function to the mobile device 700, and FIG. 13A shows a feed bean monitoring screen implemented in the mobile device 700. Referring to FIG. Due to the characteristics of the device 700, rather than selecting a small area and viewing information on a fixed screen, all of the feed bins to be monitored can be displayed on the screen and detailed information can be selected and provided.

13B is a detailed information about the feed bin. Referring to FIG. 13B, a pop-up screen showing detailed information when a feed bin is selected on the screen showing the feed bin type in FIG. 13A. It can be provided by displaying the remaining stock from the amount of feed at the time of buffering, the amount of safety stock that is judged to be necessary to order, the temperature and humidity, and the time the information was updated.

13C is a setting and notification history screen. As shown in FIG. 13C, the GUI screen allows you to set whether or not to push notification and the amount of safety stock in the smart feed bin mobile device 700 app. If there is a need, you can send a push message to confirm the order. Push messages can be searched for details, so even if the message is turned off, you can touch the details to place an order.

13D is an order request screen. As shown in FIG. 13D, an order status inquiry (delivery inquiry) is possible, a list and detailed information about the ordered case can be checked, and the current location by transmitting location information from the app installed to the delivery driver. You can query the distance to the and farm location.

Meanwhile, FIG. 14 is a flowchart illustrating a method of ordering feed management based on a feed management order system for a feed bean using solar energy and building a feed residual range analysis function based on big data collection according to an embodiment of the present invention. Referring to FIG. 14, the photovoltaic device 200a stores photovoltaic energy in the battery 210a through photovoltaic power generation (S11).

After step (S11), the IoT detection unit 200 and the IoT smart gateway device 300 are basically using AC power, which is the constant power, and if the AC power, which is the constant power, is short-circuited, stored as an emergency power solar power generation. The battery 210a uses power (DC power) (S12).

After step (S12), each IoT detection unit 200 collects sensing data including distance data using a laser sensor (S13). More specifically, according to an embodiment of the present invention, the IoT sensing unit 200 checks that the measurement period has arrived through a timer. When the measurement period arrives, the IoT sensing unit 200 installed on the inner surface of the top cover 101 of the feed bin 100 measures each sensing data using a racer sensor, a temperature sensor, and a humidity sensor. The laser sensor senses the surface distance between the sensor and the feed using a laser. The temperature sensor and the humidity sensor sense the temperature and humidity of the inner space of the feed bin 100.

After step S13, each IoT sensing unit 200 transmits sensing data to the IoT smart gateway device 300 (S14). When the sensing data is measured, the IoT detection unit 200 determines a communication connection state of the IoT smart gateway device 300. If the communication state is wirelessly connected, it is determined as an abnormal state, and the measured sensing data is temporarily stored in the EEPROM memory and transmitted to the IoT smart gateway device 300, but after the transmission, the data in the EEPROM memory is not affected by power supply problems. It is not deleted to prevent transmission errors.

If it is determined that the communication is connected by wire and is in a normal state, the IoT sensing unit 200 transmits sensing data to the IoT smart gateway device 300. When the transmission is complete, the IoT sensing unit 200 deletes the temporary data stored in the EEPROM.

After step (S14), the IoT smart gateway device 300 calculates the remaining amount of feed using the sensing data (S15). More specifically, the IoT smart gateway device 300 receives sensing data transmitted from the IoT sensing unit 200 using power line communication, and then calculates the remaining amount of feed. The IoT smart gateway device 300 may convert the received signal data of temperature and humidity into corresponding sensing information.

After step (S16), the IoT smart gateway device 300 transmits the sensing data to the feed management server 400 and requests feed order and feed price settlement (S16).

That is, the IoT smart gateway device 300 transmits the sensing data to the feed management server 400, but after the sensing data is collected by the feed management server 400, the mobile device 700 corresponding to the farmhouse terminal for monitoring Monitoring information is provided through the screen UI at the request of Furthermore, the IoT smart gateway device 300 may notify the farm terminal of a corresponding alarm when there is a concern about deterioration or contamination due to changes in temperature and humidity.

Meanwhile, the feed management server 400 receives sensing data from the IoT smart gateway device 300. The feed management server 400 extracts information of the IoT smart gateway device 300 and the IoT detection unit 200 and the remaining amount/distance/humidity of feed from the received sensing data, and matches the extracted information to match the sensing information DB ( 404).

If the feed management server 400 is less than the reference amount set in the corresponding feed bin 100, the feed management server 400 predicts the shortage of feed and determines the target of the online order. The feed management server 400 orders feed online. Thereafter, when the payment settlement time arrives, the paid farmer's feed order cost is settled to the feed manufacturer. Here, for the processing of livestock farmers, gateways, feed bins, sensing information, feed manufacturers, feed, billing, online order, settlement, etc., the feed management server 400 registers information in the DBs 401-408 of FIG. 2 And manage the registered information.

After step S16, the feed management server 400 provides big data-based information to the mobile device 700 through the network 500 in the manner described above in FIGS. 9 to 13 (S17).

The present invention can also be implemented as a computer-readable code on a computer-readable recording medium. The computer-readable recording medium includes all types of recording devices that store data that can be read by a computer system.

Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disk, and optical data storage devices, and are implemented in the form of carrier waves (for example, transmission through the Internet). Also includes.

In addition, the computer-readable recording medium is distributed over a computer system connected through a network, so that computer-readable codes can be stored and executed in a distributed manner. In addition, functional programs, codes, and code segments for implementing the present invention can be easily inferred by programmers in the technical field to which the present invention belongs.

As described above, in the present specification and drawings, a preferred embodiment of the present invention has been disclosed, and although specific terms are used, this is only used in a general meaning to easily explain the technical content of the present invention and to aid understanding of the invention. , It is not intended to limit the scope of the present invention. In addition to the embodiments disclosed herein, it is apparent to those of ordinary skill in the art that other modified examples based on the technical idea of the present invention may be implemented.

1: Establishment of analysis function for feed residual content based on big data collection and feed management order system for feed beans powered by solar energy
100: feed bin
200: IoT detection unit
200a: photovoltaic device
300: IoT smart gateway device
400: feed management server
500: network
600: Big data server
700: mobile device

Claims (7)

Feed management including a plurality of feed bins 100, an IoT detection unit 200 formed in each feed bin 100, a photovoltaic device 200a, an IoT smart gateway device 300, and a feed management server 400 In the ordering system,
The photovoltaic device 200a stores photovoltaic energy in the battery 210a through photovoltaic power generation, and the IoT detection unit 200 and IoT smart corresponding to the constant power supply combined feed bin remaining amount and internal environment monitoring IoT Unit Supplying solar energy generated as emergency power to the gateway device 300,
The feed management unit 410 of the feed management server 400,
Receiving sensing information from the IoT smart gateway device 300, matching the information of the IoT smart gateway device 300, the IoT sensing unit 200, and the feed bin 100 corresponding to the sensing information, and matching the sensing information The sensing information is stored in the sensing information DB 404, and the stored sensing information is managed, but when the sensing information is received, the residual amount of feed in the sensing information and a preset reference amount for the corresponding feed bin 100 are compared, and the residual amount of feed is the reference amount. If it is less than that, it is judged that the feed is insufficient and an online order of feed is required, and the online order is ordered by referring to the feed manufacturer information, and when the settlement date arrives, the farm is charged for the feed for the online order. And, the feed order cost is settled to the feed manufacturer from the feed price of the farm, and livestock farm DB 401, gateway DB 402, and feed bean DB corresponding to a plurality of DBs for the management of livestock farms, gateway and feed 403), sensing information DB 404, feed manufacturer DB 405, feed information DB 406, billing DB 407, and order DB 408 are managed, and information of livestock farms registered as members (mobile device ( 700) is registered and stored in the livestock farm DB 401, and the feed management unit 410 registers the information of the IoT smart gateway device 300 installed for each livestock farm and registers the information in the gateway DB 402. Upon storage, the gateway information is mapped to the terminal number and farmhouse information of the mobile device 700 as 1:1, and the information of the feed bean 100 managed by the IoT smart gateway device 300 and the mobile device 700 is registered. When stored in the feed bin DB 403, the information of the IoT smart gateway device 300 / mobile device 700 and the feed bin 100 is mapped to 1: n (n is a natural number of 2 or more),
When receiving sensing information including information of the IoT smart gateway device 300, mobile device 700, IoT sensing unit 200, and feed bean 100 and storing it in the sensing information DB 404, the IoT sensing unit ( 200) and the information of the feed bin 100 are mapped to 1:1 so that mutual identification is possible.When the information of the feed manufacturer is registered and stored in the feed manufacturer DB 405, the feed manufacturer Feed and 1: m (m is a natural number equal to or different from n) of 2 or more,
When feed information including livestock type, age, and use of feed sold by feed manufacturers is registered and stored in feed information DB 406, feed bin 100 and feed are mapped to 1:1, but L (L is n , In the case of a mixed feed of two or more products equal to or different from m) feed bin 100 and feed are mapped to 1: L, and the feed manufacturer's basic or event-applied billing information is registered from the feed manufacturer and billing DB ( 407), it is determined that the remaining amount of feed is insufficient, and order information is generated each time an online order is placed and stored in the order DB 408,
Feed management server 400 further includes a function providing unit 420,
The function providing unit 420 includes a big data collection/analysis module 421, a rental system management module 422, an independent system management module 423, a member company providing module 424 and a customer providing module 425,
Big data collection/analysis module 421 includes livestock farm DB 401, gateway DB 402, feed bean DB 403, sensing information DB 404, feed manufacturer DB 405, corresponding to a plurality of DBs. By providing the data collected by feed information DB 406, billing DB 407, and order DB 408 to the big data server 600 through the network 500 so that the collected data can be classified and refined into statistical data, The data collected in the DB of the feed management server 400 by the server 600 are automatically classified according to at least one of the criteria of region, date, and livestock type, and statistics are generated for the classified data to be the basis of the analysis function. It allows it to be used as data, and provides analysis data according to order, delivery, and inventory analysis algorithms back to the feed management server 400,
The rental system management module 422,
Provides a service authentication function for the analysis data between the big data collection/analysis module 421 and the big data server 600, but provides additional services for big data collection and analysis by operating data provided through the network. By providing a function to obtain authentication for use in a company that has an independent system built to enable the system to be authenticated periodically, a notification to the mobile device 700 corresponding to each system administrator (using either SMS or e-mail) ) Function and authentication function that can prevent illegal use through system authentication,
The standalone system management module 423,
The functions required for the stand-alone system are provided to the mobile device 700 through the network 500, but not only provide an administrator management function, provide an authority group and menu authority designation management function, provide a schedule management function, and provide a code management function. , Provides a member authentication function for the use of analysis data for the mobile device 700 through the network 500, a system authentication function for receiving analysis data transmission, and an administrator contact information registration function for periodic authentication renewal,
The member company providing module 424,
Provides an automation function for dispatch and schedule to the feed manufacturer terminal through the network 700, but provides a delivery and dispatch automation function based on analysis data, and automatically sets the dispatch schedule with the feed manufacturer corresponding to the member company. It provides a notification function so that customers can check the schedule regularly/irregularly, and provides a function to inquire location information in real time using the delivery driver's mobile phone or PDA, and the collected location information is not recognized by member companies. It provides not only maps and address information to be converted into information, but also provides feed product inventory management functions, provides information management functions for inventory status and delivery/receipt, and statistics and inventory prediction based on analysis data Provide information,
The customer-supplied module 425,
Provides a delivery information inquiry function to the mobile device 700 through the network 700, but provides a function to search location information in real time using the delivery driver's mobile phone or PDA, and the collected location information is provided by the user. Provides a function that can be converted into map, address, and estimated arrival time information for recognition, and provides inventory information management function to the mobile device 700 through the network 700, but inventory status and analysis Provides statistics and prediction information based on data,
The feed bin 100,
A feed storage tank that stores feed for livestock in a farmhouse. Individual farms have at least one feed bin 100 according to the number of livestock, and an inlet corresponding to the top cover 101 is provided. Feed is injected through, and feed is stored inside, and a feed outlet is formed at the bottom of the feed bin 100,
IoT detection unit 200,
It is installed on the inner side of the cover 101 to measure the distance between the IoT sensing unit 200 and the feed inside the feed bin 100, but the laser sensor is used to measure the amount of feed inside the feed bin 100. It is attached to the center of the inside of the feed bin and measures the position value (distance) while rotating the sensor at the center of the feed bin and calculates the remaining amount (%) through the feed surface scanning method. By measuring the temperature and humidity of the feed space inside the feed bin 100, as well as having a servo motor for rotating the laser sensor and performing the calculation through, the remaining feed amount (distance) and the storage environment (temperature and Humidity), and transmits the sensed data through power line communication (PLC) or wired and wireless communication, and in the case of power line communication, the transmitter IoT detection unit 200 and the receiver IoT smart gateway Each of the devices 300 is equipped with a PLC modem for power line communication, so that sensing data is transmitted to the IoT smart gateway device 300 as an electrical signal. In the case of wired and wireless communication, the IoT sensing unit 200 becomes an IoT device Transmits sensing data to the IoT smart gateway device 300 through communication,
IoT smart gateway device 300,
A computer device that is installed for each individual farm and receives sensing data from the IoT sensing unit 200, and receives sensing data transmitted by at least one IoT sensing unit 200 from the farm, and feeds the distance data of the received sensing data. It calculates as the remaining amount, converts the signal of the received sensing data into information of temperature and humidity, and transmits the remaining amount of feed, temperature and humidity as sensing information to the feed management server 400,
The data communication protocol between the IoT detection unit 200 and the IoT smart gateway device 300 is not divided into wired communication (PLC) or wireless communication (Zigbee), but is used in combination, but the protocol needs to be changed according to the communication method. In order to avoid confusion in the transmission/reception method by using one protocol without the need for communication, wired communication is designed to use AC power, which is basically always power, by providing the 2-1 communication unit 320 as a PLC/Zigbee communication conversion module. It is applied to use (PLC), but when AC power, which is the constant power, is short-circuited, wired communication (PLC) cannot be used, so the second control unit 310 automatically converts to wireless communication (Zigbee), and Wired & Wireless (Wi-Fi) Embedded System, so that communication with the feed management server 400 and big data server 600 corresponding to the SCM Cloud Server can be used as both Wired (Ethernet) & Wireless (Wi-Fi). , By applying the Android platform, first check whether wired communication (Ethernet) is possible with the feed management server 400 and the big data server 600 through the network 400, and if wired communication (Ethernet) is not possible, wireless communication ( Wi-Fi) is implemented and applied so that it is automatically converted into a feed bin analysis function based on big data collection, and feed management order system for feed beans powered by solar energy.
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