AI Case Study
Farmers are able to quickly identify issues such as crop stress and disease and pest infestation on heatmaps enabled by drones and machine learning
Microsoft has partnered with drone maker DJI to provide farmers greater insight into their own fields using data and artificial intelligence. They aim at eliminating the days farmers spend walking around their fields trying to spot issues in their crops. By using drones and machine learning their solution enables farmers to get all the information they need to make the important decisions for their field through a heatmap, generated from ground-based sensors, tractors, cameras and aerial imagery.
"A new partnership between Microsoft and leading drone maker DJI builds on the work both companies are doing with data and agriculture that could make it easier and more affordable for farmers like Stratman to quickly get the information they need to make crucial decisions about soil moisture and temperature, pesticides and fertilizer. Hours and days spent walking or driving the fields to try to detect problems can be eliminated.
Microsoft’s FarmBeats program sends large amounts of data from ground-based sensors, tractors and cameras to a computer on the farm using TV white spaces, a type of internet connectivity similar to Wi-Fi but with a range of a few miles. TV white spaces are unused TV broadcast spectrum, which is plentiful in rural areas where most farms are located, and where standard internet connections are often spotty.
DJI’s PC Ground Station Pro software provides on-the-fly generation of orthomosaics, or stitched aerial imagery, which are used by the FarmBeats machine learning algorithms running on the Azure IoT Edge to create detailed heatmaps. Those heatmaps enable farmers to quickly identify crop stress and disease, pest infestation or other issues that may reduce yield. The maps are transmitted using TV white space technology to the Azure IoT edge device located on the farm.
The FarmBeats program uses DJI’s commercially available Phantom 4 Pro drone for the project at the farm Stratman manages, at other FarmBeats locations in the United States – New York, California and North Dakota – and in India. For larger farms, where there is a need for increased battery life and advanced payloads like multispectral sensors, the team is using DJI’s Matrice 200."
Sean has used the heatmaps to help with everything from his planting strategy – for example, whether the soil temperature is ripe for seed germination – to learning where beavers had created dams along a lengthy drainage ditch, creating flooding in some of his fields.
New machine learning algorithms process and analyze the data, and run on the Azure Internet of Things (IoT) Edge, which delivers cloud intelligence locally, on the edge, if you will, of a larger computing network. In Stratman’s case, the “edge” is in the barn, a seemingly old-fashioned setting for a high-tech solution to help solve serious problems.
"Since 2011, farmer Sean Stratman has grown kale, cauliflower, broccoli and squash in Carnation, Washington. Then, a few years ago, he added a new crop to his bounty: knowledge, using drones and the intelligent edge to get near-real-time information about issues like soil moisture and pests. It’s the kind of information that is not only helping him, but could benefit farmers around the world."
data from ground-based sensors, tractors and cameras, aerial images and drone footage