이 애플리케이션의 일부 콘텐츠는 현재 사용할 수 없습니다.
이 상황이 계속되면 다음 주소로 문의하십시오피드백 및 연락
1. (WO2019032648) MACHINE LEARNING IN AGRICULTURAL PLANTING, GROWING, AND HARVESTING CONTEXTS
국제사무국에 기록된 최신 서지정보정보 제출

공개번호: WO/2019/032648 국제출원번호: PCT/US2018/045719
공개일: 14.02.2019 국제출원일: 08.08.2018
IPC:
A01B 79/02 (2006.01) ,A01C 21/00 (2006.01) ,A01B 79/00 (2006.01)
A SECTION A — 생활필수품 농업
01
농업; 임업; 축산; 수렵; 포획; 어업
B
농업 또는 임업에 있어서의 토작업; 농기구 또는 기구의 부품, 세부 또는 부속구 일반
79
토작업의 방법(특별한 작업기의 사용을 필요로 하는 것은 관련되는 적절한 그룹을 참조)
02
다른 농작업 과정과 결합한 것, 예. 시비, 식부
A SECTION A — 생활필수품 농업
01
농업; 임업; 축산; 수렵; 포획; 어업
C
식부; 파종; 시비
21
시비방법
A SECTION A — 생활필수품 농업
01
농업; 임업; 축산; 수렵; 포획; 어업
B
농업 또는 임업에 있어서의 토작업; 농기구 또는 기구의 부품, 세부 또는 부속구 일반
79
토작업의 방법(특별한 작업기의 사용을 필요로 하는 것은 관련되는 적절한 그룹을 참조)
출원인:
INDIGO AG, INC. [US/US]; 500 Rutherford Avenue North Building Boston, MA 02129, US
발명자:
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
대리인:
JACOBSON, Anthony T.; US
SHUSTER, Michael, J.; US
BAILEY, F., Pinar; US
SEQUEIRA, Antonia, L.; US
BECKER, Daniel, M.; US
우선권 정보:
16/057,38707.08.2018US
62/542,70508.08.2017US
발명의 명칭: (EN) MACHINE LEARNING IN AGRICULTURAL PLANTING, GROWING, AND HARVESTING CONTEXTS
(FR) APPRENTISSAGE MACHINE DANS DES CONTEXTES DE PLANTATION, DE CULTURE ET DE RÉCOLTE AGRICOLES
요약서:
(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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지정국: 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
아프리카지역 지식재산권기구(ARIPO) (BW, GH, GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, UG, ZM, ZW)
유라시아 특허청(EAPO) (AM, AZ, BY, KG, KZ, RU, TJ, TM)
유럽 특허청(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)
아프리카 지식재산권기구(OAPI) (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, KM, ML, MR, NE, SN, TD, TG)
공개언어: 영어 (EN)
출원언어: 영어 (EN)