# Artificial Intelligence of Things: A Survey

arXiv: https://arxiv.org/abs/2410.19998 · HTML: https://mlsanity.com/paper/2410.19998/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 16 references that are in the map.
- First posted on arXiv 25 Oct 2024.

## Builds on (most cited first, 6 of 6)

- [Empowering Things with Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things](https://mlsanity.com/paper/2011.08612/) (2020)
- [SAFA: a Semi-Asynchronous Protocol for Fast Federated Learning with Low Overhead](https://mlsanity.com/paper/1910.01355/) (2019)
- [FedMultimodal: A Benchmark For Multimodal Federated Learning](https://mlsanity.com/paper/2306.09486/) (2023)
- [Enable Deep Learning on Mobile Devices: Methods, Systems, and Applications](https://mlsanity.com/paper/2204.11786/) (2022)
- [DeepMix: Mobility-aware, Lightweight, and Hybrid 3D Object Detection for Headsets](https://mlsanity.com/paper/2201.08812/) (2022)
- [MDLdroid: a ChainSGD-reduce Approach to Mobile Deep Learning for Personal Mobile Sensing](https://mlsanity.com/paper/2002.02897/) (2020)

## Built on by (most cited first, 12 of 12)

- [A Survey of Foundation Models for IoT: Taxonomy and Criteria-Based Analysis](https://mlsanity.com/paper/2506.12263/) (2025)
- [Towards Pervasive Distributed Agentic Generative AI -- A State of The Art](https://mlsanity.com/paper/2506.13324/) (2025)
- [Creation of AI-driven Smart Spaces for Enhanced Indoor Environments -- A Survey](https://mlsanity.com/paper/2412.14708/) (2024)
- [Hydra-Bench: A Benchmark for Multi-Modal Leaf Wetness Sensing](https://mlsanity.com/paper/2507.22685/) (2025)
- [Privacy-Preserving Explainable AIoT Application via SHAP Entropy Regularization](https://mlsanity.com/paper/2511.09775/) (2025)
- [On-device Large Multi-modal Agent for Human Activity Recognition](https://mlsanity.com/paper/2512.19742/) (2025)
- [AWEMixer: Adaptive Wavelet-Enhanced Mixer Network for Long-Term Time Series Forecasting](https://mlsanity.com/paper/2511.04722/) (2025)
- [Mixing Makes Markovian Contexts Cheap for Linear Bandits](https://mlsanity.com/paper/2603.12530/) (2026)
- [AI-IoT-Robotics Integration: Survey of Frameworks, Emerging Trends, and the Path Toward Connected Robotics](https://mlsanity.com/paper/2606.01015/) (2026)
- [FMplex: Model Virtualization for Serving Extensible Foundation Models](https://mlsanity.com/paper/2606.09643/) (2026)
- [Agentic IoT: Architectures, Applications, and Challenges Toward the Internet of Agents](https://mlsanity.com/paper/2607.04219/) (2026)
- [A Recommendation System Approach for Interference-Robust Sensor Subset Selection](https://mlsanity.com/paper/2608.11143/) (2026)

## Abstract (arXiv)

The integration of the Internet of Things (IoT) and modern Artificial Intelligence (AI) has given rise to a new paradigm known as the Artificial Intelligence of Things (AIoT). In this survey, we provide a systematic and comprehensive review of AIoT research. We examine AIoT literature related to sensing, computing, and networking & communication, which form the three key components of AIoT. In addition to advancements in these areas, we review domain-specific AIoT systems that are designed for various important application domains. We have also created an accompanying GitHub repository, where we compile the papers included in this survey: https://github.com/AIoT-MLSys-Lab/AIoT-Survey. This repository will be actively maintained and updated with new research as it becomes available. As both IoT and AI become increasingly critical to our society, we believe AIoT is emerging as an essential research field at the intersection of IoT and modern AI. We hope this survey will serve as a valuable resource for those engaged in AIoT research and act as a catalyst for future explorations to bridge gaps and drive advancements in this exciting field.