AUTHOR=Dong Younsuk , Werling Benjamin , Cao Zhichao , Li Gen 

TITLE=Implementation of an in-field IoT system for precision irrigation management

JOURNAL=Frontiers in Water

VOLUME=Volume 6 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/water/articles/10.3389/frwa.2024.1353597

DOI=10.3389/frwa.2024.1353597

ISSN=2624-9375

ABSTRACT=As climate change has impacted agriculture and water security issues emerge, proper irrigation management becomes more important to overcome the challenges. IoT (Internet of Things) technology has been utilized in agriculture to allow collecting field information and share it through websites in real time. This paper discusses the effort to develop an IoT-based sensor station and user-friendly website and smartphone app for irrigation management. In addition, the demonstration of the IoTbased sensor station and its effectiveness are discussed. Before deploying the sensor station, soil moisture sensor calibration was conducted in a laboratory experiment. Overall, the calibrated soil moisture sensors met the statistical criteria for both sand (RMSE = 0.01 cm 3 /cm 3 , IA = 0.97, MBE = 0.01) and loamy sand (RMSE = 0.023 cm 3 /cm 3 , IA = 0.98, MBE = -0.02). This paper focuses on case studies from corn, blueberry, and tomato fields in Michigan, USA. At the corn and blueberry fields, the evaluation of farmers' irrigation practices using IoT-based sensor technology was focused. At the tomato field, a demonstration of automation irrigation was conducted. Overirrigation has been observed using the IoT-based sensor station in some fields that have sandy soil and uses a drip irrigation system. In the blueberry demonstration field, the total yield per plant (P-value = 0.025) and 50-berry weights (P-value = 0.013) were higher with the recommended irrigation management than the grower's existing field. In the tomato demonstration field, there were no statistical differences in the number of marketable tomatoes (P-value = 0.382) and weights (P-value = 0.756) between the grower's existing method and recommended irrigation strategy However, 30% of less water was applied to the recommended irrigation strategy plot. Thus, the result shows that the IoT sensor-based irrigation strategy can save up to 30% on irrigation while maintaining the same yields and quality of the product.