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Secure and Decentralised IoT Systems

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

Deadline for manuscript submissions: 20 October 2025 | Viewed by 1265

Special Issue Editor


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Guest Editor
Computer Science Section, University of Camerino, 62032 Camerino, Italy
Interests: formal models for complex systems; IoT; blockchain

Special Issue Information

Dear Colleagues,

The Internet-of-Things (IoT) is one of the modern technological revolutions that enables communication amongst a plethora of different devices. The IoT is essential in implementing various visions such as smart cities, smart buildings, and industry 4.0. Although IoT applications are now spreading throughout everyday life, they are still organised vertically in an isolated manner. The distributed interconnection of IoT devices is still a challenge since devices have different communication protocols, heterogeneous hardware, and different security capabilities and belong to different domains.

To date, some solutions have been proposed but are mainly based on a logically centralised infrastructure. This introduces a single trusted party that prevents data democratisation and holds all sensitive data. A centralised solution also limits scalability.

This Special Issue aims to collect papers on conceptual and practical approaches for building secure and decentralised IoT applications.

Topics include but are not limited to the following:

  • Latest tools and methodologies that underpin the design and implementation of IoT applications.
  • Use of blockchain for designing and building decentralised and secure IoT applications.
  • Industrial case studies.
  • State of the art and future perspectives about the design, validation, and implementation of decentralised and secure IoT applications.

This Special Issue will critically review most aspects of various technologies and methodologies such as distributed ledger technologies and smart contracts for the IoT; simulation, modelling, and programming frameworks; machine learning; testing; edge computing; federated learning; and real-life case studies for building decentralised and secure IoT applications.

Dr. Diletta Romana Cacciagrano
Guest Editor

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. 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
  • blockchain
  • edge computing
  • machine learning
  • scalability
  • security

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Published Papers (2 papers)

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Research

20 pages, 4569 KiB  
Article
Lightweight Vision Transformer for Frame-Level Ergonomic Posture Classification in Industrial Workflows
by Luca Cruciata, Salvatore Contino, Marianna Ciccarelli, Roberto Pirrone, Leonardo Mostarda, Alessandra Papetti and Marco Piangerelli
Sensors 2025, 25(15), 4750; https://doi.org/10.3390/s25154750 - 1 Aug 2025
Viewed by 408
Abstract
Work-related musculoskeletal disorders (WMSDs) are a leading concern in industrial ergonomics, often stemming from sustained non-neutral postures and repetitive tasks. This paper presents a vision-based framework for real-time, frame-level ergonomic risk classification using a lightweight Vision Transformer (ViT). The proposed system operates directly [...] Read more.
Work-related musculoskeletal disorders (WMSDs) are a leading concern in industrial ergonomics, often stemming from sustained non-neutral postures and repetitive tasks. This paper presents a vision-based framework for real-time, frame-level ergonomic risk classification using a lightweight Vision Transformer (ViT). The proposed system operates directly on raw RGB images without requiring skeleton reconstruction, joint angle estimation, or image segmentation. A single ViT model simultaneously classifies eight anatomical regions, enabling efficient multi-label posture assessment. Training is supervised using a multimodal dataset acquired from synchronized RGB video and full-body inertial motion capture, with ergonomic risk labels derived from RULA scores computed on joint kinematics. The system is validated on realistic, simulated industrial tasks that include common challenges such as occlusion and posture variability. Experimental results show that the ViT model achieves state-of-the-art performance, with F1-scores exceeding 0.99 and AUC values above 0.996 across all regions. Compared to previous CNN-based system, the proposed model improves classification accuracy and generalizability while reducing complexity and enabling real-time inference on edge devices. These findings demonstrate the model’s potential for unobtrusive, scalable ergonomic risk monitoring in real-world manufacturing environments. Full article
(This article belongs to the Special Issue Secure and Decentralised IoT Systems)
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22 pages, 1386 KiB  
Article
A Scalable Approach to IoT Interoperability: The Share Pattern
by Riccardo Petracci and Rosario Culmone
Sensors 2025, 25(15), 4701; https://doi.org/10.3390/s25154701 - 30 Jul 2025
Viewed by 256
Abstract
The Internet of Things (IoT) is transforming how devices communicate, with more than 30 billion connected units today and projections exceeding 40 billion by 2025. Despite this growth, the integration of heterogeneous systems remains a significant challenge, particularly in sensitive domains like healthcare, [...] Read more.
The Internet of Things (IoT) is transforming how devices communicate, with more than 30 billion connected units today and projections exceeding 40 billion by 2025. Despite this growth, the integration of heterogeneous systems remains a significant challenge, particularly in sensitive domains like healthcare, where proprietary standards and isolated ecosystems hinder interoperability. This paper presents an extended version of the Share design pattern, a lightweight and contract-based mechanism for dynamic service composition, tailored for resource-constrained IoT devices. Share enables decentralized, peer-to-peer integration by exchanging executable code in our examples written in the LUA programming language. This approach avoids reliance on centralized infrastructures and allows services to discover and interact with each other dynamically through pattern-matching and contract validation. To assess its suitability, we developed an emulator that directly implements the system under test in LUA, allowing us to verify both the structural and behavioral constraints of service interactions. Our results demonstrate that Share is scalable and effective, even in constrained environments, and supports formal correctness via design-by-contract principles. This makes it a promising solution for lightweight, interoperable IoT systems that require flexibility, dynamic configuration, and resilience without centralized control. Full article
(This article belongs to the Special Issue Secure and Decentralised IoT Systems)
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