Using the IIoT to yield better tomatoes

August 28, 2017

Using the IIoT to yield better tomatoes

Students will use the IoT to track the conditions and movement of produce from the tomato plant to the end location, with a goal of improving the quality, yields, and profitability of that produce.

Last year, as part of our IoT Roadshow, I interviewed Michael Murray, General Manager of Analog Devices’ Industrial Sensing Group. The interview was titled Get into the application to really understand it. At the time, we were talking about autonomous sensing, basically describing what it is and how it works. The part that Michael and I discussed that didn’t get included into the video is the farming application that the company is involved with.

To be honest, I had forgotten about this very cool application until recently, when an announcement crossed my desk that says, “Analog Devices’ monitoring initiative aims to improve crop quality and yields and boost profitability of local farmers.”

According to the announcement, ADI has “entered into a collaboration with the Cornucopia Project and ripe.io to explore the local food supply chain and use this work as a vehicle for educating students at ConVal Regional High School in Peterborough, N.H., and local farmers on 21st century agriculture skills.”

Here at Embedded Computing Design, we talk a lot about Industrial IoT. In most cases, we refer to manufacturing, building automation, robotics, smart cities, and so on. But the agriculture topic is becoming extremely popular in many parts of the country. I’ve heard examples of tomato farming and grape harvesting. This announcement from ADI shows that the proof is in the pudding…well, maybe the tomato paste.

Students will use the IoT to track the conditions and movement of produce from the tomato plant to the end location, with a goal of improving the quality, yields, and profitability of that produce. Analog Devices will provide a prototype version of its sensor-to-cloud crop monitoring solution, which can measure environmental factors that can affect a crop, like water, fertilization, ripeness, etc. That solution is combined with a near infrared (NIR) miniaturized spectrometer that conducts further analysis.

You have to love it when a project like this comes to fruition (ouch!).

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IoT