How the internet of things and machine learning are automating agriculture
A new generation of farmers is tapping the internet of things and machine learning to operate self-sustaining urban farms with minimal supervision
By Aaron Tan
Computer Weekly
July 21, 2021
Excerpt:
Xie said the smart farm, located at a rooftop carpark in Singapore, is also equipped with sensors that monitor the pH and electrical conductivity levels of water. Among the sensors, which are connected to a Lora low-power wide area network, is a dozer that automatically releases acidic or alkaline nutrients to maintain optimal pH levels.
Whereas the farmers of old had to physically inspect their crops, AbyFarm’s agronomists and farmers can do so remotely using video cameras and image recognition technology to identify crops that might be succumbing to 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,” said Xie, adding that agronomists will also advise farmers on taking corrective actions to prevent disease or restore the health of their crops.
Like any machine learning system, AbyFarm’s algorithms get smarter over time. Each time a crop is affected by disease, data about the occurrence and corrective action is fed into the system, enabling its algorithms to formulate solutions for other farmers with similar crop issues – without consulting an agronomist.
With that, said Xie, even those who are new to the field can use the system to guide them on treating diseased crops, which can be isolated from other crops to prevent cross-infections.
