118 citations · 189 across the 14 of their papers we have counts for
14 papers
Towards Data-driven Nitrogen Estimation in Wheat Fields using Multispectral Images
Andreas Tritsarolis, Tomaž Bokan, Matej Brumen +2
The modernization of agriculture has motivated the development of advanced analytics and decision-support systems to improve resource utilization and reduce environmental impacts.…
On Electric Vehicle Energy Demand Forecasting and the Effect of Federated Learning
Andreas Tritsarolis, Gil Sampaio, Nikos Pelekis +1
The wide spread of new energy resources, smart devices, and demand side management strategies has motivated several analytics operations, from infrastructure load modeling to user…
Bikelution: Federated Gradient-Boosting for Scalable Shared Micro-Mobility Demand Forecasting
Antonios Tziorvas, Andreas Tritsarolis, Yannis Theodoridis
The rapid growth of dockless bike-sharing systems has generated massive spatio-temporal datasets useful for fleet allocation, congestion reduction, and sustainable mobility. Bike d…
MoDE-Boost: Boosting Shared Mobility Demand with Edge-Ready Prediction Models
Antonios Tziorvas, George S. Theodoropoulos, Yannis Theodoridis
Urban demand forecasting plays a critical role in optimizing routing, dispatching, and congestion management within Intelligent Transportation Systems. By leveraging data fusion an…
Electric Vehicle Charging Load Forecasting: An Experimental Comparison of Machine Learning Methods
Iason Kyriakopoulos, Yannis Theodoridis
With the growing popularity of electric vehicles as a means of addressing climate change, concerns have emerged regarding their impact on electric grid management. As a result, pre…
FLP-XR: Future Location Prediction on Extreme Scale Maritime Data in Real-time
George S. Theodoropoulos, Andreas Patakis, Andreas Tritsarolis +1
Movements of maritime vessels are inherently complex and challenging to model due to the dynamic and often unpredictable nature of maritime operations. Even within structured marit…
On Vessel Location Forecasting and the Effect of Federated Learning
Andreas Tritsarolis, Nikos Pelekis, Konstantina Bereta +2
The wide spread of Automatic Identification System (AIS) has motivated several maritime analytics operations. Vessel Location Forecasting (VLF) is one of the most critical operatio…
Towards Mobility Data Science (Vision Paper)
Mohamed Mokbel, Mahmoud Sakr, Li Xiong +45
Mobility data captures the locations of moving objects such as humans, animals, and cars. With the availability of GPS-equipped mobile devices and other inexpensive location-tracki…
Sustainable Urban Mobility in the Post-Pandemic Era (position paper)
Christos Theodoridis, Yannis Theodoridis
COVID-19 is the first pandemic of the modern world causing significant changes to the everyday life of billions of people in all continents. To reduce its expansion, most governmen…
Scalable Distributed Subtrajectory Clustering
Panagiotis Tampakis, Nikos Pelekis, Christos Doulkeridis +1
Trajectory clustering is an important operation of knowledge discovery from mobility data. Especially nowadays, the need for performing advanced analytic operations over massively…
Distributed Subtrajectory Join on Massive Datasets
Panagiotis Tampakis, Christos Doulkeridis, Nikos Pelekis +1
Joining trajectory datasets is a significant operation in mobility data analytics and the cornerstone of various methods that aim to extract knowledge out of them. In the era of Bi…
Moving Objects Analytics: Survey on Future Location & Trajectory Prediction Methods
Harris Georgiou, Sophia Karagiorgou, Yannis Kontoulis +4
The tremendous growth of positioning technologies and GPS enabled devices has produced huge volumes of tracking data during the recent years. This source of information constitutes…
Online Event Recognition from Moving Vessel Trajectories
Kostas Patroumpas, Elias Alevizos, Alexander Artikis +3
We present a system for online monitoring of maritime activity over streaming positions from numerous vessels sailing at sea. It employs an online tracking module for detecting imp…
Optimal Time-dependent Sequenced Route Queries in Road Networks
Camila F. Costa, Mario A. Nascimento, Jose A. F. Macedo +3
In this paper we present an algorithm for optimal processing of time-dependent sequenced route queries in road networks, i.e., given a road network where the travel time over an ed…