Cyber-agricultural systems draw from mathematics, engineering and computer science, building on cyber-physical systems that have revolutionized industries like manufacturing, aerospace engineering and transportation.
Sarkar, a professor of mechanical engineering, worked on cyber-physical systems in industry before coming to Iowa State in 2014. He soon met Singh, who was experimenting with using machine learning and artificial intelligence to improve variety development for crop production. The two quickly realized the potential of adapting cyber-physical approaches for agriculture.
Recently, they reviewed the new field they helped launch for the journal Trends in Plant Sciences. With co-authors from around campus and the country, they describe how CAS is complementary yet distinct from precision and smart ag and outline three main components defining the CAS framework:
- Data absorption from sensors and cameras of many kinds affixed to satellites, drones and robots that collect a multitude of data on plants, weeds, insects, diseases or animal behavior, along with information on landscape position, weather and environmental conditions.
- Modeling using the data to answer questions and make predictions.
- Decision-support applications based on the modeling results informing digitally based tools designed to answer specific questions, such as ‘What is this disease?’ and “What are recommendations for its management?’
Along with revolutionizing the practice of agriculture, CAS ushers in new tools and a new suite of acronyms, from SCFs (smart connected farms) to DTs (digital twins, for computer fieldscapes that reflect real farms) and IoT (the internet of things).
Source : iastate.edu