Focus area of Data Science

Edge AI

Computational intelligence and network science at the edge (of the Internet of Things)


Connectivity is, already now, possible between virtually anything. Internet of things relies on a multitude of technologies to help anything communicate and share its own data. However, it is the local computational intelligence that will allow smarter things generate more valuable and actionable data. At the intersection of artificial intelligence, network science and internet of things, this working group strives to research and build things that are able to autonomously act and share data, self-organize and interact with their environment.

Autonomous evolution, self-orchestration and global interconnection of everything are features of real ecosystems. An ecosystem of IoT devices is capable of self-organizing in clusters, competing for resources with each other, gaining new capabilities and devising new strategies to boost their own survivability. In such a system, analyzing data is the key to achieving awareness of the local environment and detecting internal and external threats. The interaction of such an ecosystem with the human society, business models and applications will define a dynamic set of rules of operation.

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Research challenges

In our research we investigate the architecture of global self-evolving IoT systems to attain swarming, competing and behavior emergence characteristics. We also develop methods to manage risks in distributed and interconnected IoT systems, resulting in designing security measures and procedures that provide immediate security advice to customers and network managers. Another line is building data mining methods and tools for automated detection of emerging patterns in data streams and interoperability of IoT systems. Finally, we design future-proof autonomous and dependable networks ready to deal with massive scale and traffic, complexity and security challenges.

Project examples

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