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1. (WO2019032648) MACHINE LEARNING IN AGRICULTURAL PLANTING, GROWING, AND HARVESTING CONTEXTS
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Pub. No.: WO/2019/032648 International Application No.: PCT/US2018/045719
Publication Date: 14.02.2019 International Filing Date: 08.08.2018
IPC:
A01B 79/02 (2006.01) ,A01C 21/00 (2006.01) ,A01B 79/00 (2006.01)
A HUMAN NECESSITIES
01
AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
B
SOIL WORKING IN AGRICULTURE OR FORESTRY; PARTS, DETAILS, OR ACCESSORIES OF AGRICULTURAL MACHINES OR IMPLEMENTS, IN GENERAL
79
Methods for working soil
02
combined with other agricultural processing, e.g. fertilising, planting
A HUMAN NECESSITIES
01
AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
C
PLANTING; SOWING; FERTILISING
21
Methods of fertilising
A HUMAN NECESSITIES
01
AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
B
SOIL WORKING IN AGRICULTURE OR FORESTRY; PARTS, DETAILS, OR ACCESSORIES OF AGRICULTURAL MACHINES OR IMPLEMENTS, IN GENERAL
79
Methods for working soil
Applicants:
INDIGO AG, INC. [US/US]; 500 Rutherford Avenue North Building Boston, MA 02129, US
Inventors:
PERRY, David Patrick; US
VON MALTZAHN, Geoffrey Albert; US
BERENDES, Robert; US
JECK, Eric Michael; US
KNIGHT, Barry Loyd; US
RAYMOND, Rachel Ariel; US
TRIVISVAVET, Ponsi; US
WONG, Justin Y.H.; US
RAJDEV, Neal Hitesh; US
MEUNIER, Marc-cedric Joseph; US
MICHELL, Charles, Vincent Jr.; US
LEIST, Casey James; US
TADI, Pranav Ram; US
FLAHERTY, Andrea Lee; US
BRUMMITT, Charles David; US
SINHA, Naveen Neil; US
LAMBERT, Jordan; US
HENNECK, Jonathan; US
BECCO, Carlos; US
ALLEN, Mark; US
BACHNER, Daniel; US
DEROSSI, Fernando; US
LAMONT, Ewan; US
LOWENTHAL, Rob; US
CREAGH, Dan; US
ABRAMSON, Steve; US
ALLEN, Ben; US
SHANKAR, Jyoti; US
MOSCARDINI, Chris; US
CRANE, Jeremy; US
WEISMAN, David; US
KEATING, Gerard; US
MOORES, Lauren; US
PATE, William; US
Agent:
JACOBSON, Anthony T.; US
SHUSTER, Michael, J.; US
BAILEY, F., Pinar; US
SEQUEIRA, Antonia, L.; US
BECKER, Daniel, M.; US
Priority Data:
16/057,38707.08.2018US
62/542,70508.08.2017US
Title (EN) MACHINE LEARNING IN AGRICULTURAL PLANTING, GROWING, AND HARVESTING CONTEXTS
(FR) APPRENTISSAGE MACHINE DANS DES CONTEXTES DE PLANTATION, DE CULTURE ET DE RÉCOLTE AGRICOLES
Abstract:
(EN) A crop prediction system performs various machine learning operations to predict crop production and to identify a set of farming operations that, if performed, optimize crop production. The crop prediction system uses crop prediction models trained using various machine learning operations based on geographic and agronomic information. Responsive to receiving a request from a grower, the crop prediction system can access information representation of a portion of land corresponding to the request, such as the location of the land and corresponding weather conditions and soil composition. The crop prediction system applies one or more crop prediction models to the access information to predict a crop production and identify an optimized set of farming operations for the grower to perform.
(FR) L'invention concerne un système de prédiction de culture végétale effectuant diverses opérations d'apprentissage machine pour prédire la production d'une culture végétale et identifier un ensemble d'opérations agricoles qui, si elles sont exécutées, optimisent la production d'une culture végétale. Le système de prédiction de culture végétale utilise des modèles de prédiction de culture végétale entraînés à l'aide de diverses opérations d'apprentissage machine sur la base d'informations géographiques et agronomiques. En réponse à la réception d'une demande provenant d'un cultivateur, le système de prédiction de culture végétale peut accéder à une représentation d'informations d'une partie de terrain correspondant à la demande, par exemple l'emplacement du terrain, les conditions météorologiques correspondantes et la composition du sol. Le système de prédiction de culture végétale applique un ou plusieurs modèles de prédiction de culture végétale aux informations d'accès pour prédire la production d'une culture végétale et identifier un ensemble optimisé d'opérations agricoles que le cultivateur doit effectuer.
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Designated States: AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW
African Regional Intellectual Property Organization (ARIPO) (BW, GH, GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, UG, ZM, ZW)
Eurasian Patent Office (AM, AZ, BY, KG, KZ, RU, TJ, TM)
European Patent Office (EPO) (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, LV, MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TR)
African Intellectual Property Organization (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, KM, ML, MR, NE, SN, TD, TG)
Publication Language: English (EN)
Filing Language: English (EN)