Eden Library is the first digital platform to host agri-food image data and Artificial Intelligence algorithms which allow the development of Artificial Intelligence and Machine Learning tools to solve agricultural field problems such as pest detection, pest control, sorting and yield prediction.
The aim of Eden Library is to bridge the gap between image processing technologies and real field problems. Over 7,000 image data are already available in the platform related to plants and crops with a variety of characteristics/symptoms (healthy, infested by weeds or pests, malnutrition). Data collection is performed with state-of-the-art equipment and cameras, such as the use of multispectral and colour-RGB cameras, as well as ground-based sensors and drones. The image data provided are enriched with annotated data and are accompanied by useful metadata to maintain the validity of the diagnosis of the problem while the supervision of data by scientifically trained partners and industry experts, including agronomists, phytologists, entomologists, and AI experts.
The platform targets a wide range of stakeholders in the agri-food sector because of the possibilities it provides in utilizing the image data at different stages of production, from the selection of seed varieties to product sorting in the post-harvest stage. Typically agro-technology companies, phytochemical companies, researchers as well as individual producers and agronomists can use the digital platform to access image data and services that meet the challenges of different crops.
Eden Library is inspired by the need for more quality image data that will allow the development of computer vision applications throughout the agri-food value chain and aspires to become the largest image database in agri-food. The goal is to build a strong community in the field of Artificial Intelligence in agriculture and to foster research and business development in the field.
Eden Library platform was initiated by EdenCore, one of the first spin-off companies of the Agricultural University of Athens. The company was “born” in the Laboratory of Agricultural Engineering, which specializes in precision agriculture, robotics and computer vision. The company has reached the top 10 business ideas, among 264 submitted proposals, in the 11th Innovation Competition “NBG Business Seeds” organized by the National Bank of Greece.