Extreme-scale Urban Mobility Data Analytics as a Service

Digital, Industry & SpaceHORIZON-RIAID: 101093051
EC Contribution
€49,984
Consortium Size
22 orgs
Start Year
2023
Summary

EMERALDS’s vision is to design, develop and create an urban data-oriented Mobility Analytics as a Service (MAaaS) toolset, consisting of the so-called ‘emeralds’ services, compiled in a proof-of-concept prototype, capable of exploiting the untapped potential of extreme urban mobility data. The toolset will enable the stakeholders of the urban mobility ecosystem to collect and manage ubiquitous spatio-temporal data of high-volume, high-velocity and of high-variety, analyse them both in online and offline settings, import them to real-time responsive AI/ML algorithms and visualize results in interactive dashboards, whilst implementing privacy preservation techniques at all data modalities and at all levels of its architecture. The toolset will offer advanced capabilities in data mining (searching and processing) of large amounts and varieties of urban mobility data and its efficiency will be assessed, validated and demonstrated in three TRL5 pilot use cases (by following a co-development approach with mobility and city stakeholders to improve decision making in urban smart city environments), and deployed/showcased in two early adopters’ data-driven TRL6 applications (by integrating the new services to existing systems to improve commercial offerings).

Consortium (22)

Project Results (41)

Source: CORDIS, the EU research results database.

Publications (33)
Bicycle Travel Time Estimation via Dual Graph-Based Neural Networks
IEEE Transactions on Intelligent Transportation Systems· 2026DOI
Ting Gao, Winnie Daamen, Elvin Isufi, Serge P. Hoogendoorn
CrowdSense: Interpretable and Efficient Multivariate Crowd Forecasting with Active Learning
· 2025
Wachsenegger, Anahid; Graser, Anita; Weißenfeld, Axel; Dragaschnig, Melitta
Estimating Urban Traffic Using Public Transit Buses as Probes
Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems· 2025DOI
Bahare Salehi, Mahmoud Sakr
GeoPandas-AI: A Smart Class Bringing LLM as Stateful AI Code Assistant
Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems· 2025DOI
Gaspard Merten, Gilles Dejaegere, Mahmoud Sakr
Hot Spot Analysis for Big Trajectory Data in Road Networks
· 2025
Panagiota Keziou, Christos Doulkeridis
Map‐matching for cycling travel data in urban area
IET Intelligent Transport Systems· 2025DOI
Ting Gao, Winnie Daamen, Panchamy Krishnakumari, Serge Hoogendoorn
Map‐matching for cycling travel data in urban area
IET Intelligent Transport Systems· 2025DOI
Ting Gao, Winnie Daamen, Panchamy Krishnakumari, Serge Hoogendoorn
PCIe Monitoring for Secure Code Execution in Heterogeneous System Architectures
2025 IEEE International Conference on Cyber Security and Resilience (CSR)· 2025DOI
Iasonas Georgakas, Eva Papadogiannaki, Konstantinos Georgopoulos, Sotiris Ioannidis
Shared Micro-mobility Demand Forecasting using Gradient Boosting methods
· 2025
Antonios Tziorvas, George S. Theodoropoulos, Yannis Theodoridis
ST-SplitVFL: Spatio-Temporal Split Vertical Federated Learning
· 2025DOI
Graser, Anita (Producer), Lorencio Abril, Jose Antonio (Producer), Weißenfeld, Axel (Producer), Jalali, Anahid (Producer)
Timeseries Foundation Models for Mobility: A Benchmark Comparison with Traditional and Deep Learning Models
· 2025DOI
Graser, Anita
I2DS: FPGA-Based Deep Learning Industrial Intrusion Detection System
Lecture Notes in Computer Science, Embedded Computer Systems: Architectures, Modeling, and Simulation· 2024DOI
Ioannis Morianos, Konstantinos Georgopoulos, Andreas Brokalakis, Thomas Kyriakakis, Sotiris Ioannidis
MobilityDL: a review of deep learning from trajectory data
GeoInformatica· 2024DOI
Anita Graser, Anahid Jalali, Jasmin Lampert, Axel Weißenfeld, Krzysztof Janowicz
Spatio-Temporal Vertical Federated Learning to Overcome Data Sharing Limitations
Abstracts of the ICA· 2024DOI
Lorencio Abril, Jose Antonio; Graser, Anita; Weißenfeld, Axel; Wachsenegger, Anahid
Brussels Mobility Twin
Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems· 2023DOI
Sakr, Mahmoud; Merten, Gaspard
Data-Driven Digital Mobility Twins
SIGSPATIAL '23: 31st ACM International Conference on Advances in Geographic Information Systems· 2023DOI
Mahmoud Sakr
Data-Driven Digital Mobility Twins
· 2023
Sakr, Mahmoud
Timeseries Foundation Models for Mobility: A Benchmark Comparison with Traditional and Deep Learning Models
· 2023DOI
Graser, Anita
Towards Mobility Data Science (Vision Paper)
CoRR· 2023DOI
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
Abandon All Hope Ye Who Enter Here: A Dynamic, Longitudinal Investigation of Android's Data Safety Section
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)
Brussels Mobility Twin
SIGSPATIAL '23: 31st ACM International Conference on Advances in Geographic Information SystemsDOI
Mahmoud Sakr, Gaspard Merten
Crowd Safety Manager: Towards Data-Driven Active Decision Support for Planning and Control of Crowd Events
TRB Annual Meeting 2024DOI
P Krishnakumari, S Hoogendoorn-Lanser, J Steenbakkers, S Hoogendoorn
Efficient Semantic Similarity Search over Spatio-textual Data
George S. Theodoropoulos, Kjetil Nørvåg and Christos Doulkeridis
Evaluation of Machine Learning and Deep Learning models for Multi-Horizon Crowd Forecasting at Scheveningen Beach, Netherlands
Transportation Research Record: Journal of the Transportation ResearchDOI
Theivaprakasham Hari, Winnie Daamen, Sascha Hoogendoorn-Lanser,Jeroen Steenbakkers, Serge Paul Hoogendoorn
Experimental Probing of Graph Convolutional Neural Networks Architectures for Traffic Analysis
2024 IEEE 40th International Conference on Data Engineering Workshops (ICDEW)DOI
Bahare Salehi, Mahmoud Sakr
Here Is Not There: Measuring Entailment-Based Trajectory Similarity for Location-Privacy Protection and Beyond
Proceedings of the 4th International Symposium on Platial Information Science (PLATIAL’23)DOI
Z Liu, K Janowicz, K Currier, M Shi, J Rao, S Gao, L Cai, A Graser
Mobility Data Science: Perspectives and Challenges
ACM Transactions on Spatial Algorithms and SystemsDOI
Mohamed Mokbel, Mahmoud Sakr, et al.
Parallel Spatial Join Processing with Adaptive Replication
Proceedings of 28th International Conference on Extending Database Technology (EDBT'25), Barcelona, Spain
Nikolaos Koutroumanis, Christos Doulkeridis, Akrivi Vlachou
Path-based Traffic Flow Prediction
Proceedings of the Workshops of the EDBT/ICDT 2024 Joint Conference (March 25-28, 2024), Paestum, Italy
Karkanis, E., Pelekis, N., Chondrodima, E., & Theodoridis, Y
Processing of Spatial-Keyword Range Queries in Apache Spark
BigSpatial '23: Proceedings of the 11th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial DataDOI
A Karabinos, P Tampakis, C Doulkeridis, A Vlachou
Pythia: Distributed Pattern-based Future Location Prediction of Moving Objects
CEUR Workshop Proceedings
Panagiotis Tampakis, Nikos Pelekis
Towards eXplainable AI for Mobility Data Science
ArxiV Computer Science Artificial IntelligenceDOI
Anahid Jalali, Anita Graser, Clemens Heistracher
Trajectools Demo: Towards No-Code Solutions for Movement Data Analytics
Graser, A. & Dragaschnig, M.
Deliverables (7)
Other Results (1)
Periodic Reporting for period 1 - EMERALDS (Extreme-scale Urban Mobility Data Analytics as a Service)