Artificial Intelligence can really help humanity if its put to good use in farming. But then, there are many challenges in the farming space due to lack of data and cost-effectiveness of AI tools.
Let’s look at how AI is being used in farming and agriculture globally.
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An Apple picking robot which can work 24 hours, working non-stop, works on the same technology on which the most modern self-driving vehicles currently work on, LIDAR.
The robot does not even damage the trees or fruits and not only pinpoints the fruit, but also it's ripeness with computer vision algorithm.
To facilitate the use of these robots, even the farms and it's Apple trees are being 'converted', shortened and flattened trees are the new order of the day.
"Picking fruit is heavy work.To pick a hectare of apples involves pickers collectively doing something like 5 vertical miles going up and down ladders. With mechanization and robotics, it allows us to take out a lot of the heavy work.”
Feed is the single biggest cost in fishing operations, averaging at about 60-70% of the total cost.
With the climate change triggering different patterns each year, the fishes are hard to come easy, which means more and more use of feed, when the precise location of fishing shoals is based on trial and error or traditional methods.
Now Japanese companies are employing AI technology in drones, which can spot the shoals of fish and can even estimate their size and volume, giving the fishing farmer an instant estimate of the value of their catch, with which they can determine if the fish is worth the trouble and cost or not!
Timely detection of onset of an infection in crops could mean safeguard against a disappointing loss of crops. While small farmers could still rely on visual infection, for large farms it is not possible.
That's where drones combined with Computer Vision are helping farmers in detecting areas of a crop field which are infested with disease and then apply remedial measures on a timely basis.
Specially useful for crops which have a high density of plants per acre, where the chances are that many a times some individual plant would escape the routine normal eyesight inspection.
Vertical indoor farms are future of farming, not only because they can resist the vagaries of nature, but also because they require much less land and water usage.
Combining it with Machine Learning, Computer Vision and Robotics, in some cases the yield has been found to increase by 100 times.
This talk describes how to build an AI farming technology infrastructure, tools and techniques.
ICRISAT and Microsoft together have developed a sowing application which forecasts the optimum sowing date for the famers of Andhra Pradesh.
The application uses Cortana Analytics to determine the sowing date based on weather and soil conditions.
The pilot project indicated an average increase of 30% in per hectare yield with the use of application.