mlsanityData to 7 Oct 2026

Graph Neural Networks in IoT: A Survey

arXiv 2203.15935 ↗First posted 29 Mar 2022cs.LGcited by 27

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Abstract (arXiv)

The Internet of Things (IoT) boom has revolutionized almost every corner of people's daily lives: healthcare, home, transportation, manufacturing, supply chain, and so on. With the recent development of sensor and communication technologies, IoT devices including smart wearables, cameras, smartwatches, and autonomous vehicles can accurately measure and perceive their surrounding environment. Continuous sensing generates massive amounts of data and presents challenges for machine learning. Deep learning models (e.g., convolution neural networks and recurrent neural networks) have been extensively employed in solving IoT tasks by learning patterns from multi-modal sensory data. Graph Neural Networks (GNNs), an emerging and fast-growing family of neural network models, can capture complex interactions within sensor topology and have been demonstrated to achieve state-of-the-art results in numerous IoT learning tasks. In this survey, we present a comprehensive review of recent advances in the application of GNNs to the IoT field, including a deep dive analysis of GNN design in various IoT sensing environments, an overarching list of public data and source code from the collected publications, and future research directions. To keep track of newly published works, we collect representative papers and their open-source implementations and create a Github repository at https://github.com/GuiminDong/GNN4IoT.

Key facts. Cited by 27 papers in the map (data through 7 Oct 2026). Builds on 107 of its 344 references that are in the map. First posted on arXiv 29 Mar 2022.

Builds on

107 of 344 references.

References · 107

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38 more
  1. 2018Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networkscited by 878
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 11; 2024: 8; 2025: 5; 2026: 2.

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  1. 2023A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detectioncited by 145
  2. 2024SwitchTab: Switched Autoencoders Are Effective Tabular Learnerscited by 37
  3. 2025Graphs Meet AI Agents: Taxonomy, Progress, and Future Opportunitiescited by 23
  4. 2024IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networkscited by 22
  5. 2024Graph Neural Networks for Tabular Data Learning: A Survey with Taxonomy and Directionscited by 13
  6. 2023FAQ: Feature Aggregated Queries for Transformer-based Video Object Detectorscited by 10
  7. 2023DyEdgeGAT: Dynamic Edge via Graph Attention for Early Fault Detection in IIoT Systemscited by 10
  8. 2024Graph Neural Networks for Virtual Sensing in Complex Systems: Addressing Heterogeneous Temporal Dynamicscited by 7
  9. 2023Graph Neural Network for spatiotemporal data: methods and applicationscited by 6
  10. 2024Survey of Graph Neural Network for Internet of Things and NextG Networkscited by 4
  11. 2023A Comprehensive Survey on Graph Summarization with Graph Neural Networkscited by 3
  12. 2026PRISM: Topology-Aware Cross-Modal Imputation for Modality-Deficient Federated Graph Learningcited by 3
15 more
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  2. 2023CAT: A Causally Graph Attention Network for Trimming Heterophilic Graphcited by 2
  3. 2024A Benchmark for Fairness-Aware Graph Learningcited by 2
  4. 2024Edge Graph Intelligence: Reciprocally Empowering Edge Networks with Graph Intelligencecited by 2
  5. 2025Searching Neural Architectures for Sensor Nodes on IoT Gatewayscited by 2
  6. 2025AuditVotes: Elevating Provable Defense for GNNs with Efficient Augmentation and Conditional Smoothingcited by 1
  7. 2022SCAI: A Spectral data Classification framework with Adaptive Inference for the IoT platformcited by 0
  8. 2023Medium. Permeation: SARS-COV-2 Painting Creation by Generative Modelcited by 0
  9. 2023Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Lehman Go Indifferentcited by 0
  10. 2023Incremental Semi-supervised Federated Learning for Health Inference via Mobile Sensingcited by 0
  11. 2023An FPGA-Based Accelerator for Graph Embedding using Sequential Training Algorithmcited by 0
  12. 2024A Review of Graph-Powered Data Quality Applications for IoT Monitoring Sensor Networkscited by 0
  13. 2025GNN-XAR: A Graph Neural Network for Explainable Activity Recognition in Smart Homescited by 0
  14. 2025JANUS: A Dual-Constraint Generative Framework for Stealthy Node Injection Attackscited by 0
  15. 2026Interpreting Manifolds and Graph Neural Embeddings from Internet of Things Traffic Flowscited by 0