Data-driven agriculture: How IoT could change farming

Azure IoT Edge is powering Microsoft Research’s agricultural monitoring and machine learning platform, called FarmBeats

People often think about the internet of things in an industrial or commercial setting, providing sensors and data to a well-defined process or activity. But there’s one fundamental part of our society that can benefit immensely from IoT technologies, one that’s being left behind because it’s not traditionally seen as a technological activity: agriculture and, more specifically, farming.

AI for Earth

Microsoft’s AI for Earth initiative supports a wide selection of academic and nongovernment organization projects with Azure resources and access to its Cognitive Services APIs. The six-month-old program has already showing interesting results, using machine learning to identify areas affected by natural disasters with satellite imagery and using game theory to predict where to find poachers before they can kill endangered animals.

Microsoft has also worked with the Snow Leopard Trust to improve its image-recognition services, training its neural networks on images and streams of highly camouflaged big cats, helping to deliver a comprehensive survey of endangered animal numbers. It’s research that’s led to new thinking about how to process imagery and how to work with historical data.

FarmBeats: IoT and machine learning for agriculture

Those same machine learning techniques and tools are being combined with IoT hardware and research wireless networks to provide precision metrics and near-real-time information to farmers around the world, as part of Microsoft Research’s FarmBeats project. It builds on many of the key Azure IoT technologies I’ve been writing about, along with new partnerships like support of DJI’s drones in Azure’s IoT SDKs.

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