Next-Generation IoT and Smart Systems for Communication and Sensing

Topic Information

Dear Colleagues,

The following Topical Advisory Panel is dedicated to the advancement of next-generation Internet of Things (IoT) architectures and intelligent systems aimed at improving communication, sensing, and decision-making processes. In light of the increasing demand for interconnected devices and smart environments, the panel investigates pioneering strategies in embedded systems, distributed sensing, and communication technologies.

Special emphasis is placed on emerging applications within industrial automation, smart cities, and healthcare monitoring. These domains require robust designs that integrate intelligent decision-making, low-latency communication, and adaptive sensing capabilities.

Low-latency communication is particularly appreciated in smart cities, given the utilization of massive quantities of data, concerning technologies based on cloud computing, big data analytics, and the Internet of Things (IoT), which demands seamless connectivity and real-time data processing.

We therefore cordially invite the submission of scientific articles concerning (but not limited to) the following topics:

• IoT-enabled sensing
• Communication protocols
• Intelligent system architectures
• Embedded technologies and their applications (e.g., smart manufacturing, smart cities, environmental monitoring, healthcare systems, and urban infrastructure development)

Submissions may include original research, case studies, and innovative designs that tackle the challenges and opportunities present in this rapidly evolving domain.

Dr. Luis Pires
Dr. Ricardo Santos
Dr. Francisco Rego
Dr. Vitor Fialho
Dr. Dinh-Thuan Do
Dr. Vasco Velez
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Applied Sciences applsci	2.5	5.5	2011	19.8 Days	CHF 2400	Submit
Electronics electronics	2.6	6.1	2012	16.8 Days	CHF 2400	Submit
Future Internet futureinternet	3.6	8.3	2009	17 Days	CHF 1600	Submit
IoT IoT	2.8	8.7	2020	25.7 Days	CHF 1400	Submit
Technologies technologies	3.6	8.5	2013	21.8 Days	CHF 1600	Submit
Inventions inventions	1.9	4.9	2016	21.8 Days	CHF 1800	Submit
Sensors sensors	3.5	8.2	2001	19.7 Days	CHF 2600	Submit
Vehicles vehicles	2.2	5.3	2019	22.1 Days	CHF 1600	Submit

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Published Papers (2 papers)

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All Applied Sciences Electronics Future Internet IoT Technologies Inventions Sensors Vehicles

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23 pages, 4379 KiB  

Open AccessArticle

Large Vision Language Model: Enhanced-RSCLIP with Exemplar-Image Prompting for Uncommon Object Detection in Satellite Imagery

by Taiwo Efunogbon, Abimbola Efunogbon, Enjie Liu, Dayou Li and Renxi Qiu

Electronics 2025, 14(15), 3071; https://doi.org/10.3390/electronics14153071 - 31 Jul 2025

Viewed by 303

Abstract

Large Vision Language Models (LVLMs) have shown promise in remote sensing applications, yet struggle with “uncommon” objects that lack sufficient public labeled data. This paper presents Enhanced-RSCLIP, a novel dual-prompt architecture that combines text prompting with exemplar-image processing for cattle herd detection in [...] Read more.

Large Vision Language Models (LVLMs) have shown promise in remote sensing applications, yet struggle with “uncommon” objects that lack sufficient public labeled data. This paper presents Enhanced-RSCLIP, a novel dual-prompt architecture that combines text prompting with exemplar-image processing for cattle herd detection in satellite imagery. Our approach introduces a key innovation where an exemplar-image preprocessing module using crop-based or attention-based algorithms extracts focused object features which are fed as a dual stream to a contrastive learning framework that fuses textual descriptions with visual exemplar embeddings. We evaluated our method on a custom dataset of 260 satellite images across UK and Nigerian regions. Enhanced-RSCLIP with crop-based exemplar processing achieved 72% accuracy in cattle detection and 56.2% overall accuracy on cross-domain transfer tasks, significantly outperforming text-only CLIP (31% overall accuracy). The dual-prompt architecture enables effective few-shot learning and cross-regional transfer from data-rich (UK) to data-sparse (Nigeria) environments, demonstrating a 41% improvement over baseline approaches for uncommon object detection in satellite imagery. Full article

(This article belongs to the Topic Next-Generation IoT and Smart Systems for Communication and Sensing)

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36 pages, 2135 KiB  

Open AccessArticle

Privacy Framework for the Development of IoT-Based Systems

by Yaqin Y. Shaheen, Miguel J. Hornos and Carlos Rodríguez-Domínguez

Future Internet 2025, 17(8), 322; https://doi.org/10.3390/fi17080322 - 22 Jul 2025

Viewed by 234

Abstract

Addressing privacy concerns is one of the key challenges facing the development of Internet of Things (IoT)-based systems (IoTSs). As IoT devices often collect and process personal and sensitive information, strict privacy policies must be defined and enforced to keep data secure and [...] Read more.

Addressing privacy concerns is one of the key challenges facing the development of Internet of Things (IoT)-based systems (IoTSs). As IoT devices often collect and process personal and sensitive information, strict privacy policies must be defined and enforced to keep data secure and safe, ensuring security and regulatory compliance. Any data breach could compromise the security of the system, leading to various types of threats and attacks, some of which could even endanger human life. Therefore, it is crucial to design and build a comprehensive and general privacy framework for the development of IoTSs. This framework should not be limited to specific IoTS domains but should be general enough to support and cover most IoTS domains. In this paper, we present a framework that assists developers by (i) enabling them to build IoTSs that comply with privacy standards, such as the General Data Protection Regulation (GDPR), and (ii) providing a simplified and practical approach to identifying and addressing privacy concerns. In addition, the framework enables developers to implement effective countermeasures. Full article

(This article belongs to the Topic Next-Generation IoT and Smart Systems for Communication and Sensing)

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