Extreme-scale Urban Mobility Data Analytics as a Service

Resultado final

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.

EMERALDS Toolset Adoption and Lessons Learned

Prototype Software demonstrator developed by commercial partner which calls on EMERALDS services to perform Transport network optimisation for road/transport network operators and corresponding report.

Dissemination, Communication and Liaison Activities

Report detailing the orchestration, execution and impact of EMERALDs dissemination, communication and liaison activities towards stakeholder groups throughout the project’s lifecycle. Presentation of key impact metrics and effectiveness of Dissemination and Communication measures.

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.

Mobility Data Processing Services v2

Software library containing the updated versions of the extreme mobility data processing services, methods and tools, embedding the necessary revisions according to the feedback from the continuous deployment and integration loops performed during the demonstrators documented in detailed report and manual.

Containerized EMERALDS Toolset v2

Updated version of the integrated tools as a re-usable and containerized toolset that can be deployed in multiple cloud native platform environments and called from all tiers of the computing continuum with updated functionalities according to requirements incurred from the first iterations of the demonstrators in WP5 as well as the introduction of advanced features from the security and data governance layer in D2.6.

Mobility Data Analytics and Learning Services v2

Updated software library, with AI-as-a Service features, federated ML and improved Mobility Data Analytics Services configurable and extensible by design. Implementation of MAaaS stack to be deployed on ATOS platform accompanied by report and manual.

Security and Data Governance Layer

Software library and report containing remote attestation modules, security controls over data collection and streams, privacy preservation at the edge and trust protocols.

Demonstration of integrated services (EMERALDS) v2

Final version of integrated services in CARTO platform environment via standardized exchange format using MobilityDB, as an extension to its current data management API. The demonstrator will focus on leveraging the mobility functions of the Analytics Toolbox to unlock advanced extreme spatial analysis for commuter patterns on a combination of data sources.

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.

Multi-modal integrated traffic management v1

Interim Prototype software demonstrator utilizing components from the EMERALDS toolset in partner native systems capable of handling extreme multi modal integrated traffic data and producing informed traffic forecasts with progress report.

Multi-modal integrated traffic management v2

Updated prototype software demonstrator, applying real-time control and prediction on multi-modal integrated traffic management proving the achievement of the use-case KPIs and report.

Trip Characteristics Inference and Traffic Flow Data Analytics v1

Demonstrator of the first version of the data-driven analytics tool enabled by components of the EMERALDS Toolset for different Riga transportation mode traveller trip characteristics inference and traffic flow studies including report.

Risk-assessment, prediction and forecasting during events v1

Proof-of-concept early instantiation of the architecture using the containerized toolset and SaaS from the platform providers suiting the purposes of AI for risk assessment, prediction, and forecasting including report.

Risk-assessment, prediction and forecasting during events v2

Prototype demonstrator on risk-assessment, prediction and forecasting during crowded events showcasing the recorded improvements in performance and KPIs attainment in a final report.

Trip Characteristics Inference and Traffic Flow Data Analytics v2

Final release of the data-driven analytics tool enabled by components of the EMERALDS Toolset for different Riga transportation mode traveller trip characteristics inference and traffic flow studies with performance metrics with report describing the recorded progress.

Publicaciones

Shared Micro-mobility Demand Forecasting using Gradient Boosting methods

Autores: Antonios Tziorvas, George S. Theodoropoulos, Yannis Theodoridis
Publicado en: 2025, ISSN 1613-0073
Editor: CEUR

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

Autores: Gaspard Merten, Gilles Dejaegere, Mahmoud Sakr
Publicado en: Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems, 2025
Editor: ACM
DOI: 10.1145/3748636.3762765

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

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

ST-SplitVFL: Spatio-Temporal Split Vertical Federated Learning

Autores: Graser, Anita (Producer), Lorencio Abril, Jose Antonio (Producer), Weißenfeld, Axel (Producer), Jalali, Anahid (Producer)
Publicado en: 2025
Editor: Zenodo
DOI: 10.5281/ZENODO.17661670

Processing of Spatial-Keyword Range Queries in Apache Spark

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

Data-Driven Digital Mobility Twins

Autores: Sakr, Mahmoud
Publicado en: 2023
Editor: DI fusion

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

Autores: P Krishnakumari, S Hoogendoorn-Lanser, J Steenbakkers, S Hoogendoorn
Publicado en: TRB Annual Meeting 2024
Editor: National Academies TRB
DOI: 10.48550/ARXIV.2308.00076

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

Autores: Panagiotis Tampakis, Nikos Pelekis
Publicado en: CEUR Workshop Proceedings, Edición roceedings of the Workshops of the EDBT/ICDT 2024 Joint Conference (March 25-28, 2024), Paestum, Italy, ISSN 1613-0073
Editor: CEUR

PCIe Monitoring for Secure Code Execution in Heterogeneous System Architectures

Autores: Iasonas Georgakas, Eva Papadogiannaki, Konstantinos Georgopoulos, Sotiris Ioannidis
Publicado en: 2025 IEEE International Conference on Cyber Security and Resilience (CSR), 2025
Editor: IEEE
DOI: 10.1109/CSR64739.2025.11130157

CrowdSense: Interpretable and Efficient Multivariate Crowd Forecasting with Active Learning

Autores: Wachsenegger, Anahid; Graser, Anita; Weißenfeld, Axel; Dragaschnig, Melitta
Publicado en: 2025, ISSN 1613-0073
Editor: CEUR Workshop Proceedings

Experimental Probing of Graph Convolutional Neural Networks Architectures for Traffic Analysis

Autores: Bahare Salehi, Mahmoud Sakr
Publicado en: 2024 IEEE 40th International Conference on Data Engineering Workshops (ICDEW), ISSN 2473-3490
Editor: IEEE
DOI: 10.1109/ICDEW61823.2024.00009

Parallel Spatial Join Processing with Adaptive Replication

Autores: Nikolaos Koutroumanis, Christos Doulkeridis, Akrivi Vlachou
Publicado en: Proceedings of 28th International Conference on Extending Database Technology (EDBT'25), Barcelona, Spain
Editor: openproceedings.org

Data-Driven Digital Mobility Twins

Autores: Mahmoud Sakr
Publicado en: SIGSPATIAL '23: 31st ACM International Conference on Advances in Geographic Information Systems, 2023
Editor: SIGSPATIAL ACM Special Interest Group on Spatial Information
DOI: 10.1145/3615896.3628417

Estimating Urban Traffic Using Public Transit Buses as Probes

Autores: Bahare Salehi, Mahmoud Sakr
Publicado en: Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems, 2025
Editor: ACM
DOI: 10.1145/3748636.3762759

Brussels Mobility Twin

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

Hot Spot Analysis for Big Trajectory Data in Road Networks

Autores: Panagiota Keziou, Christos Doulkeridis
Publicado en: 2025, ISSN 1613-0073
Editor: CEUR

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

Autores: 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)
Editor: USENIX Security 2024

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

Autores: Graser, A. & Dragaschnig, M.
Publicado en: ISBN 979-8-3503-7455-1
Editor: IEEE

Path-based Traffic Flow Prediction

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

I2DS: FPGA-Based Deep Learning Industrial Intrusion Detection System

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

Towards eXplainable AI for Mobility Data Science

Autores: Anahid Jalali, Anita Graser, Clemens Heistracher
Publicado en: ArxiV Computer Science Artificial Intelligence, ISSN 2307-0846
Editor: ArxiV Computer Science Artificial Intelligence
DOI: 10.48550/ARXIV.2307.08461

Brussels Mobility Twin

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

Efficient Semantic Similarity Search over Spatio-textual Data

Autores: George S. Theodoropoulos, Kjetil Nørvåg and Christos Doulkeridis
Publicado en: ISSN 2367-2005
Editor: openproceedings.org

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

Autores: Theivaprakasham Hari, Winnie Daamen, Sascha Hoogendoorn-Lanser,Jeroen Steenbakkers, Serge Paul Hoogendoorn
Publicado en: Transportation Research Record: Journal of the Transportation Research, ISSN 0361-1981
Editor: SAGE Publishing
DOI: 10.1177/03611981261422125

Bicycle Travel Time Estimation via Dual Graph-Based Neural Networks

Autores: Ting Gao, Winnie Daamen, Elvin Isufi, Serge P. Hoogendoorn
Publicado en: IEEE Transactions on Intelligent Transportation Systems, Edición 27, 2026, ISSN 1524-9050
Editor: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/TITS.2025.3633150

Map‐matching for cycling travel data in urban area

Autores: Ting Gao, Winnie Daamen, Panchamy Krishnakumari, Serge Hoogendoorn
Publicado en: IET Intelligent Transport Systems, Edición 18, 2025, ISSN 1751-956X
Editor: Institution of Engineering and Technology (IET)
DOI: 10.1049/ITR2.12567

MobilityDL: a review of deep learning from trajectory data

Autores: Anita Graser, Anahid Jalali, Jasmin Lampert, Axel Weißenfeld, Krzysztof Janowicz
Publicado en: GeoInformatica, 2024, ISSN 1384-6175
Editor: Springer Science and Business Media LLC
DOI: 10.1007/s10707-024-00518-8

Map‐matching for cycling travel data in urban area

Autores: Ting Gao, Winnie Daamen, Panchamy Krishnakumari, Serge Hoogendoorn
Publicado en: IET Intelligent Transport Systems, Edición 18, 2025, ISSN 1751-956X
Editor: Institution of Engineering and Technology (IET)
DOI: 10.1049/ITR2.12567

Mobility Data Science: Perspectives and Challenges

Autores: Mohamed Mokbel, Mahmoud Sakr, et al.
Publicado en: ACM Transactions on Spatial Algorithms and Systems, ISSN 2374-0353
Editor: ACM
DOI: 10.1145/3652158

Spatio-Temporal Vertical Federated Learning to Overcome Data Sharing Limitations

Autores: Lorencio Abril, Jose Antonio; Graser, Anita; Weißenfeld, Axel; Wachsenegger, Anahid
Publicado en: Abstracts of the ICA, 2024
Editor: ICA
DOI: 10.5194/ICA-ABS-7-95-2024

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

Autores: Graser, Anita
Publicado en: 2025
Editor: arXiv
DOI: 10.48550/ARXIV.2504.03725

Towards Mobility Data Science (Vision Paper)

Autores: 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
Publicado en: CoRR, 2023
Editor: ACM
DOI: 10.48550/ARXIV.2307.05717

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

Autores: Graser, Anita
Publicado en: 2023
Editor: arXiv
DOI: 10.48550/ARXIV.2504.03725

Resultado final

Publicaciones

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