Recent advances in artificial intelligence for wireless internet of things and cyber–physical systems: A comprehensive survey

BA Salau, A Rawal, DB Rawat - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
Advances in artificial intelligence (AI) and wireless technology are driving forward the large
deployment of interconnected smart technologies that constitute cyber–physical systems …

Federated learning for internet of things: A comprehensive survey

DC Nguyen, M Ding, PN Pathirana… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of
intelligent services and applications empowered by artificial intelligence (AI). Traditionally …

Machine learning for wireless communications in the Internet of Things: A comprehensive survey

J Jagannath, N Polosky, A Jagannath, F Restuccia… - Ad Hoc Networks, 2019 - Elsevier
Abstract The Internet of Things (IoT) is expected to require more effective and efficient
wireless communications than ever before. For this reason, techniques such as spectrum …

The challenges of artificial intelligence in wireless networks for the Internet of Things: Exploring opportunities for growth

I Ahmad, S Shahabuddin, T Sauter… - IEEE Industrial …, 2020 - ieeexplore.ieee.org
The Internet of Things (IoT), a term first coined by Ashton in [1], is an extension of network
connectivity to physical devices, such as actuators, sensors, and mobile devices, that are …

Communication-efficient and distributed learning over wireless networks: Principles and applications

J Park, S Samarakoon, A Elgabli, J Kim… - Proceedings of the …, 2021 - ieeexplore.ieee.org
Machine learning (ML) is a promising enabler for the fifth-generation (5G) communication
systems and beyond. By imbuing intelligence into the network edge, edge nodes can …

Federated learning based on CTC for heterogeneous internet of things

D Gao, H Wang, XZ Guo, L Wang, G Gui… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
Federated learning (FL) is a machine learning technique that allows for on-site data
collection and processing without sacrificing data privacy and transmission. Heterogeneity is …

Learning paradigms for communication and computing technologies in IoT systems

W Ejaz, M Basharat, S Saadat, AM Khattak… - Computer …, 2020 - Elsevier
Wireless communication and computation technologies are becoming increasingly complex
and dynamic due to the sophisticated and ubiquitous Internet of things (IoT) applications …

Deep learning for intelligent IoT: Opportunities, challenges and solutions

YB Zikria, MK Afzal, SW Kim, A Marin… - Computer …, 2020 - Elsevier
Next-generation wireless networks have to be robust and self-sustained. Internet of things
(IoT) is reshaping the technological adaptation in the daily life of human beings. IoT …

Communication-efficient and distributed learning over wireless networks: Principles and applications

J Park, S Samarakoon, A Elgabli, J Kim… - arXiv preprint arXiv …, 2020 - arxiv.org
Machine learning (ML) is a promising enabler for the fifth generation (5G) communication
systems and beyond. By imbuing intelligence into the network edge, edge nodes can …

Federated learning for internet of things: Recent advances, taxonomy, and open challenges

LU Khan, W Saad, Z Han, E Hossain… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
The Internet of Things (IoT) will be ripe for the deployment of novel machine learning
algorithm for both network and application management. However, given the presence of …