Precision agriculture for a rural area with limited connectivity

Taken from Microsofot presentation

Among many hyped agriculture technologies under industry 4.0 umbrella I’ve ever seen, this Microsoft solution, namely FarmBeats, appropriately addresses Indonesia’s geographical challenges.

As a solution architect, what I like the most from the presentation is that how they synthesized the problem and designed a solution for it.
Here are the summaries of the challenges:
1) limited connectivity from the farm (sensors) to farmer’s home/office (few miles away, multipath propagation due to hill/trees). Solution: extend WiFi signal using empty UHF/VHF channels which have much better propagation & are abundant in rural areas
2) limited resources (sensors) to portrait the entire field. Solution: combine readings from only a few sensors and images from a flying moving object into a machine learning model’s inference to predict unmeasured points in order to build a complete precision map 
3) high-cost aerial imagery. Solution: instead of an expensive drone, “helium” balloon equipped with smartphone/power bank attached to moving object (such as walk, motor, car, bike, tractor) is used
4) limited Internet of farmer’s home/office. Solution: edge approach. The trained model stays local to infer real-time data, data stored locally and sent in a compressed format to the cloud for model improvement (retrain), web server instance/cache replicated from one in the cloud stays local to serve multiple services, such as irrigation, pest infection, fertilizing, etc.

Here is the full video from Microsoft.

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