Extreme-scale Urban Mobility Data Analytics as a Service

Risultati finali

Document registering the key activities pertaining to maximizing the dissemination of EMERALDs outcomes during and after the project’s lifecycle.

EMERALDS Reference Architecture

EMERALDS Toolset reference architecture that utilises dedicated components from partners and open software, and distributed systems including edge/fog nodes and cloud nodes with the aim to deliver the EMERALDS services and their respective configuration towards establishing robust extreme mobility data analytics pipelines. The report will also include information on functional requirements, technical development aspects and definition of technical KPIs.

Use Cases Scoping Document

Report outlining the KPIs, timeplans, implementation plans, key resources and datasets of each use case as well as the end-to-end validation procedure to evaluate performance and effectiveness of the visioned MAaaS and the baseline situation of existing tools and approaches in the use cases.The report will detail also the solutions adopted for the technical implementation of the different tools that will be demonstrated in WP5.

Demonstration of integrated services (EMERALDS) v1

First integration of EMERALDS tools in CARTO platform environment, testing of the MapVectorTile standard performance in voluminous spatial map plots.

Containerized EMERALDS Toolset v1

Early integration of the developments from WP3 and WP4 into a re-usable and containerized toolset to be demonstrated in applications foreseen in WP5 and WP6 adhering to continuous integration and deployment software development principles. Introducing an efficient, interoperable and easy-to-deploy urban MAaaS toolset, containing methods for executing extreme data workflows.

Mobility Data Processing Services v1

Software library containing early prototypes of the extreme mobility data processing services, methods and tools which are scalable and support the ingestion of heterogeneous data types from each tier of the computing continuum.The deliverable will include a report and manual defining the data preparation activities, that include data modelling (ensuring standardisation thus interoperability), data semantics, annotation, multilingual processing aspects.

Mobility Data Analytics and Learning Services v1

Software library containing early versions of the extreme Mobility Data Analytics and Learning Services with embedded privacy-preserving tools and ingesting heterogeneous data types from each tier of the computing continuum accompanied by report consolidating release notes and instructions on executing the developed methods. A report will document the advancement of AI models compared to state-of-the art models and methods.

Pubblicazioni

Shared Micro-mobility Demand Forecasting using Gradient Boosting methods

Autori: Antonios Tziorvas, George S. Theodoropoulos, Yannis Theodoridis
Pubblicato in: 2025, ISSN 1613-0073
Editore: CEUR

GeoPandas-AI: A Smart Class Bringing LLM as Stateful AI Code Assistant

Autori: Gaspard Merten, Gilles Dejaegere, Mahmoud Sakr
Pubblicato in: Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems, 2025
Editore: ACM
DOI: 10.1145/3748636.3762765

Here Is Not There: Measuring Entailment-Based Trajectory Similarity for Location-Privacy Protection and Beyond

Autori: Z Liu, K Janowicz, K Currier, M Shi, J Rao, S Gao, L Cai, A Graser
Pubblicato in: Proceedings of the 4th International Symposium on Platial Information Science (PLATIAL’23)
Editore: PLATIAL’X Symposium Series
DOI: 10.5281/ZENODO.8286277

ST-SplitVFL: Spatio-Temporal Split Vertical Federated Learning

Autori: Graser, Anita (Producer), Lorencio Abril, Jose Antonio (Producer), Weißenfeld, Axel (Producer), Jalali, Anahid (Producer)
Pubblicato in: 2025
Editore: Zenodo
DOI: 10.5281/ZENODO.17661670

Processing of Spatial-Keyword Range Queries in Apache Spark

Autori: A Karabinos, P Tampakis, C Doulkeridis, A Vlachou
Pubblicato in: BigSpatial '23: Proceedings of the 11th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data
Editore: 11th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data 2023
DOI: 10.1145/3615833.3628592

Data-Driven Digital Mobility Twins

Autori: Sakr, Mahmoud
Pubblicato in: 2023
Editore: DI fusion

Crowd Safety Manager: Towards Data-Driven Active Decision Support for Planning and Control of Crowd Events

Autori: P Krishnakumari, S Hoogendoorn-Lanser, J Steenbakkers, S Hoogendoorn
Pubblicato in: TRB Annual Meeting 2024
Editore: National Academies TRB
DOI: 10.48550/ARXIV.2308.00076

Pythia: Distributed Pattern-based Future Location Prediction of Moving Objects

Autori: Panagiotis Tampakis, Nikos Pelekis
Pubblicato in: CEUR Workshop Proceedings, Numero roceedings of the Workshops of the EDBT/ICDT 2024 Joint Conference (March 25-28, 2024), Paestum, Italy, ISSN 1613-0073
Editore: CEUR

PCIe Monitoring for Secure Code Execution in Heterogeneous System Architectures

Autori: Iasonas Georgakas, Eva Papadogiannaki, Konstantinos Georgopoulos, Sotiris Ioannidis
Pubblicato in: 2025 IEEE International Conference on Cyber Security and Resilience (CSR), 2025
Editore: IEEE
DOI: 10.1109/CSR64739.2025.11130157

CrowdSense: Interpretable and Efficient Multivariate Crowd Forecasting with Active Learning

Autori: Wachsenegger, Anahid; Graser, Anita; Weißenfeld, Axel; Dragaschnig, Melitta
Pubblicato in: 2025, ISSN 1613-0073
Editore: CEUR Workshop Proceedings

Experimental Probing of Graph Convolutional Neural Networks Architectures for Traffic Analysis

Autori: Bahare Salehi, Mahmoud Sakr
Pubblicato in: 2024 IEEE 40th International Conference on Data Engineering Workshops (ICDEW), ISSN 2473-3490
Editore: IEEE
DOI: 10.1109/ICDEW61823.2024.00009

Parallel Spatial Join Processing with Adaptive Replication

Autori: Nikolaos Koutroumanis, Christos Doulkeridis, Akrivi Vlachou
Pubblicato in: Proceedings of 28th International Conference on Extending Database Technology (EDBT'25), Barcelona, Spain
Editore: openproceedings.org

Data-Driven Digital Mobility Twins

Autori: Mahmoud Sakr
Pubblicato in: SIGSPATIAL '23: 31st ACM International Conference on Advances in Geographic Information Systems, 2023
Editore: SIGSPATIAL ACM Special Interest Group on Spatial Information
DOI: 10.1145/3615896.3628417

Estimating Urban Traffic Using Public Transit Buses as Probes

Autori: Bahare Salehi, Mahmoud Sakr
Pubblicato in: Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems, 2025
Editore: ACM
DOI: 10.1145/3748636.3762759

Brussels Mobility Twin

Autori: Mahmoud Sakr, Gaspard Merten
Pubblicato in: SIGSPATIAL '23: 31st ACM International Conference on Advances in Geographic Information Systems
Editore: SIGSPATIAL ACM Special Interest Group on Spatial Information
DOI: 10.1145/3589132.3625634

Hot Spot Analysis for Big Trajectory Data in Road Networks

Autori: Panagiota Keziou, Christos Doulkeridis
Pubblicato in: 2025, ISSN 1613-0073
Editore: CEUR

Abandon All Hope Ye Who Enter Here: A Dynamic, Longitudinal Investigation of Android's Data Safety Section

Autori: Ioannis Arkalakis, Michalis Diamantaris, Serafeim Moustakas, and Sotiris Ioannidis (Technical University of Crete); Jason Polakis (University of Illinois Chicago) Panagiotis Ilia (Cyprus University of Technology)
Editore: USENIX Security 2024

Trajectools Demo: Towards No-Code Solutions for Movement Data Analytics

Autori: Graser, A. & Dragaschnig, M.
Pubblicato in: ISBN 979-8-3503-7455-1
Editore: IEEE

Path-based Traffic Flow Prediction

Autori: Karkanis, E., Pelekis, N., Chondrodima, E., & Theodoridis, Y
Pubblicato in: Proceedings of the Workshops of the EDBT/ICDT 2024 Joint Conference (March 25-28, 2024), Paestum, Italy, ISSN 1613-0073
Editore: BMDA 2024

I2DS: FPGA-Based Deep Learning Industrial Intrusion Detection System

Autori: Ioannis Morianos, Konstantinos Georgopoulos, Andreas Brokalakis, Thomas Kyriakakis, Sotiris Ioannidis
Pubblicato in: Lecture Notes in Computer Science, Embedded Computer Systems: Architectures, Modeling, and Simulation, 2024
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-78380-7_14

Towards eXplainable AI for Mobility Data Science

Autori: Anahid Jalali, Anita Graser, Clemens Heistracher
Pubblicato in: ArxiV Computer Science Artificial Intelligence, ISSN 2307-0846
Editore: ArxiV Computer Science Artificial Intelligence
DOI: 10.48550/ARXIV.2307.08461

Brussels Mobility Twin

Autori: Sakr, Mahmoud; Merten, Gaspard
Pubblicato in: Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems, 2023
Editore: ACM Digital Library
DOI: 10.1145/3589132.3625634

Efficient Semantic Similarity Search over Spatio-textual Data

Autori: George S. Theodoropoulos, Kjetil Nørvåg and Christos Doulkeridis
Pubblicato in: ISSN 2367-2005
Editore: openproceedings.org

Evaluation of Machine Learning and Deep Learning models for Multi-Horizon Crowd Forecasting at Scheveningen Beach, Netherlands

Autori: Theivaprakasham Hari, Winnie Daamen, Sascha Hoogendoorn-Lanser,Jeroen Steenbakkers, Serge Paul Hoogendoorn
Pubblicato in: Transportation Research Record: Journal of the Transportation Research, ISSN 0361-1981
Editore: SAGE Publishing
DOI: 10.1177/03611981261422125

Bicycle Travel Time Estimation via Dual Graph-Based Neural Networks

Autori: Ting Gao, Winnie Daamen, Elvin Isufi, Serge P. Hoogendoorn
Pubblicato in: IEEE Transactions on Intelligent Transportation Systems, Numero 27, 2026, ISSN 1524-9050
Editore: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/TITS.2025.3633150

Map‐matching for cycling travel data in urban area

Autori: Ting Gao, Winnie Daamen, Panchamy Krishnakumari, Serge Hoogendoorn
Pubblicato in: IET Intelligent Transport Systems, Numero 18, 2025, ISSN 1751-956X
Editore: Institution of Engineering and Technology (IET)
DOI: 10.1049/ITR2.12567

MobilityDL: a review of deep learning from trajectory data

Autori: Anita Graser, Anahid Jalali, Jasmin Lampert, Axel Weißenfeld, Krzysztof Janowicz
Pubblicato in: GeoInformatica, 2024, ISSN 1384-6175
Editore: Springer Science and Business Media LLC
DOI: 10.1007/s10707-024-00518-8

Map‐matching for cycling travel data in urban area

Autori: Ting Gao, Winnie Daamen, Panchamy Krishnakumari, Serge Hoogendoorn
Pubblicato in: IET Intelligent Transport Systems, Numero 18, 2025, ISSN 1751-956X
Editore: Institution of Engineering and Technology (IET)
DOI: 10.1049/ITR2.12567

Mobility Data Science: Perspectives and Challenges

Autori: Mohamed Mokbel, Mahmoud Sakr, et al.
Pubblicato in: ACM Transactions on Spatial Algorithms and Systems, ISSN 2374-0353
Editore: ACM
DOI: 10.1145/3652158

Spatio-Temporal Vertical Federated Learning to Overcome Data Sharing Limitations

Autori: Lorencio Abril, Jose Antonio; Graser, Anita; Weißenfeld, Axel; Wachsenegger, Anahid
Pubblicato in: Abstracts of the ICA, 2024
Editore: ICA
DOI: 10.5194/ICA-ABS-7-95-2024

Timeseries Foundation Models for Mobility: A Benchmark Comparison with Traditional and Deep Learning Models

Autori: Graser, Anita
Pubblicato in: 2025
Editore: arXiv
DOI: 10.48550/ARXIV.2504.03725

Towards Mobility Data Science (Vision Paper)

Autori: Mohamed F. Mokbel; Mahmoud Attia Sakr; Li Xiong 0001; Andreas Züfle; Jussara M. Almeida; Taylor Anderson 0001; Walid G. Aref; Gennady L. Andrienko; Natalia V. Andrienko; Yang Cao 0011; Sanjay Chawla; Reynold Cheng; Panos K. Chrysanthis; Xiqi Fei; Gabriel Ghinita; Anita Graser; Dimitrios Gunopulos; Christian S. Jensen; Joon-Seok Kim 0001; Kyoung-Sook Kim 0001; Peer Kröger; John Krumm; Johannes Lauer; Amr Magdy 0001; Mario A. Nascimento; Siva Ravada; Matthias Renz; Dimitris Sacharidis; Cyrus Shahabi; Flora D. Salim; Mohamed Sarwat; Maxime Schoemans; Bettina Speckmann; Egemen Tanin; Xu Teng; Yannis Theodoridis; Kristian Torp; Goce Trajcevski; Marc J. van Kreveld; Carola Wenk; Martin Werner 0001; Raymond Chi-Wing Wong; Song Wu; Jianqiu Xu; Moustafa Youssef 0001; Demetris Zeinalipour; Mengxuan Zhang 0001; Esteban Zimányi
Pubblicato in: CoRR, 2023
Editore: ACM
DOI: 10.48550/ARXIV.2307.05717

Timeseries Foundation Models for Mobility: A Benchmark Comparison with Traditional and Deep Learning Models

Autori: Graser, Anita
Pubblicato in: 2023
Editore: arXiv
DOI: 10.48550/ARXIV.2504.03725

Risultati finali

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