Data sharing is a long-established practice. There are several general-purpose cloud platforms (google, dropbox, etc.) as well as more specialized sharing services such as, for example, those provided by xenodo
ABOUT TRUST AI
The TRUST-AI project aims at bridging the gap between the analytical expressions derived from theory and the numerical models obtained with Machine Learning. A novel paradigm will be developed, whereby humans and machines can collaborate and discover new solutions.
TOTAL FUNDING (€)
PROJECT DURATION (YEARS)
three use casesThe three use cases approached will serve to guide the development of the framework, and will bring important short-term benefits, namely in cancer treatment, last-mile delivery and energy consumption.
Predicting the right treatment moment for patients with slow-growing tumors that only require specific treatment at some point in time (undergoing a wait-and-scan policy).
TIME SLOT SELECTION
Dynamically selecting delivery time slots and corresponding pricing for last mile delivery, trading-off customer satisfaction and operational efficiency.
Predicting daily, hourly and minute energy consumption by managing multiple, real time and distributed data sources.
latest from the projectCommunication & dissemination will ensure excellence and raise public awareness regarding the project. Check here our latest outcomes.
The world of the 4th Industrial Revolution is underpinned by sharing and collaboration approaches. More and more, these are entering the mainstream and gradually putting aside the proprietary mindset and models of the past.
Energy demand forecasting is practiced in several time frames; different explanatory variables are used in each case to serve different decision support mandates. For example, in the short, daily, term building level, forecasting may serve as a performance baseline.
Energy demand is essential when planning for infrastructure and grid investment (TadahiroN., Shigeyuki H., 2010).