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WO2012123877A1 - Dispositif de commande d'irrigation utilisant un réseau neuronal artificiel - Google Patents

Dispositif de commande d'irrigation utilisant un réseau neuronal artificiel Download PDF

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Publication number
WO2012123877A1
WO2012123877A1 PCT/IB2012/051135 IB2012051135W WO2012123877A1 WO 2012123877 A1 WO2012123877 A1 WO 2012123877A1 IB 2012051135 W IB2012051135 W IB 2012051135W WO 2012123877 A1 WO2012123877 A1 WO 2012123877A1
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WIPO (PCT)
Prior art keywords
control device
irrigation
soil moisture
moisture content
solar
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/IB2012/051135
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English (en)
Inventor
Reinoud Jacob HARTMAN
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
IDUS CONTROLS Ltd
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IDUS CONTROLS Ltd
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Filing date
Publication date
Application filed by IDUS CONTROLS Ltd filed Critical IDUS CONTROLS Ltd
Publication of WO2012123877A1 publication Critical patent/WO2012123877A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
    • A01G25/00—Watering gardens, fields, sports grounds or the like
    • A01G25/16—Control of watering
    • A01G25/167—Control by humidity of the soil itself or of devices simulating soil or of the atmosphere; Soil humidity sensors
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
    • Y02A40/10—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in agriculture
    • Y02A40/28—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in agriculture specially adapted for farming
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P60/00—Technologies relating to agriculture, livestock or agroalimentary industries
    • Y02P60/12—Technologies relating to agriculture, livestock or agroalimentary industries using renewable energies, e.g. solar water pumping

Definitions

  • This invention is related to the field of irrigation control devices adapted to managing irrigation in a highly intelligent and efficient manner using an artificial neural network, allowing it to be controlled to the specific requirements of the soil and the plants therein, while incorporating and utilizing environmental information to achieve precise control.
  • My invention is an artificial neural network driven compact, modular irrigation control device that intelligently manages irrigation, watering to a calibrated 'just like that' soil moisture level and maintaining that level daily in response to changing environmental conditions.
  • the control algorithm utilizes a Kohenen Neural Network in a unique way for irrigation purposes, whereby information from a capacitance-type soil moisture sensor, a daylight sensor and daily environmental conditions is used to predict and control irrigation functions.
  • Unique procedures such as use of the 'drying factor', a monitored rate of change in soil moisture as environmental conditions vary, form a key part of the intelligent control processes utilized by the control algorithm.
  • the invention can be configured in various ways including mounting the control device, irrigation control valve, and water supply and distribution plumbing in a single unit ( Figure 1) which can be easily mounted between the water supply and the irrigation system.
  • the invention can be configured with the plumbing and water control valve functions remote from the control device, with the valve operated by electronic connection from the control device to the valve ( Figure 2).
  • the control device can be configured with radio communication to allow remote monitoring of irrigation parameters in various locations, for local control in those locations or to provide information for adjusting control functions ( Figure 3).
  • Several objects and advantages of the invention are to: save domestic water by irrigating to only the amount of soil moisture content required for optimal plant growth, avoiding over-watering and waste of water; provide precise control to maintain desired soil moisture settings in the face of changing environmental conditions as weather changes from day to day; provide for rendering the irrigation function dormant when it has rained and soil moisture levels are above the 'just like this' set-point; utilize a Neural Network 'learning' algorithm whereby the control device learns from, and employs information to predict and adjust the irrigation regime as environmental conditions change; allow operator adjustment to move the soil moisture calibration set-point up or down with push button controls and LED visual display of the soil moisture content; allow operator adjustment to move the control device to another location or to different soil and re-calibrate the device to a new 'just like that' set-point for moisture level control; provide a compact, easily-installed device that can be affixed to a hose or piping system in a manner similar to attaching a garden sprinkler to a hose, rendering
  • Figure 1 is an illustration of the control device of one embodiment of the present invention.
  • Figure 2 is an illustration of the control device another embodiment of the invention mounted to a post.
  • Figure 3 is an illustration of the control device of another embodiment of the invention wherein a first and a second control device are in wireless communication.
  • Figure 4 is a schematic diagram illustrating components of the operating regime for the control device programmed with the Kohenen Neural Network.
  • Figure 5 depicts the operational steps and control functions of the control device on system start-up and initial calibration.
  • Figure 6 depicts the daily irrigation management processes followed by the control device.
  • An neural network drive compact modular irrigation control device is used, enabling beneficial irrigation by maintaining soil moisture levels using a capacitance -type soil moisture sensor calibrated 'just like this' avoiding over-watering and adjusting irrigation according to environmental conditions.
  • the control device utilizes a Kohenen Neural Network in a unique way for irrigation purposes by integrating inputs from the soil moisture sensor, a temperature sensor, a daylight sensor, drying rates in the soil, and the daily fluctuations in environmental conditions to predict and control irrigation requirements. Over time, utilizing up to 32 days of stored data on how the garden responds to watering and changing environmental conditions, the Neural Network refines its predictions and conducts daily watering operations.
  • the Neural Network incorporates unique parameters such as a 'drying factor' in determining how to achieve a 'just like this' soil moisture set-point in accordance with the needs of the operator, the specific needs of the plants and the soil characteristics of the area to be irrigated.
  • the 'just like that' set-point is timed to take place at around noon of each day when the plants need the appropriate moisture level the most, with watering taking place in the morning daily.
  • the control device is compact, is housed in a single unit housing, and can be configured to attach to the irrigation water supply or operate a solenoid or servo-valve attached or detached from the unit, depending on application desired. Precisely controlling irrigation so that only the optimal amount of water needed to achieve the 'just like that' calibration setting results in significant water use savings, as well as increased plant health and production.
  • FIG. 1 there is shown an illustration of one embodiment of the invention (100) that illustrates the components of the 'Hose-Head' irrigation control device (102) affixed to a water supply pipe (104) having a flow from entry portal (106) to egress portal (108).
  • Control device (102) is fixed to the water supply pipe (104) in the embodiment shown, but it can also be installed remote from the pipe as illustrated in Figure 2 discussed below.
  • the control device (102) has electrical connections (114) to a moisture content sensing device (108) embedded in the irrigated soil (110) to a suitable depth (112) for sensing soil moisture and relaying a signal proportional to soil moisture by way of cable (114) to an input (116) of the control device (102).
  • the control device (102) is also connected electrically to a valve (114) by way of cable (117) to input (119) to provide opening and closing commands to the valve (114).
  • the valve is operated by an internal electrical solenoid which is not illustrated.
  • the control device (102) has a power source comprising batteries (120) installed in a battery port (122) on the side (124) of the control device housing (103).
  • batteries 120
  • other sources of power can be employed such as AC power and solar regenerated DC power.
  • control device (102) is compact, portable and modular.
  • the control device (102) comprises a housing (124) that contains an internal electronic control board (not illustrated) that is programmed with the Kohenen Neural Network control algorithm.
  • the housing (124) is shock resistant and weather-proof .
  • control device (102) is fixed by brackets (not illustrated) to the water supply piping (104) and proximate to normally-closed solenoid valve (114).
  • the control device (102) can also be fixed to a garden hose or supply piping by a garden hose-type threaded screw connection and washer.
  • Control buttons (130) on the upper face (132) of the weather proof housing (103) allow the operator to adjust control moisture set-point levels (displayed on display (140)) upwards or downwards or re-calibrate the control device. These buttons (130) operate through a membrane (134) on the upper face (132) of the weather-proof housing preventing ingress of water. Green and Red LED visual displays (or an LCD screen (136)), visible through the membrane (134) of the housing, provide operator information on soil moisture level, facilitating upward or downward adjustment. Daylight (142) and temperature (144) sensors operate through the membrane and are protected by it. The daylight and temperature sensors provide continual information which is monitored by the control device and integrated with timing information.
  • the control device (102) is connected, by electrical connection through a lead (114), to a capacitance-type soil moisture sensor (108) inserted in the soil to be irrigated (110) at a depth (112).
  • the soil around the sensor is compacted and adjusted to the desired moisture level at the initial 'just like that' calibration procedure.
  • the desired moisture level is then used as the set-point for irrigation operations managed by the control devce.
  • Power is supplied to the unit by small domestic low-voltage alkaline batteries (120) in an efficient manner as managed by the control device so that battery life is prolonged. Batteries can be replaced by opening the weather-proof gasket-sealed port (122) in the housing.
  • control device (202) is mounted to a post (204) and not on and directly adjacent to the water supply (206) and the valve (208) which controls irrigation flow (210) into an irrigation system comprising a header (207) and irrigation lines (209).
  • the solenoid (212) or servo-control valve which opens and closes the water supplied to the irrigation system is remote connected to the control device (202) by wire (214).
  • This configuration allows the control device (202) to be retrofitted to an existing irrigation system or installed where direct attachment to the water supply itself is not desired or needed.
  • the soil moisture sensor (220) is inserted into the area to be irrigated (222) and connected electrically (224) to the control device (202).
  • Components and functions of the control device (202) illustrated in Figure 2 are identical to the control device (102) illustrated in Figure 1.
  • FIG. 3 there is illustrated yet another embodiment of the invention (300).
  • This embodiment is a depiction of the control device (302a and 302b) used in a large-scale commercial application.
  • the water supply (304) from a main supply pipe (306) is managed by the device (302a) which operates a normally-closed servo-control valve (308) supplying water to the field (310).
  • Electrical connection (312) between the control device (302a) and the servo-control valve (314) provides the means for opening and closing the valve as called for by the control devices' control algorithm.
  • Control device (302a) is illustrated mounted to the post (316) close to the servo-control valve (314) and connected to the soil moisture sensor (320) by wire (315).
  • the moisture sensor is inserted in the soil of the field (310) or garden plot to be irrigated.
  • This control device (302a) and the connected (315) moisture sensor (320) could be located anywhere in the field to optimize location and calibration of the 'just like that' set-point calibration. In this manner it could be located to represent the average conditions of sunlight and exposure for the field. Alternately, it can be located in the portion of the field experiencing the greatest sunlight exposure and drying conditions in order to ensure that portion of the field receives adequate irrigation daily.
  • the configuration (300) includes an optional second (302b) control device mounted to post (322) for controlling the irrigation of an area of land (324) shown by the patterned area.
  • the second control device (302b) is in communication with and synchronized with the first control device (302a) by electronic or radio communication (326 and 328) established between the primary (302a) and secondary control device (302b).
  • the invention permits scaling of irrigation control by use of as many control devices as necessary to cover the irrigated land and to account for variables in the moisture content of the soil. In this way, the entire field will comprise a plurality of synchronized irrigation controllers for irrigation of specific areas of land to specific soil moisture levels.
  • Figure 3 also illustrates a system of irrigation (300) comprising a primary irrigation control device (302a) which controls a primary valve (308) on a primary water supply pipe (304).
  • the primary irrigation control device has a first moisture sensor (320) and a first wireless communication means (328) for irrigation of a first area of land (310) having a first moisture content.
  • a secondary irrigation control device (302b) which controls a secondary valve (330) on a secondary water supply pipe (332) connected to the first water supply pipe (306).
  • the secondary irrigation control device (302b) has a second moisture sensor (334) and a second wireless communication means (326)for irrigation of a second area (324) within the first area of land (310).
  • the second area (324) has a higher moisture content than the first area of land (310).
  • the second moisture sensor (334) communicates (336) a higher second moisture content signal to the secondary irrigation control device (302b).
  • the secondary irrigation control device communicates (326) the higher second moisture content signal to the primary irrigation control device (302a) so that when the primary control device generates an irrigation signal to said primary water supply valve (308) to irrigate the first area of land (310) the secondary control device receives the same irrigation signal and subsequently controls the secondary valve (330) so that the second moisture content measured by moisture sensor (334) does not exceed the first moisture content.
  • FIG. 4 there is a schematic depiction of key functions and connectivity (400) related to the control device and programmed into the control device (402) and employing a Kohenen Neural Network.
  • the soil moisture sensor (404) is inserted into compacted soil (406) of the irrigation plot which is moistened to the desired soil moisture level as desired by the operator.
  • the algorithm loads data into RAM in the form of the neural network, initiates the network function, and sets timers (408).
  • the network interrogates the moisture sensor (404), temperature sensor (410), and daylight sensor (412) and records those settings and time.
  • the initial 'just like that' moisture setting equivalent to those conditions is thus established as the initial set-point calibration for managing irrigation operations (414).
  • FIG. 5 and 6 there is displayed display the steps and actions utilized by the Neural Network in managing irrigation operations.
  • Figure 5 illustrates the method (500) by which the system start-up and calibration processes that take place when the control device is installed and first activated to achieve the 'just like that' target set-point calibration.
  • step 502 the system commences its start-up.
  • the system initiates a power-up, loads the RAM into the Kohenen Neural Network and initiates the timer and sets the clock.
  • step 506 data is gathered from the moisture sensor (508), temperature sensor (510) and daylight sensor (512) as illustrated in Figure 4. These data are sent to the controller (514) and recorded by the system.
  • the data is processed by the Kohenen Neural Network to establish a "just-like-that" calibration set point (518) for the moisture control sensor.
  • the calibration is used to control the irrigation of a selected area of land.
  • the calibration is stored in the system memory.
  • FIG. 6 there is illustrated a daily irrigation management procedure (600) of the invention.
  • the procedure commences at step (602) when at daybreak each day, the system is activated by information received by the daylight sensor.
  • the control device checks and records soil moisture content (606) and temperatuire(608). One hour later the control device checks and records the soil moisture content again. This step determines the daily 'drying rate' parameter which is related to how quickly environmental conditions in the ground plot are affecting moisture content.
  • the control device then applies the predictive abilities of the neural network (612) and initiates watering (614) based on a prediction made by the neural network by opening the solenoid valve and watering to about 80% of the predicted water application.
  • One such sustained watering cycle is applied per day in the morning with the objective of watering plants early and achieving the desired 'just like that' soil moisture setting around noon when the plants are most in need of appropriate soil moisture to optimize growth and plant health.
  • the prediction calculations made by the neural network that take place at midnight prior to the predicted watering solution being implemented for the watering regime on the following day.
  • the neural network utilizes learned information and most recent data. On start-up, and during the first days of operations, the neural network uses the initial soil moisture content, temperature and daylight settings for the day as well as 16 programmed internal 'typical' daily data sets which are retained within the network's RAM memory. This data was recorded in a typical garden and is stored in the program for initial propagation into the neural network for it to work with. The network takes this information from memory as well as that from the start-up data gathering, and utilizing 5000 iterations of calculation for each data set plus the new information, makes a prediction of the water to be applied the following day.
  • This process is repeated each day, with the control device, utilizing the algorithm, recording up to 32 more daily data sets for use in predictions.
  • the initial experiential memory used for predictive purposes moves from 16 programmed data sets to 16 plus 32 new data sets acquired 'insitu', for a total of 48 data sets, each of which is involved in the daily calculation process (and each with 5000 calculation iterations).
  • This process begins afresh each day hence the network is constantly upgrading its predictions and tailoring them to actual conditions in the garden.
  • the successful prediction scenarios will move away from the initial 16 in memory and more towards the recorded daily scenarios based on actual conditions in the garden and the surrounding environment.
  • the neural network will adapt to the changing conditions of temperature, daylight and rainfall utilizing predictions that enable it to adapt based on experience with wetter and dryer periods in the garden.
  • control and fail-safe functions that limit the amount of watering that takes place in a given day (to avoid system malfunction and waste of water or damage to the plants) as well as monitor battery condition, and shut down the system if battery current levels fall so low as to risk having insufficient power to close the valve.

Landscapes

  • Life Sciences & Earth Sciences (AREA)
  • Soil Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Water Supply & Treatment (AREA)
  • Environmental Sciences (AREA)
  • Feedback Control In General (AREA)

Abstract

Selon l'invention, un dispositif de commande d'irrigation modulaire, compact, entraîné par un algorithme est utilisé, permettant une irrigation bénéfique par maintien des niveaux d'humidité du sol à l'aide d'un capteur d'humidité du sol de type capacité étalonné « juste comme ça » évitant un sur-arrosage et ajustant l'irrigation selon les conditions environnementales. L'algorithme de commande utilise un réseau neuronal de Kohenen d'une manière unique à des fins d'irrigation, intégrant des entrées provenant du capteur d'humidité du sol, d'un capteur de température, d'un capteur de lumière du jour, des vitesses de séchage dans le sol, et les fluctuations quotidiennes des conditions environnementales pour prédire et commander des exigences d'irrigation.
PCT/IB2012/051135 2011-03-14 2012-03-12 Dispositif de commande d'irrigation utilisant un réseau neuronal artificiel Ceased WO2012123877A1 (fr)

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US201161452543P 2011-03-14 2011-03-14
US61/452,543 2011-03-14

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Cited By (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2017045630A1 (fr) * 2015-09-16 2017-03-23 黄方元 Procédé de culture de brassica napus
WO2017133625A1 (fr) * 2016-02-01 2017-08-10 苏州宝时得电动工具有限公司 Système de maintenance de cour intelligent et procédé de maintenance correspondant
CN107646641A (zh) * 2017-09-25 2018-02-02 重庆公茂科技有限公司 一种光伏农业智能灌溉微控制系统
WO2018039917A1 (fr) * 2016-08-30 2018-03-08 广东森维绿联科技有限公司 Structure d'irrigation au goutte-à-goutte pour dispositif de plantation intelligent
WO2018039913A1 (fr) * 2016-08-30 2018-03-08 广东森维绿联科技有限公司 Dispositif intelligent de commande d'arrosage
WO2018101848A1 (fr) * 2016-11-29 2018-06-07 Coolfarm S.A. Système de détection et d'actionnement environnementaux basé sur un nuage dynamique prédictif et procédé de fonctionnement respectif
CN110476785A (zh) * 2019-09-04 2019-11-22 韩瑞峰 一种农业智能化控制灌溉装置
CN111656940A (zh) * 2020-07-10 2020-09-15 张艳霞 一种水利灌溉的控制方法
CN113575381A (zh) * 2021-09-29 2021-11-02 潍坊市园林环卫服务中心 隐蔽式园林浇灌自动喷雾装置及自动喷雾系统
CN114451257A (zh) * 2021-12-23 2022-05-10 珠海格力电器股份有限公司 基于神经网络的灌溉方法、装置、存储介质及电子设备
CN115756006A (zh) * 2022-11-14 2023-03-07 黑龙江大学 用于滴灌管的防堵方法、装置、设备以及系统
US11608813B2 (en) 2021-03-22 2023-03-21 Westbrook Labs, Inc. Wind machine control and monitor systems and methods
CN115812574A (zh) * 2022-11-25 2023-03-21 临泉真牛智能装备有限责任公司 一种灌溉机器人
US11824253B2 (en) 2020-03-02 2023-11-21 Husqvarna Ab Transmitter device

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CA2606464A1 (fr) * 2006-10-10 2008-04-10 Curtis S. Leggett Systeme sans fil de commande d'irrigation et de dissuasion d'entree non autorisee
US20100179701A1 (en) * 2009-01-13 2010-07-15 At&T Intellectual Property I, L.P. Irrigation system with wireless control
US20100324744A1 (en) * 2008-11-21 2010-12-23 Charles Kelly Cox Automatic gated pipe actuator

Patent Citations (3)

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Publication number Priority date Publication date Assignee Title
CA2606464A1 (fr) * 2006-10-10 2008-04-10 Curtis S. Leggett Systeme sans fil de commande d'irrigation et de dissuasion d'entree non autorisee
US20100324744A1 (en) * 2008-11-21 2010-12-23 Charles Kelly Cox Automatic gated pipe actuator
US20100179701A1 (en) * 2009-01-13 2010-07-15 At&T Intellectual Property I, L.P. Irrigation system with wireless control

Cited By (17)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2017045633A1 (fr) * 2015-09-16 2017-03-23 黄方元 Système d'irrigation de brassica napus
WO2017045630A1 (fr) * 2015-09-16 2017-03-23 黄方元 Procédé de culture de brassica napus
WO2017133625A1 (fr) * 2016-02-01 2017-08-10 苏州宝时得电动工具有限公司 Système de maintenance de cour intelligent et procédé de maintenance correspondant
WO2018039917A1 (fr) * 2016-08-30 2018-03-08 广东森维绿联科技有限公司 Structure d'irrigation au goutte-à-goutte pour dispositif de plantation intelligent
WO2018039913A1 (fr) * 2016-08-30 2018-03-08 广东森维绿联科技有限公司 Dispositif intelligent de commande d'arrosage
WO2018101848A1 (fr) * 2016-11-29 2018-06-07 Coolfarm S.A. Système de détection et d'actionnement environnementaux basé sur un nuage dynamique prédictif et procédé de fonctionnement respectif
CN107646641A (zh) * 2017-09-25 2018-02-02 重庆公茂科技有限公司 一种光伏农业智能灌溉微控制系统
CN110476785A (zh) * 2019-09-04 2019-11-22 韩瑞峰 一种农业智能化控制灌溉装置
US11824253B2 (en) 2020-03-02 2023-11-21 Husqvarna Ab Transmitter device
CN111656940A (zh) * 2020-07-10 2020-09-15 张艳霞 一种水利灌溉的控制方法
US11608813B2 (en) 2021-03-22 2023-03-21 Westbrook Labs, Inc. Wind machine control and monitor systems and methods
CN113575381B (zh) * 2021-09-29 2021-12-10 潍坊市园林环卫服务中心 隐蔽式园林浇灌自动喷雾装置及自动喷雾系统
CN113575381A (zh) * 2021-09-29 2021-11-02 潍坊市园林环卫服务中心 隐蔽式园林浇灌自动喷雾装置及自动喷雾系统
CN114451257A (zh) * 2021-12-23 2022-05-10 珠海格力电器股份有限公司 基于神经网络的灌溉方法、装置、存储介质及电子设备
CN115756006A (zh) * 2022-11-14 2023-03-07 黑龙江大学 用于滴灌管的防堵方法、装置、设备以及系统
CN115756006B (zh) * 2022-11-14 2023-05-30 黑龙江大学 用于滴灌管的防堵方法、装置、设备以及系统
CN115812574A (zh) * 2022-11-25 2023-03-21 临泉真牛智能装备有限责任公司 一种灌溉机器人

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