The program is concerned with raising the level of CIMA Research Foundation high-tech services already available and creating new ones, so as to create an advanced back-bone for end-to-end solutions, from monitoring networks to platforms for sharing data and modeling results.
Therefore, the program intends to harmonize the work done on the architectures of all platforms, consolidating them in operational use among existing stakeholders, but also increasingly disseminating them. Regarding the more strictly ICT part, the program aims to increase knowledge and capabilities on a variety of fronts, in synergy with the programs Intelligent Data Use in a Changing Climate and Impact-Based Early Warning Systems on Climate Threats programs, by carrying out technology scouting and research on new IT architectures that can respond better and with greater speed and security to the needs of stakeholders in the different projects. In addition, we will pursue research and activities in the area of Artificial Intelligence, starting with the development and training of simple machine learning models that flank physically based models (meteorological and hydrological) to make their data assimilation processes more efficient.
The program also carries forward the Acronet paradigm, which brings together activities aimed at the implementation of technological solutions for local monitoring of environmental parameters, proposing itself as a model for the design, implementation, deployment, and field installation of environmental monitoring systems, based on Open Hardware concepts. In this area, it is intended both to improve the hardware equipment and software systems necessary for measurements and data fruition, and to extend the scope beyond simple monitoring, in order to also allow access to remote environmental monitoring, to all those to whom this is not possible today.
Project support on the monitoring front also includes further development of ‘expertise’ and specialized solutions in the use of drone-taken imagery and video, particularly for damage estimation from floods, fires and other natural disasters.