Turf Research: Improving Irrigation Management in Turfgrass and Landscapes through Next Generation Soil Moisture Sensors, Underground Wireless Networks, IoT,
LoRa Technology,
and Artificial Intelligence 

Lead Researchers: Jay Ham, Tony Koski, Qian Yaling, Cathie Lavis,
Dale Bremer, Jack Fry, Jared Hoyle, Ambika Chandra, Benjamin Wherley

Industry Partners: The Toro Company, AeXonis 

The need: Improving turf and landscape irrigation management systems using internet-of-things (IoT) sensors, machine learning, and cloud-based systems can make technologies cheaper and more user friendly. 

 The goal:  Researchers conducted some of the first field tests specifically designed to improve irrigation management using IoT sensor technology coupled with machine learning (A.I.) and cloud computing on turf sites in Colorado and Kansas, using both warm and cool season turfgrass varieties. A now-patented, low-cost, wireless soil sensor (SMS) network for managing irrigation was also developed and evaluated.  

 Impact:  The team’s new low-cost soil sensor measures water content and soil temperature and contains a novel temperature-controlled chamber that quantifies   thermal response. The sensor was successfully calibrated against gravimetric samples on fairways at three golf courses over the summer season and will be tested in different settings in 2021. A novel IoT cellular carrier board reads the soil moisture sensors and sends the data to the cloud via a LoRa network installed with the help of industry partner AeXonis. The team invested considerable effort to make the system low power so it can operate all spring, summer, and fall on a small battery pack – no solar panel required! The entire carrier board system has been designed to fit in a small 6-inch valve box normally used in irrigation system installation.