Soilless growing systems inside greenhouses, known as controlled environment agriculture, promise to advance the year-round production of high-quality specialty crops, according to an interdisciplinary research team at Penn State. But to be competitive and sustainable, this advanced farming method will require the development and implementation of precision agriculture techniques. To meet that demand, the team developed an automated crop-monitoring system capable of providing continuous and frequent data about plant growth and needs, allowing for informed crop management.
"Traditionally, crop monitoring in controlled environment agriculture soilless systems is a critical, time-consuming task requiring specialized personnel," said team lead Long He, associate professor of agricultural and biological engineering. "And traditional crop-monitoring methods do not allow frequent data collection to capture plant growth dynamics throughout the crop cycle. Automated crop-monitoring systems allow continuous monitoring of the plants with frequent data collection and a more efficient and informed management of the crop."
In findings published in Computers and Electronics in Agriculture, the researchers reported that an integrated "internet of things," artificial intelligence (AI) and a computer vision system tailored for controlled environment agriculture soilless growing systems, enabling continuous monitoring and analysis of plant growth throughout the crop cycle. An internet of things - often referred to as IoT - is a network of physical objects that can connect and exchange data over the internet, linking devices that are embedded with sensors, software and other technologies.
