CALLISTO

Vision

CALLISTO aims to bridge the gap between Copernicus Data and Information Access Services (DIAS) providers and application end-users through dedicated Artificial Intelligence (AI) solutions. It will provide an interoperable Big Data platform integrating Earth Observation (EO) data deriving from the Data and Information Access Services (DIAS) with crowdsourced, geo-referenced and distributed data from various sources. All data will be served in Mixed Reality environments.

CALLISTO will be pilot-tested in real environment, providing geo-location based services in applications relevant to policymaking, water management, journalism and border security.

The main objectives of CALLISTO are to:

• Integrate with Copernicus data already indexed on DIAS platforms using High-performance computing (HPC) infrastructure for enhanced scalability
• Complement the available data with Galileo signals from a mobile application and video recording on Unmanned Aerial Vehicles (UAVs), web and social media data linking them with open geospatial data, and in-situ sensor data
• Ensure availability and the quality of annotated datasets using clustering techniques and Generative Adversarial Networks (GANs)
• Generate Mixed Reality visual content through the development of 3D-models constructed from satellite data
• Retrieve additional in-situ information from geo-referenced video content to validate and further enrich the outcomes of the Deep Learning analysis of Copernicus imagery
• Develop and optimize air quality forecasting with Machine Learning techniques using HPC infrastructure
• Use ontologies to extract Named Entities from textual content that is present in crowdsourced information, so as to be linked with EO data

Project Consortium

The formed consortium has been shaped of sixteen (16) partners from eight (8) countries.The project combines different key players and organisation in order to ensure a multifarious cooperation.