Interface : Inria centre at the University of Lille demonstration space

Smart Data is an illustration of variable data analysis based on advanced statistical methods, drawing partly on the software program MixtComp. The software shows how to get the most out of a large data set (big data), enabling this to be classified and interpreted and allowing predictions to be made.

Demonstration developed by the Modal project team, in association with Alstom and HDFID. Open data sources: Atos, Insee/MEL, J.C. Decaux and SNCF.

My Local Info

Many data are collected everyday via our online interactions. The data collection generates innovative services based on machine learning but also raises major problems about users private lives.
In response to these issues, Magnet project-team developed a protocol in order to calculate the data average of a high number of users, while assuring this data does not come out of the initial device, and the average being calculated by a central server.

Demonstration developed by the Magnet project team, in association with the University of Lille

This demonstration gives one possible example of how a soft robot could be used: inspection. The head of the robot is equipped with a camera used to inspect different areas within the white box. The robot's capacity to change shape means it is able to get around obstacles, while its flexibility makes it less likely to cause damage to its immediate environment, and its 10 motors ensure enhanced dexterity.

Demonstration developed by the Defrost project team, in association with the University of Lille.

Involving the use of a touchscreen tablet, this demonstration highlights latency reduction for interactive systems. It demonstrates a method that can be used to compensate the latency between the movement of a user’s finger and the movement of an object on the screen in real-time, improving interaction efficiency and the subjective preferences of users.

Demonstration developed by the Loki and Valse project teams, in association with the University of Lille within the framework of the ANR TurboTouch.

It takes an engineer 3.5 months to read a million lines of code. And while he's doing that, he can’t do anything else. He can’t understand its structure or identify certain properties. Thanks to these visualizations in these two posters, or other visualizations, the Rmod team offers a way to understand various aspects of a software application (architecture, dependencies, authors, hierarchy and inheritance, quality, bugs, tests...)

Demonstration developed by the RmoD project team, in association with the University of Lille.