Research projects

The aim of the project is to continue the cooperation between Dr. Segata and Electrolux, in particular by working on the classification of IoT devices.

The potential of mmWave technology (30 GHz to 300 GHz) for future mobile networks led to significant research investments, and motivated the European Commission to recommend opening up parts of the mmWave spectrum for broadband services.

In this MSCA European training network, we train 15 doctoral students in different aspects of mmWave communications, networking, sensing, and applications, with the objective to create a cohort of experts in mmWave technology for the academia and industry.

RECAP is a Horizon2020 project that provides novel methodologies, tools and an enabling workflow for automated infrastructure deployment, monitoring, and analytics that result in lower costs and better quality of service.

Underwater acoustic communications (UWAC) is increasingly perceived as a cost-effective ocean exploration and monitoring means. However, while carrying out these tasks, UWAC devices are left unattended over long periods of time and may become vulnerable to external attacks. The recent introduction of standards protocols for UWAC makes these attacks more viable.

In SAFE-UComm, we explore new ways to secure UWAC against attackers. Our solutions eliminate the need to change existing modems or include encryption systems, and rather provide a protective layer that can be added to any modem, offering a practical solution to underwater cybersecurity.

The aim of SECEDA is the small-scale, real-world development and testing of cooperative driving maneuvers and vehicular communication protocols through a cooperative driving fleet composed of model cars. SECEDA will work the development and the testing of new Multi-access Edge Computing (MEC)-based remote control. This idea exploits MEC cloud computing to bring the control of the vehicles to the edge, bringing great adaptation potentials to variable road traffic and communication conditions. The testbed will also pave the road to other research studies, spanning from collective data sensing and distributed embedded machine learning.

SYMBIOSIS provided a mature, cost effective autonomous opto-acoustic prototype for the characterization, classification, and biomass evaluation of six target pelagic fish that are important to the fishery industry and that reflect on the health of the environment. SYMBIOSIS is devised as a blend of acoustic and optical components, including an active underwater acoustic array, optical cameras and strobes, control electronics, embedded processing, and batteries.

With the increase of marine activity, protecting marine infrastructures from terrorist threats has become a main concern. We propose to develop and demonstrate a novel prototype for reliable, real-time detection of diver and mines. Our system combines acoustic remote detection with verification using pattern recognition on underwater imagery. First, we analyse the acoustic reflections to localize a target that fits the pattern of a diver or a submerged mine. Then, in case the release or presence of a mine is suspected, a vehicle is dispatched to first inspect the target through its optical and sonar systems, and then to send the processed information back through underwater acoustic communication.