Marine and Environment: The Internet of Floating Things
Led by Georgios Sklivanitis, Ph.D.
This project focuses on the design, development, and evaluation of small, lightweight, low-power, low-cost hardware and open-source software frameworks for secure, high-rate marine data acquisition. The objective is to transform ocean observation into a new era of persistent and pervasive measurement. A major challenge to understanding the ocean at scale is cost. New oceanographic measurement capabilities have enabled new ways to observe, monitor, and predict ocean processes, but these instruments generally rely on expensive, bespoke, one-of-a-kind designs. The next frontier of ocean networking will see the deployment of large-scale buoy and drifter-based mesh networks, with an equal emphasis on secure high-speed data transfer and energy efficiency. The objective of the planned project is to deploy small form-factor, AI-assisted, programmable modems that build self-optimized, networked swarms of underwater and sea-surface sensors. The intellectual merit of the project stems from significantly advancing: (1) acoustic/ultrasonic/visible-light wireless communications underwater and over the water surface (using radio and mmWave frequencies); (2) energy harvesting for battery-less Internet of Floating Things devices; and (3) simulation and experimental evaluation of wireless networked robots. The broader impacts of the project derive from the anticipated advancements in open-source, software-defined network architectures for buoys, drifters, and unmanned underwater vehicles, and the attendant impacts on our understanding of the oceans.
Under the leadership of Dr. Sklivanitis, the project will involve up to two REU participants, with a focus on developing and evaluating wireless networking algorithms and protocols through simulation studies and real-world experiments. The participants will develop electronic subsystems and supporting software for the Internet of Floating Things platforms. The intent is for one participant to focus on hardware developments for energy-efficient Internet of Floating Things, and the other to focus on software frameworks for simulation and emulation of algorithms for secure, high-rate networking, with both students participating in experimental evaluation. The participants will gain experiences and skills in a variety of areas, including signal processing, AI/ML, wireless communication, robotics, and software-defined radios.