FarmBeats

Democratizing AI for farmers around the world

a farm with data overlay
"As I'm starting to understand the value of this data and all of the possible ways I can use it … I'd say it's pretty much priceless.”
Sean Stratman

About FarmBeats

Several studies have demonstrated the need to significantly increase the world’s food production by 2050. However, there is limited amount of additional arable land, and water levels have also been receding. Although technology could help the farmer, its adoption is limited because the farms usually do not have power, or Internet connectivity, and the farmers are typically not technology savvy. We are working towards an end-to-end approach, from sensors to the cloud, to solve the problem. Our goal is to enable data-driven farming. We believe that data, coupled with the farmer’s knowledge and intuition about his or her farm, can help increase farm productivity, and also help reduce costs. However, getting data from the farm is extremely difficult since there is often no power in the field, or Internet in the farms. As part of the FarmBeats project, we are building several unique solutions to solve these problems using low-cost sensors, drones, and vision and machine learning algorithms.

Video

FarmBeats tracks soil, moisture data 24/7 FarmBeats, a new agriculture research project developed by Microsoft, uses solar-powered white space-based Internet connectivity to record soil temperature and moisture levels and track them with cloud-based computing models. FarmBeats enables data-driven farming in remote areas through the use of inexpensive monitoring equipment, including cameras, to help increase the food yield of farms. Learn more: http://research.microsoft.com/

Journey

Ranveer Chandra is the principal researcher behind FarmBeats, a data-driven farming project designed to help increase farm productivity and reduce costs. FarmBeats highlights something essential for our future: AI doesn’t replace human knowledge; it augments it. In this case, data from low-cost sensors in soil and drones with machine learning algorithms work with farmers’ knowledge and intuition to help them gather and parse data about their farms – informing what, when, and where to plant in order to drive the highest-possible yields and reduce costs.

In just two and a half years, the team behind FarmBeats has iterated on their 2015 Hackathon prototype and created a working system melding technology with traditional agricultural practices.

person testing soil

Team

team of farmers and iOT

Ranveer Chandra, Akshay Uttama Nambi, Anirudh Badam, Ashish Kapoor, Chetan Bansal, Kenneth Tran, Manohar Swaminathan, Raghuram Lanka, Ranveer Chandra, Sudipta Sinha

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