MX2019014283A - Sistema y metodo para la gestion de riego mediante el uso de flujos de trabajo de aprendizaje de maquina. - Google Patents
Sistema y metodo para la gestion de riego mediante el uso de flujos de trabajo de aprendizaje de maquina.Info
- Publication number
- MX2019014283A MX2019014283A MX2019014283A MX2019014283A MX2019014283A MX 2019014283 A MX2019014283 A MX 2019014283A MX 2019014283 A MX2019014283 A MX 2019014283A MX 2019014283 A MX2019014283 A MX 2019014283A MX 2019014283 A MX2019014283 A MX 2019014283A
- Authority
- MX
- Mexico
- Prior art keywords
- machine learning
- field
- sensors
- irrigation management
- learning module
- Prior art date
Links
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
- A01G25/09—Watering arrangements making use of movable installations on wheels or the like
- A01G25/092—Watering arrangements making use of movable installations on wheels or the like movable around a pivot centre
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/041—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a variable is automatically adjusted to optimise the performance
-
- 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
-
- 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
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
Landscapes
- Engineering & Computer Science (AREA)
- Artificial Intelligence (AREA)
- Life Sciences & Earth Sciences (AREA)
- Water Supply & Treatment (AREA)
- Environmental Sciences (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Health & Medical Sciences (AREA)
- Evolutionary Computation (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Soil Sciences (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
La presente invención proporciona un sistema y método que incluye un módulo de aprendizaje de máquina que analiza los datos recolectados de una o más fuentes tales como los UAV, satélites, sensores de cultivos montados en los tramos, sensores directos de suelo y sensores climáticos. De acuerdo con una modalidad preferida adicional, el módulo de aprendizaje de máquina crea preferentemente conjuntos de objetos de campo dentro de un campo dado y usa los datos que recibe para crear un modelo predictivo para cada objeto de campo definido en función de las características detectadas de cada objeto de campo dentro del campo.
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US201762513479P | 2017-06-01 | 2017-06-01 | |
PCT/US2018/035400 WO2018222875A1 (en) | 2017-06-01 | 2018-05-31 | System and method for irrigation management using machine learning workflows |
Publications (1)
Publication Number | Publication Date |
---|---|
MX2019014283A true MX2019014283A (es) | 2021-01-08 |
Family
ID=64455578
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
MX2019014283A MX2019014283A (es) | 2017-06-01 | 2018-05-31 | Sistema y metodo para la gestion de riego mediante el uso de flujos de trabajo de aprendizaje de maquina. |
Country Status (8)
Country | Link |
---|---|
US (2) | US11429071B2 (es) |
EP (1) | EP3629695A4 (es) |
CN (1) | CN110708948B (es) |
AU (1) | AU2018275673B2 (es) |
CA (1) | CA3064038A1 (es) |
MX (1) | MX2019014283A (es) |
WO (1) | WO2018222875A1 (es) |
ZA (1) | ZA201907448B (es) |
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CN114364253B (zh) * | 2019-09-12 | 2024-02-09 | 瓦尔蒙特工业股份有限公司 | 用于分析中心支轴式灌溉系统内的电流和电压水平的系统和方法 |
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US11313811B2 (en) * | 2019-12-27 | 2022-04-26 | International Business Machines Corporation | Dynamic determination of irrigation-related data using machine learning techniques |
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-
2018
- 2018-05-31 AU AU2018275673A patent/AU2018275673B2/en active Active
- 2018-05-31 EP EP18809610.1A patent/EP3629695A4/en active Pending
- 2018-05-31 CA CA3064038A patent/CA3064038A1/en active Pending
- 2018-05-31 CN CN201880035172.9A patent/CN110708948B/zh active Active
- 2018-05-31 MX MX2019014283A patent/MX2019014283A/es unknown
- 2018-05-31 US US15/994,260 patent/US11429071B2/en active Active
- 2018-05-31 WO PCT/US2018/035400 patent/WO2018222875A1/en active Application Filing
-
2019
- 2019-11-11 ZA ZA201907448A patent/ZA201907448B/en unknown
-
2022
- 2022-07-15 US US17/865,858 patent/US11868100B2/en active Active
Also Published As
Publication number | Publication date |
---|---|
EP3629695A1 (en) | 2020-04-08 |
US20220365496A1 (en) | 2022-11-17 |
CN110708948A (zh) | 2020-01-17 |
AU2018275673A1 (en) | 2019-12-05 |
CA3064038A1 (en) | 2018-12-06 |
EP3629695A4 (en) | 2021-03-03 |
ZA201907448B (en) | 2020-11-25 |
AU2018275673B2 (en) | 2024-06-20 |
US11868100B2 (en) | 2024-01-09 |
US11429071B2 (en) | 2022-08-30 |
BR112019024937A2 (pt) | 2020-06-23 |
CN110708948B (zh) | 2022-12-02 |
US20180348714A1 (en) | 2018-12-06 |
WO2018222875A1 (en) | 2018-12-06 |
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