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Online Research Seminar
15:30 pm, Thursday, 27 October 2022

Smart cities are ones that deploy innovative technology, create more innovative ways of delivering public services and make better use of data with the ultimate objective of becoming more prosperous, sustainable and a better place to live. Smart environments are usually built on a network of sensors and Internet of Things (IoT) sensing devices to enable real-time monitoring and response. Data collected from the IoT network can be processed both in real-time and a posteriori to provide insights for advancing and automating processes within and for the urban city environment. A large variety of sensing devices already exist and provide the ability to collect a wide range of city data, from environmental conditions (temperature, air pollution etc.), traffic and road congestions (both for vehicles and humans), sound monitoring, waste management and much more. Current urban city monitoring systems manage to understand changes in the city environment and provide automated mitigation solutions that improve the city management strategy and ease citizens’ life within the city.

In a parallel and disconnected path, research initiatives utilize information posted in social media to identify and contextualize events (either social or infrastructure related). This area of research is based on humans as sensors and utilizes the power of the crowd to provide citizens, government officials, journalists, and other interested parties with city-wide situation awareness.

We will present a project that aims to research the “Technical Sensor” and “Human Sensor” environments and identify points of association between these two currently disconnected worlds. These points of association will aggregate the information coming from the two environments, in what we call the ‘Feedback Loop’, that will allow the enhancement of the insights the two approaches can offer.

About the speaker

Dr. Christodoulos Efstathiades is an Assistant Professor of Computer Science at CIIM. He has held positions both in academia and industry in the fields of Data Management, Data Science and Analytics. He holds a PhD in Computer Science from the National Technical University of Athens (NTUA), a MSc in Networked Computer Systems from University College London (UCL) and a BSc in Computer Science from the University of Cyprus. He had worked as a Data Analytics Engineer at the Bank of Cyprus and as a Technology Consultant and Data Engineer at EY Cyprus. He has been a Lecturer at the Department of Computer Science and Engineering at the European University Cyprus and has also taught at the University of Cyprus. Dr. Efstathiades has also been an academic member of the Center of Excellence in Risk and Decision Sciences (CERIDES) where he had worked on various R&D projects. He held R&D appointments at the Institute for the Management of Information Systems of the “Athena” Research Center, at NTUA as a Marie Curie Fellow, at George Mason University (USA) and at the University of Cyprus, where he has worked extensively on National and European projects in the area of Big Data management and analysis and the application of data mining and machine learning in other sciences. His current research interests lie in the areas of database systems and geospatial data management for big data, genomic data science and the application of data mining and machine learning in other sciences.