公开(公告)号：US20210068334A1

公开(公告)日：2021-03-11

申请号：US16565457

申请日：2019-09-09

申请人： International Business Machines Corporation

发明人： Juliet Mutahi ,  David W. Kaguma ,  Samuel Maina Karumba ,  Nelson Kibichii Bore ,  Percival Silva de Lucena ,  Andrew Kinai ,  Komminist Weldemariam ,  Peninah M. Waweru

IPC分类号： A01B79/00 ,  B60W40/09 ,  G07C5/08 ,  G06F17/27 ,  G06F17/28 ,  G06F16/951 ,  G06N20/00

摘要： A memory embodies instructions, and a processor is coupled to the memory and is operative by the instructions to facilitate: accessing a source of information regarding farm cultivation techniques; constructing a cultivation knowledge graph by parsing the source of information regarding farm cultivation techniques, using natural language processing; identifying cultivation quality assessment factors by applying machine learning to the cultivation knowledge graph; estimating quality of a farm cultivation task by comparing a stream of real-time data to the cultivation quality assessment factors, wherein the stream of real-time data is related to performance of the farm cultivation task; identifying from the stream of real-time data, using the cultivation knowledge graph, a controllable variable that affects the quality of the farm cultivation task; and improving the quality of the farm cultivation task by facilitating a change in the controllable variable. The controllable variable may be the identity of a tractor operator.

公开(公告)号：US11497156B2

公开(公告)日：2022-11-15

申请号：US16565457

申请日：2019-09-09

申请人： International Business Machines Corporation

发明人： Juliet Mutahi ,  David W. Kaguma ,  Samuel Maina Karumba ,  Nelson Kibichii Bore ,  Percival Silva de Lucena ,  Andrew Kinai ,  Komminist Weldemariam ,  Peninah M. Waweru

IPC分类号： A01B79/00 ,  B60W40/09 ,  G07C5/08 ,  G06F16/951 ,  G06N20/00 ,  G06F40/44 ,  G06F40/205 ,  B60W50/00

摘要： A memory embodies instructions, and a processor is coupled to the memory and is operative by the instructions to facilitate: accessing a source of information regarding farm cultivation techniques; constructing a cultivation knowledge graph by parsing the source of information regarding farm cultivation techniques, using natural language processing; identifying cultivation quality assessment factors by applying machine learning to the cultivation knowledge graph; estimating quality of a farm cultivation task by comparing a stream of real-time data to the cultivation quality assessment factors, wherein the stream of real-time data is related to performance of the farm cultivation task; identifying from the stream of real-time data, using the cultivation knowledge graph, a controllable variable that affects the quality of the farm cultivation task; and improving the quality of the farm cultivation task by facilitating a change in the controllable variable. The controllable variable may be the identity of a tractor operator.