Smart City Gnosys
Smart city article details
| Title | A Multi-Agent Architecture For Context Sources Integration In Smart Cities |
|---|---|
| ID_Doc | 2756 |
| Authors | do Nascimento L.V.; de Oliveira J.P.M. |
| Year | 2025 |
| Published | Future Generation Computer Systems, 172 |
| DOI | http://dx.doi.org/10.1016/j.future.2025.107862 |
| Abstract | Contextual data in smart cities are present in large quantities and distributed sources. Many applications can benefit from these data to provide better services to their users. The scale and dynamic nature of urban environments pose significant challenges in making context sources available to applications. These challenges involve transparent access to context, resilience, decentralization, extensibility, scalability, and redundancy of data. This study introduces a new architecture designed to address these issues. This architecture aims to facilitate the acquisition of context by integrating distributed data sources. The developed architecture not only overcomes the challenges posed by the scale and dynamicity of urban environments but also prepares for more innovative and effective solutions for smart cities. The architecture is distributed, decentralized, and fault-tolerant, providing data fusion mechanisms and dynamic context source composition. Compared to existing works, our architecture contributes to the state-of-the-art addressing all these five challenges in one design. The architecture uses the multi-agent paradigm, which is inherently distributed and facilitates decentralization. A scenario was used to execute several experiments demonstrating that the architecture can obtain context data transparently by any application. © 2025 |
| Author Keywords | Context; Context-aware systems; Data source integration; Multi-agent systems; Smart cities |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
34287  | 0.876 | Gupta M.; Khan M.S.; Mishra S.; Sharma P. | Iterative Approach To Implement And Deployment For Smart City And Urbanization | 5G-Enabled Technology for Smart City and Urbanization System (2024) |
| 41686 | 0.876 | Aguilar, J; Jerez, M; Mendonça, M; Sánchez, M | Performance Analysis Of The Ubiquitous And Emergent Properties Of An Autonomic Reflective Middleware For Smart Cities | COMPUTING, 102, 10 (2020) |
| 5124 | 0.869 | Nezamoddini N.; Gholami A. | A Survey Of Adaptive Multi-Agent Networks And Their Applications In Smart Cities | Smart Cities, 5, 1 (2022) |
| 54471 | 0.86 | Bazan-Muñoz A.; Ortiz G.; Augusto J.C.; Garcia-de-Prado A. | Taxonomy And Software Architecture For Real-Time Context-Aware Collaborative Smart Environments | Internet of Things (Netherlands), 26 (2024) |
| 37589 | 0.857 | Lom, M; Pribyl, O | Modeling Of Smart City Building Blocks Using Multi-Agent Systems | NEURAL NETWORK WORLD, 27, 4 (2017) |
| 50366 | 0.854 | Goumopoulos C. | Smart City Middleware: A Survey And A Conceptual Framework | IEEE Access, 12 (2024) |
| 1073 | 0.851 | Aiello G.; Camillo A.; Del Coco M.; Giangreco E.; Pinnella M.; Pino S.; Storelli D. | A Context Agnostic Air Quality Service To Exploit Data In The Ioe Era | 2019 4th International Conference on Smart and Sustainable Technologies, SpliTech 2019 (2019) |
| 27886 | 0.85 | Prieto, AE; Preciado, JC; Conejero, JM; Rubio-Largo, A | Geo-Time Broker: A Web Agent Of Dynamic Flows Of Geo-Temporal Activity For Smart Cities | CURRENT TRENDS IN WEB ENGINEERING (ICWE 2018), 11153 (2018) |