KR102515565B1 - Smart farm environment control applying power noise reduction technology of sensor board - Google Patents

Abstract

The smart farm complex environment control system provides manual cultivation data by a preset pool of experts, and from the point when learning data over a predetermined range is accumulated, a remote cultivation consulting system that provides automatic cultivation data based on the learning data, and temperature An automated control system comprising a sensor board including a sensor and a humidity sensor and controlling a growth environment of plants based on the passive cultivation data and the automatic cultivation data, wherein the sensor board includes a decoupling capacitor connected to an internal circuit. It is characterized in that it includes a power supply noise processing unit that is connected and reduces resonance noise caused by the power supply while the resistance value is varied.

Description

Smart farm environment control system with reduced power noise of sensor board {Smart farm environment control applying power noise reduction technology of sensor board}

The present invention relates to a smart farm complex environment control system, and more particularly, to a smart farm complex environment control system in which power supply noise of a sensor board is reduced.

Agriculture-related industries are weakening due to the decrease in domestic farm households and farm household population, stagnant farm household income, and decrease in production due to climate change, and there is a need to promote technology development to strengthen agricultural technology competitiveness.

According to data from the National Statistical Office, the number of farm households in 2019 is only 5.3% of the total number of households, and the farm population is also about 2.42 million, or 4.7%. The farming household aging rate (the proportion of the population aged 65 or older) was 42.3% as of 2019, a 10.7% increase from 2010.

In order to stably secure agricultural production in this reality, many projects are underway to build a smart farm by converging information and communication technology.

Korean Patent Publication No. 10-2011-0111073 “Automated management system for managing crops according to the crop growth cycle” can establish complete automation for the entire growth cycle of crops, that is, the entire process from sowing to harvesting. In addition, it suggests that crops can be efficiently managed and that the manager's convenience can be promoted.

However, systems related to conventional smart farms, such as Korean Patent Publication No. 10-2011-0111073, simply use data collected mainly on environmental data such as temperature, humidity, illuminance, oxygen, and carbon dioxide information to automatically We are staying to support cultivation.

That is, the conventional smart farm system has the disadvantage of not generating information necessary for decision-making to increase production and improve quality.

On the other hand, the smart farm complex environment control system is equipped with various sensors to check the growth environment of plants. That is, a sensor board for measuring a temperature sensor, a humidity sensor, a carbon dioxide sensor, an illuminance sensor, and an oxygen sensor is provided.

Since the sensor board may be exposed to the external environment, noise is expected to occur. If distortion of the clock signal, control signal, power supply, etc. occurs, it may affect the life and reliability of the sensor board, preventing and eliminating signal noise. Noise prevention technology that can reduce or reduce noise must be applied.

KR 10-2011-0111073 A

The present invention is proposed to solve the above technical problem, and provides a smart farm complex environment control system equipped with a sensor board that is connected to a decoupling capacitor and reduces resonance noise caused by power while the resistance value is varied.

According to an embodiment of the present invention for solving the above problem, while providing manual cultivation data by a preset expert pool, automatic cultivation data based on the learning data is provided from the point when learning data over a predetermined range is accumulated. An automated control system comprising a remote cultivation consulting system, a sensor board including a temperature sensor and a humidity sensor, and controlling the growth environment of plants based on the manual cultivation data and the automatic cultivation data, the sensor board, A smart farm complex environment control system is provided, characterized in that it is connected to a decoupling capacitor connected to the internal circuitry and has a power supply noise processing unit that reduces resonance noise caused by power while the resistance value is varied.

In addition, the power noise processing unit included in the present invention includes the internal circuit part receiving the power voltage and the ground voltage, the decoupling capacitor having one end connected to the input part of the power voltage of the internal circuit part, and the other end of the decoupling capacitor and the ground. It is connected between voltage inputs and corresponds to the power voltage or ground voltage supplied to the internal circuitry so that the voltage level difference between the power supply voltage or ground power supply and the power supply voltage or ground power input to the internal circuitry unit is minimized. It is characterized in that it includes; a variable resistance unit in which a resistance value for reducing resonance noise is varied.

In addition, the variable resistance unit included in the present invention is characterized in that it includes a plurality of resistance elements connected in parallel and a switching element for selecting the plurality of resistance elements.

In addition, the plurality of resistance elements included in the present invention include a plurality of NMOS transistors having a drain terminal connected to the decoupling capacitor and a source terminal connected to the ground line, a drain terminal connected to the decoupling capacitor, and a source terminal connected to the decoupling capacitor. It is characterized in that it comprises an NMOS transistor connected to the ground line and to which a power supply voltage is applied to a gate terminal.

In addition, the present invention further includes a growth analysis system that monitors the growth state of plants and provides monitoring data to at least one or more of a remote cultivation consulting system and an automated control system.

The smart farm complex environment control system according to an embodiment of the present invention is connected to a decoupling capacitor and is provided with a sensor board that reduces resonance noise caused by power while the resistance value is varied.

In addition, the sensor board may protect the internal circuit by discharging static electricity to the outside through the internal circuit protection unit.

In addition, the smart farm complex environment control system can provide automatic cultivation data based on the learning data from the point when learning data over a predetermined range is accumulated while providing manual cultivation data by a preset expert pool.

Therefore, it has the advantage of being able to automate the information necessary for decision-making to increase production and improve quality based on accumulated learning data.

That is, at first, manual cultivation data by a pool of experts is provided, and the growth status of plants is monitored while controlling the growth environment of plants, and then learning data is continuously accumulated by feeding back the monitoring results.

After sufficient learning data is accumulated, artificial intelligence (AI) based automatic cultivation data is provided based on the learning data, so that the growth conditions of the plant can be automatically adjusted even if climate or environmental changes occur. Ultimately, it is possible to provide a solution that can automatically make cultivation decisions through the smart farm complex environment control system.

1 is a conceptual diagram of a smart farm complex environment control system 1 according to an embodiment of the present invention
Figure 2 is a more detailed configuration of the smart farm complex environment control system (1)
3 is a configuration diagram of a sensor board included in the automation control system 200
4 is a circuit diagram of a power noise processor 42 included in the sensor board
5 is a first embodiment of the attenuator of the power noise processing unit 42
6 is a second embodiment of the attenuator of the power noise processing unit 42
7 is a configuration diagram of an internal protection unit 41 included in the sensor board
8 is a schematic configuration diagram of the internal circuit protection unit 16
9 is a circuit diagram of the internal circuit protection unit 16
10 is a conceptual diagram of a remote cultivation consulting system 100
11 is a diagram showing an example of an environment analysis process considering fluid dynamics
12 is a view showing a growth measurement method using an image
13 is a view showing an example of a growth measurement process using an image
14 is a view showing a method of measuring plant growth and stress with acquired video images;

Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings in order to describe in detail enough for those skilled in the art to easily implement the technical idea of the present invention.

1 is a conceptual diagram of a smart farm complex environment control system 1 according to an embodiment of the present invention, and FIG. 2 is a more detailed configuration diagram of the smart farm complex environment control system 1.

The smart farm complex environment control system 1 according to this embodiment includes only a brief configuration for clearly explaining the technical idea to be proposed.

1 and 2, the smart farm complex environment control system 1 is configured to include a remote cultivation consulting system 100, an automated control system 200, and a growth analysis system 300.

Looking at the main operations of the smart farm complex environment control system 1 configured as described above are as follows.

The smart farm complex environment control system (1) according to the present invention secures international technological competitiveness for agriculture, escapes from a simple cultivation environment, and provides a solution that can automatically make cultivation decisions by consulting cultivation to farmers.

The smart farm complex environment control system (1) can contribute to improving productivity by accumulating big data of the growing environment and utilizing it, rather than simply managing the farm from a distance.

The smart farm complex environment control system (1) includes a remote cultivation consulting system (100) using artificial intelligence (AI) technology and a pool of agricultural experts, an automation control system (200) for environmental control in farms, and a growth analysis system. (300) can be divided into three parts.

The remote cultivation consulting system 100 is a system capable of online/offline consulting on changes in the environment and cultivated crops due to climate change. Through a pool of agricultural experts consisting of retired agricultural experts and regional agricultural masters, data collected offline is supervised learning and analyzed, and O2O remote cultivation consulting platform and electronic manual-based plant production ERP are supported.

It is an ERP that manages plant production and a cultivation consulting module that analyzes the measured growth environment. This module includes growth analysis that measures the growth size and growth stress captured by a camera. In addition, a dashboard that performs cultivation environment and control in real time and a rule engine for complex control are applied.

Initially, context awareness is performed by a pool of experts to learn measurement data into machine learning.

That is, the remote cultivation consulting system 100 provides automatic cultivation data based on the learning data from the time when learning data over a predetermined range is accumulated while providing manual cultivation data by a preset pool of experts.

All hardware and software of the automation control system 200 are developed on a standard protocol and open basis, and are developed in a form that can be installed and maintained directly in a farmhouse. The automated control system 200 is preferably configured to use a complex environment control operation without changing a program using a rule-based engine. That is, the automation control system 200 manages events and operations occurring in sensing, work, and the like as rules.

The automated control system 200 controls the growth environment of plants based on manual cultivation data and automatic cultivation data, and a dashboard system for real-time plant production and growth analysis is applied.

In other words, an intuitive graphic-based dashboard that can be easily operated by farmers is applied, and real-time ERP, production process and work monitoring systems are applied. In addition, HTML 5 based web & mobile integrated UI management is applied.

In addition, the automation control system 200 is provided with a sensor board (sensor module) for measuring a temperature sensor, a humidity sensor, a carbon dioxide sensor, an illuminance sensor, and an oxygen sensor.

The sensor board is a part that collects physical signals by directly/indirectly contacting the actual measurement target, and is directly exposed to the outside, and is therefore the part that is most affected by the outside.

The sensor board consists of a sensor in charge of actual measurement, a mechanism (case or bracket) to minimize the influence of external noise (shock, inflow of foreign matter, etc.) and various cables as a set. The most important part is the structural design that can minimize the external influence along with the formation of the optimal measurement conditions for this purpose.

Therefore, the present invention proposes a technique for reducing noise and protecting the inside of the sensor board applied to the smart farm complex environment control system. A detailed description thereof will be described later.

The growth analysis system 300 measures the shape and growth state of plants in a cultivation facility without affecting the plants.

The growth analysis system 300 includes a vision device for measuring growth non-destructively and without stress, and measures plant shape and growth stress. The growth analysis system 300 monitors the growth state of plants and provides monitoring data to at least one of a remote cultivation consulting system and an automated control system.

The growth analysis system 300 uses a standard protocol for smart farm control, and a standard interface for sensors and control is applied.

In particular, a plurality of camera modules for obtaining plant images (Viable, NIR, IR) may be provided. That is, a plant image may be photographed and analyzed using a camera for capturing a visible ray region, a camera for capturing a near-infrared region, and a camera for capturing a long-wave infrared region.

3 is a configuration diagram of a sensor board included in the automation control system 200.

The sensor board is defined as a board for measuring the temperature sensor, humidity sensor, carbon dioxide sensor, illuminance sensor, and oxygen sensor. In the embodiment of FIG. 3 , a board equipped with only a temperature sensor and a humidity sensor is shown.

That is, the sensor board includes a temperature sensor, a humidity sensor, a power supply unit, an internal protection unit 41 and a power noise processing unit 42.

Since the sensor board may be exposed to the external environment, noise is expected to occur. If distortion of the clock signal, control signal, power supply, etc. occurs, it may affect the life and reliability of the sensor board, preventing and eliminating signal noise. Noise prevention technology that can reduce or reduce noise must be applied.

For reference, as an example of a temperature sensor, the temperature sensor may include a voltage generator and a temperature code output unit.

The voltage generator includes a first temperature element having a predetermined first resistance value and a second temperature element having a second resistance value, and the voltage level is changed according to the temperature change by the first and second temperature elements. generate a corresponding voltage. In addition, the voltage generator generates a reference voltage that maintains a constant voltage level according to the driving voltage level even when a temperature change occurs.

In addition, the temperature code output unit generates a plurality of temperature codes by comparing the reference voltage and the temperature corresponding voltage. That is, the temperature code includes temperature information.

As another example of the temperature sensor, the temperature sensor may include a reference voltage output unit, a digital-to-analog converter, a comparator, a digital signal generator, a storage unit, and a data output unit.

The reference voltage output unit generates a reference voltage that changes in response to temperature.

The digital-to-analog conversion unit converts an N (integer greater than 1) bit digital signal into an analog sensing voltage and outputs it.

The comparator compares the reference voltage with the analog sensing voltage and outputs a comparison result.

The digital signal generator varies the digital signal according to the comparison result of the comparator, and the storage unit stores the output signal of the digital signal generator at the first temperature.

The data output unit outputs data corresponding to the second temperature according to the output signal of the digital signal generator and the output signal of the first storage unit at the second temperature.

That is, the proposed sensor board includes a power noise processor 42 . The power source noise processing unit 42 is connected to the decoupling capacitor and serves to reduce resonant noise caused by the power source while changing the resistance value.

4 is a circuit diagram of the power supply noise processor 42 included in the sensor board.

Referring to FIG. 4, the power noise processing unit 42 is a power supply voltage supply pad electrically connected to the internal circuit unit to supply a power voltage to the circuit unit through the power supply (VDD) line and the ground (VSS) line. A decoupling capacitor (Cde-cap) connected in parallel with the internal circuitry to the VDD Pad) and the ground voltage supply pad (VSS Pad) and connected to the power supply (VDD) line connecting the internal circuitry and the power supply voltage supply pad (VDD Pad). and a variable resistor (R).

For reference, the internal circuitry refers to all elements included in the sensor board, but in this embodiment, it is assumed that the memory is greatly affected by power supply noise.

Since the voltage value at the location where the internal circuit part is located can be expressed as the product of the impedance value at the same location and the operating current consumed by the circuit, if the current consumed by the circuit is fixed, the range of voltage fluctuation is proportional to the size of the impedance value. And, as the value of the parasitic resistance (Rde-cap) of the decoupling capacitor (Cde-cap) increases, the impedance value at resonance decreases.

This result is a phenomenon that occurs because the larger the value of the parasitic resistance (Rde-cap), the greater the loss in resonance. Similar results can be obtained even when the value of the metal resistance (Rdie) is large, but when the value of the metal resistance (Rdie) increases, This is undesirable because the voltage drop caused by the DC current becomes large.

Therefore, in the present invention, by connecting the series variable resistance unit (R) to the decoupling capacitor (Cde-cap), the impedance value at resonance is increased as in the case when the value of the parasitic resistance (Rde-cap) of the decoupling capacitor (Cde-cap) increases. reduced, limiting the voltage drop due to resonance.

The variable resistance part (R) connects the decoupling capacitor (Cde-cap) and the ground (VSS) line, and minimizes the level difference between the power supplied to the power voltage supply pad (VDD Pad) and the power entering the internal circuitry. It is configured to be used by varying the resistance value.

5 is a first embodiment of the attenuator 421 of the power source noise processor 42, and FIG. 6 is a second embodiment of the attenuator of the power noise processor 42.

Referring to FIGS. 5 and 6, first, FIG. 5 is implemented with a plurality of resistance elements R1 to R4 each connected in series with a decoupling capacitor (Cde-cap) and having a fixed resistance value, through switch on/off. A resistance value of the variable resistance unit R may be varied. At this time, it is preferable to use resistance elements R1 to R4 having different resistance values so that a resistance element capable of minimizing a voltage drop can be selected.

Next, in FIG. 6 , a plurality of NMOS transistors T1 to T4 are connected to the decoupling capacitor Cde-cap, and an external variable resistor control logic 10 is connected to the gates of the plurality of NMOS transistors T1 to T3. It is a structure in which each transistor is turned on/off according to the level of the on/off control signals a1, a2, and a3 by inputting the on/off control signals a1, a2, and a3 output therefrom.

At this time, when the levels of the on/off control signals a1, a2, and a3 are all low, the connection between the decoupling capacitor Cde-cap and the ground line is disconnected, so that the gate of the last NMOS transistor T4 is powered voltage was applied.

Meanwhile, the resistance adjusting unit 10 generates on/off control signals a1, a2, and a3 for turning on or off the respective transistors T1, T2, and T3 connected to the decoupling capacitor Cde-cap. As the output logic, it is enabled by the command signal COMMAND from the outside during the training process to output a combination of logic levels that each control signal a1, a2, and a3 can have, and select a combination with the smallest noise. and the control signals a1, a2, and a3 of the selected combination are input to the gates of the transistors T1, T2, and T3.

Therefore, when the metal resistance value is reduced through the power noise processing device 42 and the resonance problem becomes an issue, the power noise caused by the resonance can be attenuated, and accordingly, the driving power of the low-voltage high-speed operation memory can be stably processed. can

In addition, as another embodiment of the variable resistance unit, a switching variable resistance means having a switching operation and functions as a variable resistance element may be used. That is, the switching variable resistor unit may include an output pulse generator for generating a variable amplitude output pulse according to a control signal, and a variable resistor for receiving the variable amplitude output pulse and performing a switching operation and changing a resistance value.

In addition, as another embodiment of the variable resistance unit, when a plurality of resistance segments are included inside the variable resistance unit and a plurality of resistance value candidates that the variable resistance unit may have are arranged in order of size, the plurality of resistance value candidates have the same ratio. It can be configured to form a geometric sequence. That is, the variable resistance unit is composed of a plurality of resistance segments and a plurality of switches connected to the plurality of resistance segments, and the plurality of switches operate on the plurality of resistance segments by each bit or a combination of each bit of the N-bit control signal. A connection state is controlled, and a resistance value of the variable resistance unit may be determined according to an exponential function based on an N-bit control signal. Therefore, it is easy for the user to intuitively grasp the result of the resistance value change through the control code.

In addition, the sensor board includes an internal protection unit 41, and the sensor board can protect the internal circuit by discharging static electricity or unintended high voltage/current components to the outside through the internal circuit protection unit 41.

7 is a configuration diagram of the inner protection unit 41 in the sensor board.

Referring to FIG. 7 , the internal protection unit 41 according to an embodiment of the present invention protects the high voltage generator 12, the power-up signal control unit 14, the power-down mode signal control unit 18 and the internal circuit. It includes part 16.

The high voltage generator 12 generates the high voltage HVDD by pumping the driving voltage VDD applied from the outside, and provides the generated high voltage to the internal circuit protection unit 16 . In this case, the high voltage generator 12 may prevent malfunction of the internal circuit by generating the highest high voltage that can be generated in the internal circuit.

The power-up signal control unit 14 generates a power-up signal (Powerup) by detecting that the potential of the power supply voltage is higher than a predetermined potential in response to the driving voltage (VDD) applied from the outside.

In addition, the power-up signal control unit 14 delays the high level section of the generated power-up signal (Powerup) for a predetermined time to generate a power-up delay signal (PWRUP_DLY), and internally transmits the generated power-up delay signal (PWRUP_DLY). It is provided to the circuit protection unit 16.

The power down (Deep Power Down: hereinafter referred to as PWRDN) mode signal control unit 18 controls the CAS (applied from the outside) to deactivate unnecessary internal circuits to reduce power consumption in a standby state in which the sensor board is not operating. A deep power down signal (PWRDN, hereinafter referred to as a power down mode signal) is generated in response to a command generated by a combination of command signals such as column access strobe (RAS) and row access strobe (RAS).

The power-down mode signal control unit 18 delays the high-level section of the generated power-down mode signal PWRDN for a predetermined time to generate the power-down mode delay signal PWRDN_Delay.

As such, the present invention can delay the high level period of the power-up signal and the power-down mode signal PWRDN for a predetermined time. In this case, when the sensor board is initialized, the external driving voltage and the high voltage are gradually increased from the 0 level to the preset level. However, since the power-up signal and the deep power signal are activated even before the high voltage reaches a predetermined level, leakage current of the transistors is generated, and thus the sensor board malfunctions. Therefore, according to the present invention, leakage current of transistors can be prevented by delaying the active time of each signal until the high voltage reaches a preset level.

Meanwhile, the internal circuit protection unit 16 includes the power-up delay signal PWRUP_DLY applied from the power-up signal controller 14 based on the high voltage input from the high voltage generator 12, and the power-down mode signal controller ( 18) receives the power-down mode signal (PWRDN) and the power-down mode delay signal (PWRDN_Delay) applied from, and prevents overcurrent from flowing into the internal circuit.

8 is a configuration diagram of the internal circuit protection unit 16, and FIG. 9 is a circuit diagram of the internal circuit protection unit 16.

Referring to FIGS. 8 and 9 , the internal circuit protection unit 16 includes a level shifting unit 16_2 and an electrostatic discharge prevention unit 16_4.

The level shifting unit 16_2 shifts the level of the power-down mode signal PWRDN applied from the power-down mode signal adjusting unit 18 to the high voltage level in response to the high voltage applied from the high voltage generator 12 (Shift). let it

At this time, the level shifting unit 16_2 shifts the level of the power-down mode signal PWRDN to a high voltage level to flow the highest current that can flow in the internal circuit, thereby reducing the first PMOS of the static electricity prevention unit 16_4. Leakage current in the transistor T5 can be prevented, and malfunction of the internal circuit can be prevented by lowering the level of the driving voltage VDD.

The static electricity prevention unit 16_4 prevents overcurrent from flowing into an internal circuit in response to a combination signal of the power-up delay signal PWRUP_DLY and the power-down mode delay signal PWRDN_Delay.

As such, the internal protection unit 41 according to the present invention generates the highest voltage that can be generated inside to shift the level of the power-down mode signal PWRDN to the high voltage level, and the shifted high voltage level and the power supply voltage Malfunction of the internal circuit can be prevented by comparing the level of and discharging the overcurrent to the outside.

The level shifting unit 16_2 includes an inverted level of the power-down mode signal PWRDN, first and second input transistors T3 and T4 receiving the power-down mode signal PWRDN as inputs, and a mirror transistor supplying a high voltage. (T1, T2).

At this time, the level shifting unit 16_2 inverts the level of the power-down mode signal PWRDN and applies the first inverter unit IV1 to the first input transistor T3, and the power-down mode signal PWRDN to the second input transistor. A second inverter unit IV2 applying the voltage to the input transistor T4 is further included.

The static electricity prevention unit 16_4 prevents destruction of the internal circuit by controlling the amount of current applied to the internal circuit.

The static electricity prevention unit 16_4 includes a combination unit NOR1 generating a combination signal by combining the power-up delay signal PWRUP_DLY and the power-down mode delay signal PWRDN_Delay, and a power supply voltage terminal VDD and a ground voltage terminal. A first PMOS transistor T5 connected between VSS and having as an input the output signal of the level shifting unit 16_2, and a second PMOS transistor having as an input the inverted level of the combination signal output from the combination unit NOR1 ( T6), and a first NMOS transistor T7 receiving the combination signal as an input.

Hereinafter, an operation of the internal circuit protection unit 16 according to the present embodiment will be described.

First, as an example, a case in which the internal circuit protection unit 16 of the sensor board performs an initialization operation will be described.

The level shifter 16_2 receives the power-down mode signal PWRDN and the high voltage H_VDD from the power-down mode signal controller 18 and the high voltage generator 12, respectively.

At this time, since the high voltage (H_VDD) and the driving voltage (VDD) do not reach the predetermined level, the overcurrent is not introduced and the internal circuit protection unit 16 does not operate.

Therefore, the output signal of the level shifter 16_2 continues to float, and the second PMOS transistor T6 and the first NMOS transistor T7 of the static electricity prevention unit 16_4 do not operate.

Meanwhile, when the sensor board is initialized, the external driving voltage and the high voltage applied to the level shifting unit 16_2 gradually increase from 0 level to a preset level. Conventionally, when the power-up signal and the deep power signal are activated even before the high voltage reaches a predetermined level, leakage current of the transistors is generated, and thus the sensor board malfunctions. Accordingly, the present invention delays the activation time of the power-up signal and the power-down mode signal PWRDN until the high voltage reaches a preset level and applies the anti-static unit 16_4 to prevent leakage current of the transistors. can

Then, as another example, a case in which the internal circuit protection unit 16 performs a normal operation after an initialization operation will be described.

The level shifter 16_2 receives the power-down mode signal PWRDN and the high voltage H_VDD from the power-down mode signal controller 18 and the high voltage generator 12, respectively.

During normal operation, the level shifting unit 16_2 receives a low-level power-down mode signal PWRDN from the power-down mode signal controller 18. The input low-level power-down mode signal PWRDN 1 is output as a high-level power-down mode signal PWRDN by the inverter unit IV1.

The high-level power-down mode signal PWRDN is input to the first input transistor T3 through the first node N1, and the high-level power-down mode signal PWRDN passes through the second inverter unit IV2. It is inverted to a low level again and input to the second input transistor T4.

In the level shifting unit 16_2, when the high-level power-down mode signal PWRDN increases above the threshold voltage of the first input transistor T3, the first input transistor T3 is turned on. In this case, the level of the second node N2 is input to the gate of the second mirror transistor T2, and thus the second mirror transistor T2 is turned on.

However, since the low-level power-down mode signal PWRDN is input to the second input transistor T4, a high-level output signal is output to the fourth node N4.

Then, since the power-down mode signal higher than the threshold voltage of the first PMOS transistor T5 is input from the level shifting unit 16_2 to the static electricity prevention unit 16_4, the first PMOS transistor T5 does not operate.

At this time, the combination unit NOR1 of the static electricity prevention unit 16_4 combines the power-up delay signal PWRUP_DLY and the power-down mode delay signal PWRDN_Delay having a low level in normal mode to output a combined signal. In the unit 16_4, the second PMOS transistor T6 and the first NMOS transistor T7 are turned on by the combination signal output from the combination unit NOR1, but the first PMOS transistor T5 does not operate. will not emit.

Finally, as another example, a case in which the internal circuit protection unit 16 of the sensor board performs an operation when the power voltage rises excessively will be described.

The level shifter 16_2 receives the power-down mode signal PWRDN and the high voltage H_VDD from the power-down mode signal controller 18 and the high voltage generator 12, respectively.

At this time, the level shifting unit 16_2 receives a high-level power-down mode signal PWRDN from the power-down mode signal controller 18 when the internal voltage excessively rises. The input high-level power-down mode signal ( PWRDN) is output as a low-level power-down mode signal PWRDN by the first inverter unit IV1.

The low-level power-down mode signal PWRDN thus output is input to the first input transistor T3 through the first node N1, and at the same time passes through the second inverter unit IV2 to generate a high-level power-down again. It is inverted into the mode signal PWRDN and input to the second input transistor T4.

In the level shifting unit 16_2, when the low-level power-down mode signal PWRDN decreases below the threshold voltage of the first input transistor T3, the first input transistor T3 does not operate. In this case, the level of the second node N2 is output to the second mirror transistor T2, and accordingly, the second mirror transistor T2 does not operate.

However, since the high-level power-down mode signal PWRDN is input to the level shifter 16_2 to the second input transistor T4, the second input transistor T4 is turned on and thereby the fourth node N4 is turned on. The level becomes a low level, thereby outputting a low level output signal.

Then, when an output signal of a low level equal to or less than the threshold voltage of the first PMOS transistor T5 is input from the level shifter 16_2 to the static electricity prevention unit 16_4, the first PMOS transistor T5 is turned on.

At this time, the combination unit NOR1 of the antistatic unit 16_4 receives the power-up delay signal PWRUP_DLY and the power-down mode delay signal PWRDN_Delay having a low level even when VDD rises excessively and outputs a combination signal. Since the second PMOS transistor T6 and the first NMOS transistor T7 are turned on by the combination signal output from the combination unit NOR1, the prevention unit 16_4 releases current so that the level of the power supply voltage is lowered. can

As such, the internal protection unit 41 according to the present invention generates the highest voltage that can be generated inside to shift the level of the power-down mode signal, compares the shifted voltage level with the level of the power supply voltage, and removes the overcurrent from the outside. By discharging it, malfunction of the internal circuit can be prevented.

10 is a conceptual diagram of a remote cultivation consulting system 100.

Referring to FIG. 10, the remote cultivation consulting system 100 is composed of an ERP for plant production management and a machine learning part for collected data.

That is, the remote cultivation consulting system 100 may provide automatic cultivation data based on the learning data from the time when learning data over a predetermined range is accumulated while providing manual cultivation data by a preset pool of experts.

Therefore, it has the advantage of being able to automate the information necessary for decision-making to increase production and improve quality based on accumulated learning data.

That is, at first, manual cultivation data by a pool of experts is provided, and the growth status of plants is monitored while controlling the growth environment of plants, and then learning data is continuously accumulated by feeding back the monitoring results.

After sufficient learning data is accumulated, AI (Artificial Intelligence) based automatic cultivation data is provided based on the learning data, so that the growth conditions of the plant are automatically adjusted even if climate or environmental changes occur. Ultimately, it is possible to provide a solution that can automatically make cultivation decisions through the smart farm complex environment control system.

Therefore, comprehensive plant production management according to the plant cultivation electronic manual optimized through the remote cultivation consulting system 100 is possible, and the electronic manual that can be applied to changes in the environment, equipment, and production crops due to climate change is automatically created. In addition, remote cultivation consulting support is available both online and offline.

In addition, it is possible to collect and analyze structured and atypical information on plant growth, cultivation environment, pests and diseases, cultivation work, etc., and supervised learning and analysis by growth experts for machine learning of information collected in test bed cultivation. .

In particular, cultivation advice and work instructions are possible (automatic cultivation data, manual cultivation data) through real-time analysis of morphology, plant stress (NDVI: Normalized Difference Vegetation Index), and nutrient deficiency analysis.

11 is a diagram showing an example of an environment analysis process considering fluid dynamics.

Referring to FIG. 11, the smart farm complex environment control system (1) analyzes the indoor temperature change for natural convection and forced ventilation in the greenhouse using a computational fluid dynamics program, and then determines the selection, location, and operation method of the measuring device. elements can be extracted.

For example, it is possible to analyze the internal temperature change according to the natural convection and forced ventilation of the facility house, and to analyze the energy used according to the control to reduce the increasing energy in agriculture.

In other words, breaking away from simple control factors such as time, temperature, and humidity, based on the rule engine, management standards by various and complex factors such as relationship with factors, time series analysis, and energy consumption are established. can be provided automatically.

12 is a view showing a growth measurement method using an image

Referring to FIG. 12 , shape analysis, color analysis, and wavelength analysis may be performed based on a camera image.

That is, it is possible to automatically measure the growth size and shape by extracting the shape of the plant, classify the plant, and automatically predict the yield according to growth.

In addition, by analyzing the color and pigment of the plant with a histogram, it is possible to classify the plant, determine the quality, and automatically analyze the photosynthetic pigment.

In addition, it is possible to analyze the growth and element content by measuring the amount of light absorbed by each wavelength band of the plant, and automatically analyze the plant stress and photosynthetic state.

The data measured in this way is transmitted to the remote cultivation consulting system 100, used for analyzing plant growth status and stress information by image, and learning guidance and analysis by growth experts for machine learning of the information collected during cultivation in the test bed. It can be used for optimum growth temperature, yield prediction, and nutrient solution supply.

13 is a diagram showing an example of a growth measurement process using an image.

Referring to FIG. 13, conventional leaf area measurement methods are the sum of unit elevations, and an error occurs when the leaves are distinguished and the leaves overlap.

Therefore, in the smart farm complex environment control system (1), accuracy can be increased by measuring the total surface area of the leaves of the plant unit.

That is, after taking a plant image using a plurality of cameras (visible ray region imaging camera, near infrared ray region imaging camera, long-wave infrared region imaging camera), the distance of the plant is measured, and the height of the plant and the total surface area of the leaf are taken into consideration. Growth status and nutrient deficiency status can be predicted.

Here, the total surface area of the leaves of the plant unit is defined by a method of estimating the actual surface area by detecting the outer contours of all leaves (the outer contours detected on the photographed screen). By substituting the height of the plant here, the current growth state can be predicted.

In particular, the remote cultivation consulting system 100 can be used to detect the outer contours of all leaves using an algorithm based on a frangi filter. That is, when using the frangi filter, there is an advantage in that the edges of continuous shapes are more clearly distinguished. Therefore, the shape of the leaf can be detected more quickly and accurately.

14 is a diagram illustrating a method of measuring plant growth and stress using acquired video images.

Referring to FIG. 14, the remote cultivation consulting system 100 of the smart farm complex environment control system 1 applies a technology for detecting disease symptoms of plants using plant growth measurement and machine learning, which are the basis of remote cultivation consulting. do. In other words, it automatically analyzes plant morphology, plant stress (NDVI: Normalized Difference Vegetation Index), and nutrient deficiency based on the photographed images.

In addition, it is classified according to the photographing wavelength, and nutrient deficiency is automatically analyzed after capturing plant images using a plurality of cameras (visible ray region imaging camera, near infrared region imaging camera, and long-wave infrared region imaging camera).

For reference, if a time lapse camera capable of photographing plants at intervals selected from 0.3 seconds to 60 seconds is added, the remote cultivation consulting system 100 analyzes the time lapse images of a plurality of plants .

That is, the remote cultivation consulting system 100 analyzes each correlation between the growth rate of each leaf, the growth order of each leaf, the growth rate of the plant, the flowering rate of the flower, and the quality of the fruit according to the growth rate of the fruit. After that, it can be provided as analysis data. In addition, based on the growth rate of each part of the plant in the time-lapse video, the disease symptoms of the plant can be predicted and provided as analysis data. In addition, based on the color change of the fruit of the plant in the time-lapse video, the optimal harvest time can be predicted and provided as analysis data.

Meanwhile, such an image may be displayed on the user's portable terminal, and a virtual object corresponding to the actual image information of the crop image displayed on the screen of the portable terminal may be displayed. When a virtual object is touched, a motion of a preset virtual object corresponding to the touched part may be reproduced. For example, if a flower is displayed as a virtual object and a corresponding part is touched, a scene in which the flower blooms may be reproduced.

At this time, when a virtual object corresponding to the actual image information of the crop image displayed on the screen of the portable terminal is displayed, the coordinates of the virtual object are changed from the spatial coordinate system for the actual image information to the mobile coordinate system of the portable terminal, and the deselected virtual object is displayed. The coordinates of the object may be changed from the mobile coordinate system of the portable terminal to the spatial coordinate system for real image information.

The smart farm complex environment control system according to an embodiment of the present invention is connected to a decoupling capacitor and is provided with a sensor board that reduces resonance noise caused by power while the resistance value is varied.

In addition, the sensor board may protect the internal circuit by discharging static electricity to the outside through the internal circuit protection unit.

In addition, the smart farm complex environment control system can provide automatic cultivation data based on the learning data from the time when learning data over a predetermined range is accumulated while providing manual cultivation data by a preset pool of experts.

Therefore, it has the advantage of being able to automate the information necessary for decision-making to increase production and improve quality based on accumulated learning data.

That is, at first, manual cultivation data by a pool of experts is provided, and the growth status of plants is monitored while controlling the growth environment of plants, and then learning data is continuously accumulated by feeding back the monitoring results.

After sufficient learning data is accumulated, AI (Artificial Intelligence) based automatic cultivation data is provided based on the learning data, so that the growth conditions of the plant are automatically adjusted even if climate or environmental changes occur. Ultimately, it is possible to provide a solution that can automatically make cultivation decisions through the smart farm complex environment control system.

As such, those skilled in the art to which the present invention pertains will be able to understand that the present invention may be embodied in other specific forms without changing its technical spirit or essential features. Therefore, the embodiments described above should be understood as illustrative in all respects and not limiting. The scope of the present invention is indicated by the following claims rather than the detailed description above, and all changes or modifications derived from the meaning and scope of the claims and their equivalent concepts should be interpreted as being included in the scope of the present invention. do.

100: remote cultivation consulting system
200: automation control system
300: growth analysis system

Claims (5)

A remote cultivation consulting system that provides automatic cultivation data based on the learning data from the point of time when learning data over a predetermined range is accumulated while providing manual cultivation data by a preset pool of experts;
a portable terminal displaying an image provided from the remote cultivation consulting system; and
An automated control system having a sensor board including a temperature sensor and a humidity sensor and controlling the growth environment of plants based on the manual cultivation data and the automatic cultivation data;
The sensor board may include a power supply noise processing unit that is connected to a decoupling capacitor connected to an internal circuit unit to reduce resonance noise caused by a power supply while changing a resistance value; and generating an output signal by shifting the level of the power-down mode signal applied from the outside to a level equal to or higher than the driving voltage, and in response to the combined signal by the combination of the power-up delay signal and the power-down mode delay signal, the overcurrent flows into the internal circuit. Including; an internal circuit protection unit to prevent
The internal circuit protection unit includes a level shifting unit shifting the level of the power-down mode signal to a level higher than the driving voltage in response to a level higher than the driving voltage and outputting an output signal; and an anti-static unit discharging the overcurrent to the outside in response to a combination signal of the power-up delay signal and the power-down mode delay signal,
The remote cultivation consulting system detects the outer contours of all leaves using the "Frangi filter" among plant image information, estimates the total real surface area of the leaves based on the outer contours of all leaves, and considers the height of the plant additionally. to predict the current growth status,
In displaying a virtual object corresponding to the actual image information of the crop image displayed on the screen of the portable terminal, when the virtual object is touched, the movement of a preset virtual object corresponding to the touched part is reproduced. Smart farm complex environment control system.
According to claim 1,
The power supply noise processing unit,
The internal circuit part receiving power supply voltage and ground voltage;
a decoupling capacitor having one end connected to the input part of the power supply voltage of the internal circuit part; and
It is connected between the other end of the decoupling capacitor and the input of the ground voltage, and supplied to the internal circuitry such that a voltage level difference between the power supply voltage or the ground voltage and the power supply voltage or ground voltage drawn into the internal circuit unit is minimized. Smart farm complex environment control system characterized in that it comprises; a variable resistance unit in which the resistance value for reducing resonance noise is variable in response to the power supply voltage or ground voltage.
According to claim 2,
The variable resistance part,
a plurality of resistance elements connected in parallel; and
Smart farm complex environment control system comprising a; switching element for selecting the plurality of resistance elements.
According to claim 3,
The plurality of resistance elements,
a plurality of NMOS transistors having a drain terminal connected to the decoupling capacitor and a source terminal connected to a ground line; and
A smart farm complex environment control system comprising a; NMOS transistor to which a drain terminal is connected to the decoupling capacitor, a source terminal is connected to the ground line, and a power supply voltage is applied to a gate terminal.
According to claim 1,
A smart farm complex environment control system further comprising a growth analysis system that monitors the growth state of the plant and provides monitoring data to at least one or more of the remote cultivation consulting system and the automated control system.

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