How AR technology can help farmers stay relevant

Augmented reality(AR) and robotics are closely related . Both model their environment to some degree. Robotics uses that model to guide the behaviour of a machine , whereas AR uses it to provide an enhanced sensory experience to a human.

 

The exact nature of that enhanced experience is bounded only by available sensory, computational, and display (audio, haptic) hardware, and by how the data gathered can be usefully transformed into overlays that argument the natural perception of the human user. What is useful is a function of both the content of those overlays and the latency, how much lag time is introduced by the computational involved in generating the overlays. Faster computational hardware can produce more detailed overlays with the same latency or the same overlays with lower latency than slower hardware.

 

 

One important application for AR is making it easier for a human to work in collaboration with robotic hardware. For example , a robot might provide the path it intends to pass, and that information might be converted in an AR display into highlighting anything occupying that space.Or perhaps a machine wants to direct the attention of its human counterpart to some particular  element of the environment, say one specific plant . That too could be highlighting in the display.

 

While these examples only scratch the surface of what is possible, they do serve to illustrate that the content of AR overlays need not be generated entirely from data gathered by sensors attached to the display itself, but not limited to other nearby devices. Those sources might include aerial or satellite imagery and information from databases. In the farming context, they might include 3D soil maps produced from core samples.

 

 

Examples of overlays that might be useful for a farmer include thermal imagery, current soil moisture content, soil surface porosity and water absorption capacity, exaggerated vertical relief and what to expect in the way of runoff and resulting erosion for various precipitation scenarios , highlighting all plants of a particular species, all plants exhibiting bare soil, the presence, activity, and impact of various types of animals. This could go on and on.

 

Machines may be better at doing particular manipulation of data, but they are not so good at asking meaningful questions. For this reason, the combination of human and machine is more powerful than either alone.

 

It’s still very early days in AR, and there’s a great deal of room for improvement . One development that is likely to occur sooner rather than later is voice operations. With voice control, a  farmer should be able to walk through a field. For most, this will be a  more intimate and far richer connection to their land than what they currently experience.

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