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Moving Objects Analytics: Survey on Future Location & Trajectory Prediction Methods
This paper focuses on predictive analytics for moving objects and surveys the state-of-the-art in the context of future location and trajectory prediction and proposes a novel taxonomy of predictive algorithms over moving objects.
Citizens’ Campaigns for Environmental Water Monitoring: Lessons From Field Experiments
The challenges of designing citizens’ campaigns for collecting data on environmental waters are introduced and crowdsourcing by citizens has been proposed as an alternative approach for adaptive data collection that can augment the amount of data collected and bring together the diverse stakeholders and citizens in more participatory water resources management processes.
Big Data Analytics for Time Critical Mobility Forecasting: Recent Progress and Research Challenges
Progress achieved towards time critical big data analytics solutions in user-defined challenges concerning moving entities in the air-traffic management and maritime domains is described.
Semantic-aware aircraft trajectory prediction using flight plans
- H. Georgiou, N. Pelekis, Stylianos Sideridis, David Scarlatti, Y. Theodoridis
- Computer ScienceInternational Journal of Data Science and…
- 28 March 2019
Flight plans, localized weather and aircraft properties are introduced as trajectory annotations that enable modeling in a space higher than the typical 4-D spatio-temporal, including hidden Markov model (HMM), linear regressors, regression trees and feed-forward neural networks.
Online Long-Term Trajectory Prediction Based on Mined Route Patterns
- Petros Petrou, Panagiotis Tampakis, H. Georgiou, N. Pelekis, Y. Theodoridis
- Computer ScienceMASTER@PKDD/ECML
- 16 September 2019
A Big data framework for the prediction of streaming trajectory data by exploiting mined patterns of trajectories, allowing accurate long-term predictions with low latency, and follows a two-step methodology to meet this goal.
ARGO: A Big Data Framework for Online Trajectory Prediction
We present a big data framework for the prediction of streaming trajectory data, enriched from other data sources and exploiting mined patterns of trajectories, allowing accurate long-term…
DART : A Machine-Learning Approach to Trajectory Prediction and Demand-Capacity Balancing
The DART (Data-driven Aircraft Trajectory Prediction Research) project from SESAR 2020 Exploratory Research aims at reaching this goal, by means of machine learning and agent-based modeling methods in two different operational use cases: trajectory prediction and demand-capacity balancing.
COVID-19 outbreak in Greece has passed its rising inflection point and stepping into its peak
- H. Georgiou
- Environmental SciencemedRxiv
- 15 April 2020
Greece is the main focus for assessing the national outbreak and estimating the general trends and outlook of it, and standard SIEQRDP epidemic modelling is applied for Greece and for the general region around it, providing hints for the outbreak progression in the mid- and long-term.
Future Location and Trajectory Prediction
- H. Georgiou, Petros Petrou, Y. Theodoridis
- Computer ScienceBig Data Analytics for Time-Critical Mobility…
The overall assessment of the suite of FLP and TP algorithms developed addresses all the major prediction challenges regarding mobility patterns in terms of points or trajectories, respectively, and it is expected that these modeling approaches can be transferred to other domains of similar challenges and with similar success.