[HTML][HTML] Internet of Intelligent Things: A convergence of embedded systems, edge computing and machine learning

F Oliveira, DG Costa, F Assis, I Silva - Internet of Things, 2024 - Elsevier
This article comprehensively reviews the emerging concept of Internet of Intelligent Things
(IoIT), adopting an integrated perspective centred on the areas of embedded systems, edge …

Load-aware continuous-time optimization for multi-agent systems: Toward dynamic resource allocation and real-time adaptability

Q Wang, W Li, A Mohajer - Computer Networks, 2024 - Elsevier
In the realm of next-generation mobile communication networks, characterized by dynamic
and evolving workloads, the efficient resource allocation becomes paramount for achieving …

[HTML][HTML] IoT—A Promising Solution to Energy Management in Smart Buildings: A Systematic Review, Applications, Barriers, and Future Scope

M Poyyamozhi, B Murugesan, N Rajamanickam… - Buildings, 2024 - mdpi.com
The use of Internet of Things (IoT) technology is crucial for improving energy efficiency in
smart buildings, which could minimize global energy consumption and greenhouse gas …

Disruptive 6G architecture: Software-centric, AI-driven, and digital market-based mobile networks

AM Alberti, DGS Pivoto, TT Rezende, AVA Leal… - Computer Networks, 2024 - Elsevier
Mobile communications have followed a progression model detailed by the Gartner hype
cycle, from a proof-of-concept to widespread productivity. As fifth-generation (5G) mobile …

Federated learning for millimeter-wave spectrum in 6G networks: applications, challenges, way forward and open research issues

F Qamar, SHA Kazmi, MUA Siddiqui, R Hassan… - PeerJ Computer …, 2024 - peerj.com
The emergence of 6G networks promises ultra-high data rates and unprecedented
connectivity. However, the effective utilization of the millimeter-wave (mmWave) as a critical …

A comprehensive survey on machine learning techniques in opportunistic networks: Advances, challenges and future directions

J Gandhi, Z Narmawala - Pervasive and Mobile Computing, 2024 - Elsevier
Abstract Machine Learning (ML) is growing in popularity and is applied in numerous fields to
solve complex problems. Opportunistic Networks are a type of Ad-hoc Network where a …

[HTML][HTML] Artificial intelligence probabilities scheme for disease prevention data set construction in intelligent smart healthcare scenario

B RaviKrishna, ME Seno, M Raparthi, RR Yellu… - SLAS technology, 2024 - Elsevier
In the face of an aging population, smart healthcare services are now within reach, thanks to
the proliferation of high-speed internet and other forms of digital technology. Data problems …

Intelligent Computation Offloading Based on Digital Twin-Enabled 6G Industrial IoT

J Wu, R Zuo - Applied Sciences, 2024 - mdpi.com
Digital twin (DT) technology, which can provide larger and more accurate amounts of data,
combined with the additional computility brought by virtual environments, can support more …

Uncovering the Limitations and Insights of Packet Status Prediction Models in IEEE 802.15. 4-Based Wireless Networks and Insights from Data Science

M Ávalos-Arce, H Pérez-Díaz, C Del-Valle-Soto… - Informatics, 2024 - mdpi.com
Wireless networks play a pivotal role in various domains, including industrial automation,
autonomous vehicles, robotics, and mobile sensor networks. This research investigates the …

Spectrum Allocation in 5G and Beyond Intelligent Ubiquitous Networks

B Ravi, U Verma - International Journal of Network …, 2025 - Wiley Online Library
Effective spectrum allocation in 5G and beyond intelligent ubiquitous networks is vital for
predicting future frequency band needs and ensuring optimal network performance. As …