Our mission is to study, design and prototype platforms and IoT frameworks supporting the development of pervasive applications relying on decentralized and more autonomic, yet smarter devices.
The IoT is constantly growing in adoption, already representing the technology game-changer for various digitalization processes. Moreover, it is one of the major technological enablers for some groundbreaking technologies, such as Big Data and Artificial Intelligence (AI). However, several architectural and computing challenges related to the IoT need to be effectively addressed to overcome some of its major applicability limitations, such as technology integration issues linked to fragmentation; heterogeneity at all levels of the technology stack (from hardware, through communication, to software; from firmware, through middleware components, to cloud-based services); security and privacy issues that are only exacerbated by the pervasiveness of the technology in some data-sensitive applications in various settings (from consumer, through social, to industrial application domains).
However, to unlock the full IoT potential and widen its adoption it is vital to shift the computing paradigm from a cloud-centric approach where ”dumb” devices communicate with the centralized intelligence, towards a distributed paradigm where devices can autonomically cooperate since the business intelligence can be distributed along the whole IoT infrastructure. Specifically, such intelligence can be hosted either by the IoT device itself (“embedded intelligence”) or, at least, as close as possible to where data is generated, therefore in the IoT gateway located at the network edge (“edge intelligence”), before eventually reaching the cloud (“big data analysis”) in a continuous way, according to the cloud-to-thing computing continuum paradigm. The latter is particularly effective in application domains such as industrial automation, robotics, or autonomous vehicles, only to mention a few.
Fog/Edge-based IoT services, platforms and infrastructures: novel architectures based on flexible, distributed and self-adaptive infrastructures to address and cope with increasing IoT data volumes, performance and responsiveness requirements, privacy and security related IoT issues;
Edge analytics through adaptation of AI techniques to embedded devices: methodologies for the combination and optimization of SoTA AI hardware & software solutions and their adaptation to different application and infrastructural requirements;
IoT Decentralization through Blockchains: distributed ledger technologies combined with capabilities of IoT devices to perform autonomous local data analysis and execute automatic actions enable opportunities for new value creation and capture, transforming process insights into additional business value than simple process monitoring: from product and process traceability, to IoT data monetization and automatic value redistribution, to novel trust management models in value chains.