Feeding a growing population, projected to hit 9.6 billion by 2050, is a huge challenge for agriculture, especially with limited water and climate change. To sustainably meet the increasing food demand, digital tools and Internet of Things (IoT) technologies are needed, in which investments in smart agriculture by improving soil health, optimizing water use, and monitoring weather can boost productivity and food quality while protecting the environment. This paper presents Digital Twin for smart agriculture using LoRaWAN’s long-range, low-power connectivity to monitor soil conditions in real time. Soil sensors transmit data to the Eclipse Ditto platform, where the Digital Twin processes and replicates sensor behavior, enabling precise and efficient monitoring. The system addresses calibration drift by using predictive models to detect inaccuracies and dynamically recalibrate sensors remotely based on soil type, improving accuracy even in resource limited settings. This highlights how advanced digital tools can redefine agricultural practices by integrating Digital Twins with LoRaWAN technology.
Mehda, A., Pagano, A., Giuliano, F., Croce, D. (2025). Digital Twin of Smart Agriculture Sensors through LoRaWAN Connectivity. In 2025 IEEE Smart World Congress (SWC) (pp. 874-879) [10.1109/SWC65939.2025.00143].
Digital Twin of Smart Agriculture Sensors through LoRaWAN Connectivity
Mehda Adem;Pagano Antonino;Giuliano Fabrizio;Croce Daniele
2025-01-01
Abstract
Feeding a growing population, projected to hit 9.6 billion by 2050, is a huge challenge for agriculture, especially with limited water and climate change. To sustainably meet the increasing food demand, digital tools and Internet of Things (IoT) technologies are needed, in which investments in smart agriculture by improving soil health, optimizing water use, and monitoring weather can boost productivity and food quality while protecting the environment. This paper presents Digital Twin for smart agriculture using LoRaWAN’s long-range, low-power connectivity to monitor soil conditions in real time. Soil sensors transmit data to the Eclipse Ditto platform, where the Digital Twin processes and replicates sensor behavior, enabling precise and efficient monitoring. The system addresses calibration drift by using predictive models to detect inaccuracies and dynamically recalibrate sensors remotely based on soil type, improving accuracy even in resource limited settings. This highlights how advanced digital tools can redefine agricultural practices by integrating Digital Twins with LoRaWAN technology.| File | Dimensione | Formato | |
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