Software technology developed by the European project CLASS is now being tested on connected cars in the Modena Automotive Smart Area (MASA), an urban laboratory in northern Italy. The CLASS framework is powering smart city applications, from digital traffic signs and smart parking to air pollution simulation and pedestrian avoidance applications.

Allowing big-data analytics under real-time constraints, the CLASS software architecture provides a solution to managing extremely large amounts of complex data (pedestrians, traffic, vehicles, etc.) in real time. Data-in-motion and data-at-rest analytics are integrated into a single development framework, which works with real-time guarantees.

The first outcomes of this smart city use case resulted in different applications, which will improve the traffic and pollution conditions of modern urban environments.

All the software architecture components have been defined and are available to download on the dedicated CLASS GitHub channel: https://github.com/class-euproject

A real smart city use case in Modena

The CLASS software is being evaluated in MASA. Data is already being generated and collected from IoT devices and sensors located in the MASA and on the high-tech equipped Maserati cars.

Initial tests started generating a knowledge base with combined information of the city and the cars, upon which the following advanced smart city applications are being implemented:

• The Digital traffic sign application allows for evaluating and improving real-time traffic conditions by advising on best routes available, for instance in the case of accidents or emergency vehicles.
• The Air pollution simulation estimates the pollution emissions of the moving vehicles in real-time.
• The Smart parking gathers and provides real-time data on the available parking lots within the area.
• The Obstacle detection warns the drivers about pedestrians and objects that appear on their way, even if it is not visible to the car.

CLASS vehicle detecting obstacles in real time

For more information, please visit: https://class-project.eu/