How IoT and Machine Learning Will Impact Greenhouse Growers
Internet of things (IoT) and machine learning are becoming more prominent in our world. There is now a new generation of farmers who are putting forth this new technology to help aid in agricultural production.
One such grower is Phoebe Xie, Director and Co-Founder of AbyFarm, an agrotechnology startup based in Singapore.
Xie has been working to build smart hydroponic farms with IoT sensors and video cameras.
“To run a self-regulating farm at optimal temperature with optimal water and nutrient supply, and to control the quality and taste of vegetables and fruits, we need IoT sensors,” Xie told Computer Weekly.
Xie’s farm is located on a carpark rooftop and is equipped with pH sensors that also look at the electrical conductivity of the water. These are all connected to a Lora low-power wide area network. Xie also installed a dozer, allowing the automatic release of acidic or alkaline nutrients when pH levels are too high or low.
Farmers back in the day had to inspect crops physically, but Xie can do her monitoring remotely with cameras and image recognition software. The software is trained to identify crops that may be dying from disease.
“If the image recognition finds that a plant is likely to be sick, the farmer will be alerted to go onsite to check how the plant is right now,” Xie says.
Her machine learning software may be smart now, but it is constantly learning as it goes. Each time a crop is diagnosed with a disease, the diagnosis and corrective action data is recorded in the system’s database. This gives the algorithms the ability to come up with new solutions for other farmers facing similar problems.
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