The distributed and heterogeneous nature of the data sources in High Performance Big Data Analytics (HPDA) applications, as well as the required computational power, is pushing designers towards novel computing systems that combine HPC, Cloud, and IoT solutions (for efficient and distributed computation closer to the data) with Artificial Intelligence (AI) algorithms (for knowledge extraction and decision making). In this context, the EVEREST project addresses the matching problem between application (and data) requirements, and the characteristics of the underlying heterogeneous hardware. Only an optimal match leads to efficient computation. In particular, we forecast that the creation of future Big Data systems will be of course data-driven, but also featuring complex heterogeneous and reconfigurable architectures that must be redesigned or customized based on the nature and locality of the data, and the type of learning/decisions to be performed. The EVEREST project aims at developing a holistic approach for co-designing computation and communication in a heterogeneous, distributed, scalable and secure system for HPDA. This is achieved by simplifying the programmability of heterogeneous and distributed architectures through a “data-driven” design approach, the use of hardware-accelerated AI, and through an efficient monitoring of the execution with a unified hardware/software paradigm. EVEREST proposes a design environment that combines state-of-the-art, stable programming models, and emerging communication standards, with novel and dedicated domain-specific extensions. Three industry-relevant application scenarios are used to validate the EVEREST approach and act as business cases for the project exploitation: (i) a weather analysis-based prediction model for the renewable energy trading market, (ii) an application for air-quality monitoring of industrial sites, and (iii) a real-time traffic modeling framework for intelligent transportation in smart cities.

MUSE GRIDS aims to demonstrate, in two weakly connected areas (a town on a top of a hill and a rural neighbourhood), a set of both technological and non-technological solutions targeting the interaction of local energy grids (electricity grids, district heating and cooling networks, water networks, gas grids, electromobility etc.) to enable maximization of local energy independency through optimized management of the production via end user-driven control strategies, smart grid functionality, storage, CHP and RES integration. Two large-scale pilot projects will be implemented in two different EU regions, in urban (Osimo) and rural (Oud-Heverlee) contexts with weak connections with national grids. These pilots will test and promote the main project concepts: Smart energy system and Local Energy Community. A Smart Energy System is defined as an approach in which smart electricity, thermal, water, gas grids etc are combined with storage technologies and coordinated to identify synergies between them towards maximization of energy independency and reduction of operation costs. The purpose is to reduce energy carbon footprint while meeting energy demands and creating real and sustainable energy islands. To achieve this both physical networks (electricity, natural gas, district heating and cooling, water) and non-physical networks (mobility and citizens/communities) have to interact in order to become a Local Energy Community where inhabitants can act and exchange energy to provide reliable and cheap energy in colaboration. MUSE GRIDS will promote these two concepts not only in pilot projects but also in virtual demo-sites in India, Israel and Spain. Social and environmental aspects of smart multi-energy system transition will be investigated Osimo and Oud Heverlee citizens will be directly involved.The project involves leading EU companies and energy utilites and will be a muse of inspiration for dedicated policy redaction also providing insights to the BRIDGE initiative

ELVITEN will holistically tackle all issues impeding the wide market deployment of EL-Vs, by proposing replicable usage schemes to boost ownership or sharing of all categories of EL-Vs by systematic and occasional urban travellers and by light delivery companies. Existing charge points in the ELVITEN Demonstration Cities, including private ones, will be integrated in a Brokering and Booking service and EL-V charging possibilities will be integrated in the biggest eRoaming platform in the market, to enable EL-V users to charge independently from charge point operators. Sharing services will be set up and supporting policies and incentives will be put in place. ICT tools will be deployed, including a Brokering and a Booking service for EL-Vs and charge points, an EL-V fleet monitoring tool and Eco-Drive app, a Serious Game and an Incentive Management Smart Card. One-year long demonstrations with 383 equipped EL-Vs of all categories in Genoa, Rome, Bari, Malaga, Berlin and Trikala, will allow the collection of a big data bank of trip data and users' experiences and opinions after the trips. The analysis will shed light on the real driving and charging patterns of EL-Vs, on reported problems encountered and on the users’ opinions and perceptions. A Cost Benefit Analysis will evaluate the potential market uptake of EL-Vs. Sustainable business models will be proposed for sharing, rental, parking or charge services for EL-Vs and for the deployed ICT tools. Guidelines to EL-V manufacturers and to Planning Authorities will be prepared and agreements will be signed with another 50 Follower Cities so that they transfer in their own regions the ELVITEN usage schemes.