Adaptively adjusting parameters of equipment operating in unpredictable terrain

An edge computing device comprising memory and one or more processors, wherein the memory stores instructions that, in response to execution by the one or more processors, cause the one or more processors to:

• obtain a first image captured by one or more vision sensors transported across an agricultural field by a vehicle, wherein the first image depicts one or more plants growing in an agricultural area;
• process the first image to generate one or more agricultural inferences about one or more of the plants growing in the agricultural area, wherein the processing is based on a machine learning model;
• determine a quality metric for the one or more agricultural inferences using one or more of the edge computing devices, wherein the quality metric appraises or quantifies a value or reliability of one or more of the inferences;
• and
• while the vehicle continues to travel across the agricultural field, and based on the quality metric:
• trigger one or more hardware adjustments to one or more of the vision sensors, or
• trigger an adjustment in an operation of the vehicle.

A non-transitory computer-readable medium comprising instructions that, in response to execution of the instructions by a processor of an edge computing device, cause the processor to:

• obtain a first image captured by one or more vision sensors transported across an agricultural field by a vehicle, wherein the first image depicts one or more plants growing in an agricultural area;
• process the first image to generate one or more agricultural inferences about one or more of the plants growing in the agricultural area, wherein the processing is based on a machine learning model;
• determine a quality metric for the one or more agricultural inferences using one or more of the edge computing devices, wherein the quality metric appraises or quantifies a value or reliability of one or more of the inferences;
• and
• while the vehicle continues to travel across the agricultural field, and based on the quality metric:
• trigger one or more hardware adjustments to one or more of the vision sensors, or
• trigger an adjustment in an operation of the vehicle.