Smart farming employs hardware (IoT) and software (SaaS) to capture the data acquired through various sources (historical, geographical and instrumental) in the management of farm activities and make sense out of it.
Feugiat accumsan lorem eu ac lorem amet accumsan donec. Blandit orci porttitor.
Earth observations (EO) data are key inputs into the kinds of analyses and decisionmaking processes that are critical to promoting smart agriculture.
Satellite-based localization solutions have become quite mature and the GNSS receivers have found numerous applications in agriculture.
The ability to gain insights from data, create algorithms and invent new technologies lies on the combination of shared information, smart technology and ambitious innovation.
The most popular applications of Artificial Intelligence in agriculture are robots, predictive analytics, crop/soil monitoring, computer vision & deep-learning algorithms.
Internet of Things in agriculture involves sensors, drones and robots connected through internet which function automatically and semi automatically performing operations and gathering data aimed at increasing efficiency and predictability.