Atakan Aral: Edge AI and IoT-Driven Water Quality Monitoring

The integration of Edge Computing and Artificial Intelligence (i.e., Edge AI) unlocks new possibilities for remote monitoring of water quality across diverse environments. This talk will explore the dual aspects of "remote" monitoring: (1) collecting water quality data in geographically remote regions with limited energy and connectivity and (2) using connected water quality sensors to gain real-time insights remotely. 

By deploying low-power or energy-harvesting sensors and learning from data in close proximity to sensors, we can improve efficiency, reduce latency, and maintain learning performance in challenging environments without reliable communication and energy infrastructures. The presentation will showcase two real-world case studies in river pollution source identification and monitoring of water distribution systems.

Atakan Aral is a tenure-track assistant professor of Information Systems Engineering at the Faculty of Computer Science, University of Vienna, Austria. Prior to that, he was a tenure-track assistant professor of Distributed Systems at Umeå University, Sweden, and a postdoctoral fellow at the Data Science group at TU Wien, Austria. 

His research interests center around optimizing resource utilization and placement at the network's edge for data-driven workloads. He received a dual MSc degree in Computer Science and Engineering from Politecnico di Milano (2011) and Istanbul Technical University (2012), and a PhD in Computer Engineering from Istanbul Technical University (2016). Atakan has been granted two EIC Pathfinder CHIST-ERA projects in 2021 and 2024 as international coordinator and national PI, respectively, with a total funding value of over €2.2M.