| CPC G06T 7/0012 (2013.01) [G06V 20/10 (2022.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30188 (2013.01); G06V 20/68 (2022.01)] | 20 Claims |
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1. A method implemented using one or more edge computing devices, the method comprising:
capturing, using one or more ground-level vision sensors, a first set of one or more images that depict an agricultural plot prior to performance of an agricultural task performed in the agricultural plot;
processing the first set of one or more images in situ using one or more of the edge computing devices based on a machine learning model to generate a plurality of pre-task inferences about the agricultural plot;
capturing, using one or more of the ground-level vision sensors, a second set of one or more images that depict the agricultural plot subsequent to the performance of agricultural task in the agricultural plot;
processing the second set of one or more images in situ using one or more of the edge computing devices based on the machine learning model to generate a plurality of post-task inferences about the agricultural plot;
auditing performance of the agricultural task, wherein the auditing includes comparing the plurality of pre-task inferences to the plurality of post-task inferences to generate one or more operational metrics about the performance of the agricultural task in the agricultural plot; and
causing one or more of the operational metrics to be presented at one or more output devices.
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