Research
Resilient Systems for Intelligent Environments
This project seeks to comprehensively investigate these challenges and implement solutions to enhance data quality and develop context-aware systems that can adapt to change. The underlying hypothesis is that applications and models that integrate heterogeneous context data are more robust and accurate in monitoring, predicting, and analyzing. These systems are also more resilient to environmental changes, allowing for more informed decision-making.
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Tactical Networks
Several sources of randomness can change the radio link data rate at the edge of tactical networks. Simulations and field experiments define these sources of randomness indirectly by choosing the mobility pattern, communication technology, number of nodes, terrain, obstacles, and so on.
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Data Fusion on Intelligent Transportation Systems
Urban mobility deals with the movement of people and cargo in urban environments and has become a challenge with the constant growth of the global population. As a consequence of such an increase, more data has become available, which allows new information technologies to improve the mobility systems.
Ler maisPorvir 5g
The expected massive growth of mobile Internet traffic in 5G mobile networks introduces the need to change the operators’ networks. Such networks require a drastic transformation toward open, scalable, and elastic ecosystems that support new types of communication. The PORVIR-5G project will develop and demonstrate a programmable fronthaul and backhaul integrating wireless with optical-packet networks and cloud solutions.
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