demonstration

ARGO: A Big Data Framework for Online Trajectory Prediction

Authors:

Petros Petrou,

Panagiotis Nikitopoulos,

Panagiotis Tampakis,

Apostolos Glenis,

Nikolaos Koutroumanis,

Georgios M. Santipantakis,

Christos Doulkeridis,

Nikos Pelekis,

Gennady L. Andrienko,

Fabian Patterson,

Georg Fuchs,

Yannis Theodoridis,

George A. VourosAuthors Info & Claims

SSTD '19: Proceedings of the 16th International Symposium on Spatial and Temporal Databases

Pages 194 - 197

https://doi.org/10.1145/3340964.3340988

Published: 19 August 2019 Publication History

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Abstract

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 predictions with low latency. To meet this goal, we follow a multi-step methodology. First, we efficiently compress surveillance data in an online fashion, by constructing trajectory synopses that are spatio-temporally linked with streaming and archival data from a variety of diverse and heterogeneous data sources. The enriched stream of trajectory synopses is stored in a distributed RDF store, supporting data exploration via SPARQL queries. The enriched stream of synopses along with the raw data is consumed by trajectory prediction algorithms that exploit mined patterns from the RDF store, namely medoids of (sub-) trajectory clusters, which prolong the horizon of useful predictions. The framework is extended with offline and online interactive visual analytics tool to facilitate real world analysis in the maritime and the aviation domains.

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Cited By

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Tritsarolis APelekis NBereta KZissis DTheodoridis Y(2024)On Vessel Location Forecasting and the Effect of Federated Learning2024 25th IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM61037.2024.00031(83-92)Online publication date: 24-Jun-2024
https://doi.org/10.1109/MDM61037.2024.00031
Mandalis PChondrodima EKontoulis YPelekis NTheodoridis Y(2024)A transformer-based method for vessel traffic flow forecastingGeoInformatica10.1007/s10707-024-00521-zOnline publication date: 30-May-2024
https://doi.org/10.1007/s10707-024-00521-z
Adamopoulou EDaskalakis E(2023)Applications and Technologies of Big Data in the Aerospace DomainElectronics10.3390/electronics1210222512:10(2225)Online publication date: 13-May-2023
https://doi.org/10.3390/electronics12102225
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Index Terms

ARGO: A Big Data Framework for Online Trajectory Prediction
1. Information systems
  1. Information systems applications
    1. Spatial-temporal systems
      1. Data streaming

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Published In

SSTD '19: Proceedings of the 16th International Symposium on Spatial and Temporal Databases

August 2019

245 pages

ISBN:9781450362801

DOI:10.1145/3340964

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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TU Wien: TU Wien

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 August 2019

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SSTD '19

SSTD '19: 16th International Symposium on Spatial and Temporal Databases

August 19 - 21, 2019

Vienna, Austria

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Tritsarolis APelekis NBereta KZissis DTheodoridis Y(2024)On Vessel Location Forecasting and the Effect of Federated Learning2024 25th IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM61037.2024.00031(83-92)Online publication date: 24-Jun-2024
https://doi.org/10.1109/MDM61037.2024.00031
Mandalis PChondrodima EKontoulis YPelekis NTheodoridis Y(2024)A transformer-based method for vessel traffic flow forecastingGeoInformatica10.1007/s10707-024-00521-zOnline publication date: 30-May-2024
https://doi.org/10.1007/s10707-024-00521-z
Adamopoulou EDaskalakis E(2023)Applications and Technologies of Big Data in the Aerospace DomainElectronics10.3390/electronics1210222512:10(2225)Online publication date: 13-May-2023
https://doi.org/10.3390/electronics12102225
Chondrodima EPelekis NPikrakis ATheodoridis Y(2023)An Efficient LSTM Neural Network-Based Framework for Vessel Location ForecastingIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.324799324:5(4872-4888)Online publication date: May-2023
https://doi.org/10.1109/TITS.2023.3247993
Chondrodima EMandalis PPelekis NTheodoridis Y(2022)Machine Learning Models for Vessel Route Forecasting: An Experimental Comparison2022 23rd IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM55031.2022.00056(262-269)Online publication date: Jun-2022
https://doi.org/10.1109/MDM55031.2022.00056
Tritsarolis AChondrodima ETampakis PPikrakis ATheodoridis Y(2022)Predicting Co-movement patterns in mobility dataGeoInformatica10.1007/s10707-022-00478-x28:2(221-243)Online publication date: 22-Sep-2022
https://doi.org/10.1007/s10707-022-00478-x
Tampakis PChondrodima ETritsarolis APikrakis ATheodoridis YPristouris KNakos HKalampokis PDalamagas T(2021)i4sea: a big data platform for sea area monitoring and analysis of fishing vessels activityGeo-spatial Information Science10.1080/10095020.2021.197105525:2(132-154)Online publication date: 19-Oct-2021
https://doi.org/10.1080/10095020.2021.1971055
Shrivastava AVerma JJain SGarg S(2021)A deep learning based approach for trajectory estimation using geographically clustered dataSN Applied Sciences10.1007/s42452-021-04556-x3:6Online publication date: 1-May-2021
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Tampakis PSideridis SNikitopoulos PPelekis NTheodoridis Y(2021)Maritime Data AnalyticsGuide to Maritime Informatics10.1007/978-3-030-61852-0_4(119-147)Online publication date: 9-Feb-2021
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Tampakis P(2020)Big Mobility Data Analytics: Algorithms and Techniques for Efficient Trajectory Clustering2020 21st IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM48529.2020.00055(244-245)Online publication date: Jun-2020
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