Smart City Gnosys

Smart city article details

Title	Enhancing Efficiency In Transportation Data Storage For Electric Vehicles: The Synergy Of Graph And Time-Series Databases
ID_Doc	23786
Authors	Šidlovský M.; Ravas F.
Year	2025
Published	World Electric Vehicle Journal, 16, 5
DOI	http://dx.doi.org/10.3390/wevj16050269
Abstract	This article introduces a novel hybrid database architecture that combines graph and time-series databases to enhance the storage and management of transportation data, particularly for electric vehicles (EVs). This model addresses a critical challenge in modern mobility: handling large-scale, high-velocity, and highly interconnected datasets while maintaining query efficiency and scalability. By comparing a naive graph-only approach with our hybrid solution, we demonstrate a significant reduction in query response times for large data contexts-up to 64% faster in the XL scenario. The scientific contribution of this research lies in its practical implementation of a dual-layer storage framework that aligns with FAIR data principles and real-time mobility needs. Moreover, the hybrid model supports complex analytics, such as EV battery health monitoring, dynamic route optimization, and charging behavior analysis. These capabilities offer a multiplier effect, enabling broader applications across urban mobility systems, fleet management platforms, and energy-aware transport planning. By explicitly considering the interconnected nature of transport and energy data, this work contributes to both carbon emission reduction and smart city efficiency on a global scale. © 2025 by the authors.
Author Keywords	big data in transportation; data storage optimization; electric vehicles (EVs); graph databases; hybrid database architecture; mobility as a service (MaaS); time-series data; transportation data management

Similar Articles

Id	Similarity	Authors	Title	Published
2983	0.866	Fernandez V.; Pérez V.	A New Approach To Interoperability Within The Smart City Based On Time Series-Embedded Adaptive Traffic Prediction Modelling	Networks and Spatial Economics (2024)
25001	0.864	Qi Y.; Mai G.; Zhu R.; Zhang M.	Evkg: An Interlinked And Interoperable Electric Vehicle Knowledge Graph For Smart Transportation System	Transactions in GIS, 27, 4 (2023)
57627	0.862	Fatnassi, E; Harrabi, O; Chaouachi, J	Toward A Smart Mobility System: Integrating Electric Vehicles Within Smart Cities	PROCEEDINGS OF THE 2017 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION (GECCO'17 COMPANION) (2017)
40803	0.86	Fernandez V.; Pérez V.; Roig R.	Optimizing Energy Supply For Full Electric Vehicles In Smart Cities: A Comprehensive Mobility Network Model	World Electric Vehicle Journal, 16, 1 (2025)
53953	0.855	Khanam T.; Alam M.S.; Deb S.; Rafat Y.	Sustainable Energy Systems And E-Mobility: Review And Case Study	Computational Modelling in Industry 4.0: A Sustainable Resource Management Perspective (2022)
17420	0.855	Wang B.; Chan C.; Somasi D.; Macfarlane J.; Rask E.	Data-Driven Energy Use Estimation In Large Scale Transportation Networks	Proceedings of the 2nd ACM/EIGSCC Symposium on Smart Cities and Communities, SCC 2019 (2019)
43443	0.854	Pratap Singh A.; Sharma K.; Rengarajan A.; Gautam A.K.	Promoting Sustainable Transportation Solutions Through Electric Vehicles In Smart Cities	E3S Web of Conferences, 540 (2024)
20471	0.853	Richard R.; Cao H.; Wachowicz M.	Discovering Ev Recharging Patterns Through An Automated Analytical Workflow	2020 IEEE International Smart Cities Conference, ISC2 2020 (2020)
12029	0.853	Hussain M.M.; Beg M.M.S.; Alam M.S.; Laskar S.H.	Big Data Analytics Platforms For Electric Vehicle Integration In Transport Oriented Smart Cities: Computing Platforms For Platforms For Electric Vehicle Integration In Smart Cities	Cyber Warfare and Terrorism: Concepts, Methodologies, Tools, and Applications (2020)
54103	0.85	Kanwal, M; Malik, AW; Rahman, AU; Mahmood, I; Shahzad, M	Sustainable Vehicle-Assisted Edge Computing For Big Data Migration In Smart Cities	IEEE INTERNET OF THINGS JOURNAL, 7, 3 (2020)