DEEPaaS - Deep Learning for everybody
The key concept proposed in the DEEP Hybrid DataCloud project is the need to support intensive computing techniques that require specialized HPC hardware, like GPUs or low-latency interconnects, to explore very large datasets.
CLASS -Edge an d Cloud Computation: A Highly distributed Software for Big Data Analytics
Current trends towards the use of big data technologies in the context of smart cities suggest the need for developing novel software development ecosystems upon which advanced mobility functionalities can be developed.
AGORA - Unlocking data-driven business potentials for cross-sectorial industries
AGORA is the B2B data platform broker of Atos to connect Data Providers and Data Consumers, facilitating the access, acquisition and trade-off of Connected Vehicle and Smart Home data under the standardized data model (CIDM).
ELASTIC: A Software Architecture for Extreme-ScaLe Big-Data AnalyticS in Fog CompuTIng ECosystems
Big data technologies are nowadays being integrated in systems that are required to process a vast amount of information from geographically distributed data sources.
Traffic micro-simulation models in city centres
Freight delivery within the city has a great impact on traffic flow and is responsible for traffic congestion to a high extent. Central areas of the city face a number of situations every day:
Emission Reduction System
More and more vehicles are connected to the Cloud.
DataBench Toolbox
The goal of the DataBench Toolbox is to provide a way of reusing existing big data benchmarking efforts under a common framework, providing therefore a way to select, download and homogenize technical and business indicators.