mlsanityData to 7 Oct 2026

Applications of Federated Learning in Smart Cities: Recent Advances, Taxonomy, and Open Challenges

arXiv 2102.01375 ↗First posted 2 Feb 2021cs.LG cs.CRcited by 17

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Abstract (arXiv)

Federated learning plays an important role in the process of smart cities. With the development of big data and artificial intelligence, there is a problem of data privacy protection in this process. Federated learning is capable of solving this problem. This paper starts with the current developments of federated learning and its applications in various fields. We conduct a comprehensive investigation. This paper summarize the latest research on the application of federated learning in various fields of smart cities. In-depth understanding of the current development of federated learning from the Internet of Things, transportation, communications, finance, medical and other fields. Before that, we introduce the background, definition and key technologies of federated learning. Further more, we review the key technologies and the latest results. Finally, we discuss the future applications and research directions of federated learning in smart cities.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). Builds on 52 of its 112 references that are in the map. First posted on arXiv 2 Feb 2021.

Builds on

52 of 112 references.

References · 52

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2016Communication-Efficient Learning of Deep Networks from Decentralized Datacited by 7,592
  3. 2018Federated Optimization in Heterogeneous Networkscited by 2,971
  4. 2019Federated Learning: Challenges, Methods, and Future Directionscited by 1,531
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  12. 2019Federated Learning in Mobile Edge Networks: A Comprehensive Surveycited by 407
38 more
  1. 2019Fair Resource Allocation in Federated Learningcited by 389
  2. 2018Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learningcited by 242
  3. 2018Federated Learning via Over-the-Air Computationcited by 215
  4. 2019Federated Learning over Wireless Fading Channelscited by 178
  5. 2017A Survey on Homomorphic Encryption Schemes: Theory and Implementationcited by 154
  6. 2019Federated Adversarial Domain Adaptationcited by 140
  7. 2016Distributed Mean Estimation with Limited Communicationcited by 134
  8. 2019Federated Learning for Wireless Communications: Motivation, Opportunities and Challengescited by 128
  9. 2020FedVision: An Online Visual Object Detection Platform Powered by Federated Learningcited by 121
  10. 2018Blockchained On-Device Federated Learningcited by 105
  11. 2019Reliable Federated Learning for Mobile Networkscited by 92
  12. 2018In-Edge AI: Intelligentizing Mobile Edge Computing, Caching and Communication by Federated Learningcited by 80
  13. 2019Measure Contribution of Participants in Federated Learningcited by 78
  14. 2019Lifelong Federated Reinforcement Learning: A Learning Architecture for Navigation in Cloud Robotic Systemscited by 77
  15. 2019Federated Learning for Edge Networks: Resource Optimization and Incentive Mechanismcited by 75
  16. 2016CoCoA: A General Framework for Communication-Efficient Distributed Optimizationcited by 69
  17. 2020Personalized Federated Learning for Intelligent IoT Applications: A Cloud-Edge based Frameworkcited by 59
  18. 2019On Safeguarding Privacy and Security in the Framework of Federated Learningcited by 55
  19. 2018Learning Private Neural Language Modeling with Attentive Aggregationcited by 49
  20. 2018Blind Justice: Fairness with Encrypted Sensitive Attributescited by 41
  21. 2019Interpret Federated Learning with Shapley Valuescited by 33
  22. 2019Towards Federated Graph Learning for Collaborative Financial Crimes Detectioncited by 33
  23. 2017Learning Differentially Private Recurrent Language Modelscited by 32
  24. 2020Experiments of Federated Learning for COVID-19 Chest X-ray Imagescited by 31
  25. 2018Federated Learning for Ultra-Reliable Low-Latency V2V Communicationscited by 30
  26. 2020Asymmetrical Vertical Federated Learningcited by 26
  27. 2019Federated Imitation Learning: A Novel Framework for Cloud Robotic Systems with Heterogeneous Sensor Datacited by 24
  28. 2020Privacy-Preserving Asynchronous Federated Learning Algorithms for Multi-Party Vertically Collaborative Learningcited by 19
  29. 2020Robust Aggregation for Adaptive Privacy Preserving Federated Learning in Healthcarecited by 18
  30. 2020A Vertical Federated Learning Method for Interpretable Scorecard and Its Application in Credit Scoringcited by 16
  31. 2020Joint Auction-Coalition Formation Framework for Communication-Efficient Federated Learning in UAV-Enabled Internet of Vehiclescited by 14
  32. 2020Privacy Preserving Distributed Machine Learning with Federated Learningcited by 13
  33. 2020Peer-Assisted Robotic Learning: A Data-Driven Collaborative Learning Approach for Cloud Robotic Systemscited by 9
  34. 2020Combining Federated and Active Learning for Communication-efficient Distributed Failure Prediction in Aeronauticscited by 6
  35. 2016Confidence Decision Trees via Online and Active Learning for Streaming (BIG) Datacited by 5
  36. 2017Towards Low-Latency and Ultra-Reliable Vehicle-to-Vehicle Communicationcited by 5
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  38. 2020FLBench: A Benchmark Suite for Federated Learningcited by 2

50 most cited of 52 All 52 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 0; 2023: 5; 2024: 5; 2025: 4; 2026: 2.

17 papers.

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  1. 2023Backdoor Attacks and Defenses in Federated Learning: Survey, Challenges and Future Research Directionscited by 33
  2. 2023Towards Quantum Federated Learningcited by 20
  3. 2023On the Convergence of Decentralized Federated Learning Under Imperfect Information Sharingcited by 16
  4. 2024Achieving Linear Speedup in Asynchronous Federated Learning with Heterogeneous Clientscited by 7
  5. 2023Federated Learning for 6G: Paradigms, Taxonomy, Recent Advances and Insightscited by 4
  6. 2024Post-Fair Federated Learning: Achieving Group and Community Fairness in Federated Learning via Post-processingcited by 4
  7. 2023Collaborative Policy Learning for Dynamic Scheduling Tasks in Cloud-Edge-Terminal IoT Networks Using Federated Reinforcement Learningcited by 3
  8. 2021LoSAC: An Efficient Local Stochastic Average Control Method for Federated Optimizationcited by 2
  9. 2024Spatial Computing: Concept, Applications, Challenges and Future Directionscited by 1
  10. 2024FedNMUT -- Federated Noisy Model Update Tracking Convergence Analysiscited by 1
  11. 2024Holistic Evaluation Metrics: Use Case Sensitive Evaluation Metrics for Federated Learningcited by 1
  12. 2025Task-Agnostic Federation over Decentralized Data: Research Landscape and Visionscited by 0
5 more
  1. 2025An Empirical Study of the Impact of Federated Learning on Machine Learning Model Accuracycited by 0
  2. 2025Federated Learning on Stochastic Neural Networkscited by 0
  3. 2025FairEquityFL -- A Fair and Equitable Client Selection in Federated Learning for Heterogeneous IoV Networkscited by 0
  4. 2026A Typed Tensor Language for Shared-State Federated Computationcited by 0
  5. 2026Opinion Dynamics-based Coalition Formation for Federated Learning in Heterogeneous IoT Systemscited by 0