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Advancements and Challenges in IoT Communication Technologies for a Connected World: 2nd Edition

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: 30 November 2026 | Viewed by 6849

Special Issue Editors

Dr. Andrea Ria

E-Mail Website
Guest Editor
Department of Information Engineering, University of Pisa, Via G. Caruso 16, 56122 Pisa, PI, Italy
Interests: low-voltage; sensor interfaces; IoT system; integrated circuits
Special Issues, Collections and Topics in MDPI journals
Dr. Francesco Paolo Chietera

E-Mail Website
Guest Editor
Department of Electrical and Information Engineering, Politecnico di Bari, Via E. Orabona 4, 70125 Bari, Italy
Interests: RFID technologies; antennas; 3D-printing; additive manufacturing in electromagnetics; IoT enabling technologies; smart electromagnetic devices
Special Issues, Collections and Topics in MDPI journals
Dr. Xiao Tang

E-Mail Website
Guest Editor
School of Information and Communication Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Interests: wireless AI; game theories; information security; UAV networks; integrated communication and computation; RIS communications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

This Special Issue seeks the submission of contributions focused on the intersection of IoT communication technologies and their applications in creating a more interconnected society. Such submissions should focus on critical areas such as the integration of sensors into next-generation communication systems, new communication paradigms, and technologies such as Internet of Drones (IoD), Industrial Internet of Things (IIoT), machine-to-machine (M2M) communications, RFID, and zero-power communications and their applications in smart agriculture and smart cities. The aim of this Special Issue is to address the scientific and technological challenges faced when enhancing data transmission, processing capabilities, and energy efficiency across diverse IoT systems. Contributions are welcome to explore, among other topics, progress in RFID for efficient data gathering, the adoption of zero-power technologies to prolong the lifespan of IoT components, and the exploitation of IoD and IIoT to enhance operational efficiency and communication system performance. For this Special Issue, we encourage submissions of original research articles, comprehensive reviews, and case studies that showcase novel approaches to overcoming the limitations of current IoT communication technologies, with a particular emphasis on their practical implications in smart agriculture and smart city development.

Dr. Andrea Ria
Dr. Francesco Paolo Chietera
Dr. Xiao Tang
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 250 words) can be sent to the Editorial Office for assessment.

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. Sensors is an international peer-reviewed open access semimonthly 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 2600 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.

Keywords

  • IoT
  • communication
  • sensors

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Related Special Issue

Published Papers (2 papers)

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18 pages, 2584 KB  
Article
A High-Frequency Wearable IMU-Based System for Countermovement Jump Assessment
by Antonio Pousibet-Garrido, Cristina Benavente, Juan A. Moreno-Pérez, Sergio Pérez-Regalado, Miguel A. Carvajal, Ignacio J. Chirosa and Pablo Escobedo
Sensors 2026, 26(5), 1408; https://doi.org/10.3390/s26051408 - 24 Feb 2026
Viewed by 697
Abstract
The countermovement jump (CMJ) is widely used to monitor neuromuscular performance in sport, but its assessment is largely dependent on force platforms, which limits their use outside the laboratory due to their cost and limited portability. This work describes the development and validation [...] Read more.
The countermovement jump (CMJ) is widely used to monitor neuromuscular performance in sport, but its assessment is largely dependent on force platforms, which limits their use outside the laboratory due to their cost and limited portability. This work describes the development and validation of a fully custom wearable inertial measurement unit (IMU) system for CMJ assessment. The platform is based on a single IMU placed on the lower back and sampled at 1 kHz, and includes Bluetooth Low Energy (BLE) communication together with dedicated PC and smartphone applications. A new algorithm based on the derivative of vertical acceleration was implemented to identify take-off and landing instants. The system was evaluated using 119 CMJ trials performed by 19 participants and validated against a force platform used as the criterion reference. Different acceleration thresholds were tested, with 0.2 g providing the best compromise between detection robustness and the statistical quality of the measurements, yielding a detection rate of 97.43%. Agreement analysis showed a small systematic underestimation of flight time (bias = −0.0117 s), with moderate limits of agreement across the observed range. These results indicate that the proposed system may be suitable for practical, field-based CMJ monitoring, although the observed variability relative to force-platform measurements should be considered, particularly in applications requiring individual-level decision making. Full article
(This article belongs to the Special Issue Advancements and Challenges in IoT Communication Technologies for a Connected World: 2nd Edition)
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47 pages, 2691 KB  
Systematic Review
Buzzing with Intelligence: A Systematic Review of Smart Beehive Technologies
by Josip Šabić, Toni Perković, Petar Šolić and Ljiljana Šerić
Sensors 2025, 25(17), 5359; https://doi.org/10.3390/s25175359 - 29 Aug 2025
Cited by 5 | Viewed by 5594
Abstract
Smart-beehive technologies represent a paradigm shift in beekeeping, transitioning from traditional, reactive methods toward proactive, data-driven management. This systematic literature review investigates the current landscape of intelligent systems applied to beehives, focusing on the integration of IoT-based monitoring, sensor modalities, machine learning techniques, [...] Read more.
Smart-beehive technologies represent a paradigm shift in beekeeping, transitioning from traditional, reactive methods toward proactive, data-driven management. This systematic literature review investigates the current landscape of intelligent systems applied to beehives, focusing on the integration of IoT-based monitoring, sensor modalities, machine learning techniques, and their applications in precision apiculture. The review adheres to PRISMA guidelines and analyzes 135 peer-reviewed publications identified through searches of Web of Science, IEEE Xplore, and Scopus between 1990 and 2025. It addresses key research questions related to the role of intelligent systems in early problem detection, hive condition monitoring, and predictive intervention. Common sensor types include environmental, acoustic, visual, and structural modalities, each supporting diverse functional goals such as health assessment, behavior analysis, and forecasting. A notable trend toward deep learning, computer vision, and multimodal sensor fusion is evident, particularly in applications involving disease detection and colony behavior modeling. Furthermore, the review highlights a growing corpus of publicly available datasets critical for the training and evaluation of machine learning models. Despite the promising developments, challenges remain in system integration, dataset standardization, and large-scale deployment. This review offers a comprehensive foundation for the advancement of smart apiculture technologies, aiming to improve colony health, productivity, and resilience in increasingly complex environmental conditions. Full article
(This article belongs to the Special Issue Advancements and Challenges in IoT Communication Technologies for a Connected World: 2nd Edition)
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