Research AreasWe cover a broad range of research topics, including Internet of Things, mobile networks, wireless underwater communications and networks, ICT for smart energy grids and wearable technology.
In the past decade we have been studying a broad range of protocols for Internet of Things from data gathering to wireless reprogramming and network control. Our latest research addresses the IoT architecture, its information security, spatio-temporal compression and data mining from various application domains. Our current activities include the study of biomertrics signals from wearable IoT devices.
Research on 5G cellular nets is ongoing to achieve unprecendently experienced bitrates, exploiting massive MIMO technology, machine learning for self-adapting audio/video streaming and intelligent network policies for energy harvesting base stations and devices.
Our group has been developing sensing, data gathering and monitoring technologies for Smart Cities. Our current interest is on data mining from large data sets from real deployments such as large smart parking applications.
We are involved in several research activities for underwater mobile networking. There, our focus is centered around the design of networking protocol (channel access, routing, data gathering, etc). Various experimental activities are also on the way, including simulation, lab and field test of network protocols and at-sea testing.
Our focus is centered around the use of Distributed Energy Sources (DES) in electricity grids. This includes the joint optimization of control, communication algorithms and market rules (energy trading and pricing). Our study also encompasses PLC communication standards and network elements equipped with energy harvesting capabilities.
Droplet microfluidics refers to manipulation and control of little amount of fluids flowing into channels of micro-size scale. We are concerned with understanding microfluidic flow dynamics and their propagation characteristics. These concepts are then used to devise networking algorithms to route droplets in a controlled manner through complex microfluidic networks.
Human sensing technology is being massively introduced in our everyday life. Example are smartphone applications gathering inertial signals, assisted living products and intelligent white goods. The general idea is to measure human data / posture / vital signs or gestures to feed applications. Our group is especially interested in data mining in the contexts of physiological signals and motion tracking.