The European CLASS project’s cutting-edge software technology is now being tested on connected vehicles in a real-world urban laboratory in the northern Italian city of Modena. For improvement of mobility safety it is expected the future connectivity interactions not only among the autonomous vehicles but also with the smart cities to impose additional non-functional requirements and real time guarantees on big data systems. It is a great challenge for the current big-data analytics software solutions. Smart cities must process massive amounts of heterogeneous data from geographically dispersed sources such as data-in-motion as well as data-at-rest analytics. Data is being generated and collected from IoT (Internet of Things) devices and sensors located in the Modena Automotive Smart Area (MASA) and on three connected technology-equipped Maserati prototype vehicles.
CLASS project funded with the amount of EURO 3.9 Million by European Union’s Horizon 2020 research and innovation programme started in January 2018 and is coordinated by Barcelona Supercomputing Center (BSC) with the participation of Comune di Modena and Università degli Studi di Modena e Reggio Emilia; Maserati; IBM Research, Israel and Atos, Spain.
The developed by CLASS novel software architecture aims by converging and evolving high-performance, low-power embedded and big data analytics computing technologies to provide efficient coordination and distribution of resources along with compute continuum (from edge to cloud computing resources) in order to secure real-time guarantees required by the automotive systems.
‘CLASS is a very challenging project whose objective is to develop a novel software framework for a new generation of highly distributed computing systems with big data analytics and real-time requirements, capable of coordinating computing resources along the compute continuum. BDVA members are at the heart of this innovative project, whose technology will help bring about the smart cities of tomorrow’ says Eduardo Quiñones, CLASS Project coordinator and BSC researcher.
The CLASS project is expected to prove the implementation necessity of big-data systems in smart cities for sustainability, improved services and safe mobility, and thus lay the technological groundwork for trustworthy autonomous vehicles’ introduction. Additionally, the technology applied in CLASS Project could be used as a model for big-data analytics’ application to other application domains that combine edge and clouds, such as manufacturing floors, logistics operations, etc. The CLASS framework is capable to power fascinating smart city applications, from digital traffic signs and smart parking to air pollution simulation and pedestrian avoidance applications.