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Special Issue Information

Dear Colleagues,

This Special Issue aims to provide a comprehensive overview of the current state of the art in Future Internet technology in the USA. We invite research articles that will consolidate our understanding in this area.

The Special Issue will publish full research papers and reviews. Potential topics include, but are not limited to, the following research areas:

Advanced communication network infrastructures;
Internet of Things;
Centralized and distributed data centers;
Industrial internet;
Embedded computing;
5G/6G networking;
IoT platforms, integration, and services;
Software-defined network functions and network virtualization;
Quality of service in wireless and mobile networks;
Vehicular cloud networks;
Cloud-let and fog computing;
Cyber–physical systems;
Smart energy systems;
Smart healthcare systems;
Smart manufacturing lines;
Smart cities;
Human–computer interaction and usability;
Smart learning systems;
Artificial and augmented intelligence;
Cyber security compliance;
Public safety;
Human behavior modeling;
Hardware security;
Multi-access edge computing;
Digital twins for future internet;
Zero-touch management for IoT;
Metaverse and future networks.

Dr. Eirini Eleni Tsiropoulou
Prof. Dr. Symeon Papavassiliou
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Related Special Issue

Published Papers (1 paper)

Research

23 pages, 7707 KiB

Open AccessArticle

NeXtFusion: Attention-Based Camera-Radar Fusion Network for Improved Three-Dimensional Object Detection and Tracking

by Priyank Kalgaonkar and Mohamed El-Sharkawy

Future Internet 2024, 16(4), 114; https://doi.org/10.3390/fi16040114 - 28 Mar 2024

Viewed by 594

Abstract

Accurate perception is crucial for autonomous vehicles (AVs) to navigate safely, especially in adverse weather and lighting conditions where single-sensor networks (e.g., cameras or radar) struggle with reduced maneuverability and unrecognizable targets. Deep Camera-Radar fusion neural networks offer a promising solution for reliable AV perception under any weather and lighting conditions. Cameras provide rich semantic information, while radars act like an X-ray vision, piercing through fog and darkness. This work proposes a novel, efficient Camera-Radar fusion network called NeXtFusion for robust AV perception with an improvement in object detection accuracy and tracking. Our proposed approach of utilizing an attention module enhances crucial feature representation for object detection while minimizing information loss from multi-modal data. Extensive experiments on the challenging nuScenes dataset demonstrate NeXtFusion’s superior performance in detecting small and distant objects compared to other methods. Notably, NeXtFusion achieves the highest mAP score (0.473) on the nuScenes validation set, outperforming competitors like OFT (35.1% improvement) and MonoDIS (9.5% improvement). Additionally, NeXtFusion demonstrates strong performance in other metrics like mATE (0.449) and mAOE (0.534), highlighting its overall effectiveness in 3D object detection. Furthermore, visualizations of nuScenes data processed by NeXtFusion further demonstrate its capability to handle diverse real-world scenarios. These results suggest that NeXtFusion is a promising deep fusion network for improving AV perception and safety for autonomous driving. Full article

(This article belongs to the Special Issue State-of-the-Art Future Internet Technology in USA 2024–2025)

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