The use of information technology in agriculture has brought significant benefits to producers, such as increased profits and better product quality. Modern technology applications in agriculture rely on the use of unmanned aerial vehicles (UAVs) and wireless ground sensors to provide real-time information about fields and crops. In Europe, these techniques, referred to as Smart Farming (SF), are still in their infancy despite the large agricultural production of a wide range of products. For this reason, in this study, we experimented with the technologies of SF in the cultivation of Greek saffron, a rare spice with many uses. For this reason, and also because its harvest is quite labor intensive, it is one of the most expensive spices. Since the field of SF is relatively new and has not yet been used for this particular crop and area, the equipment and methods of data processing were selected experimentally after a review of the literature. The aim of the study was to remotely acquire image data of the crops and train a machine learning model to detect important objects such as saffron flowers and weeds.
