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Technological Advances for Sensing in IoT-Based Networks

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

Deadline for manuscript submissions: 25 October 2026 | Viewed by 455

Special Issue Editors


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Guest Editor
Department of AI and Big Data, Woosong University, Daejeon 34606, Republic of Korea
Interests: artificial intelligence; computer vision; internet of things; blockchain technology; cloud computing; cryptography; information security
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of AI and Big Data, Woosong University, Daejeon 34606, Republic of Korea
Interests: artificial intelligence; prognostics and health management; electric vehicles; industrial robots; rotating machines
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid urbanization of modern cities demands some essential steps to build a sustainable environment, such as innovative, data-driven solutions to point out the critical challenges in energy management, traffic optimization, and public safety. Artificial Intelligence is one of the fastest-growing technologies to evolve the Internet of Things (IoT), and sensors play a crucial role as an essential part. Sensors can link and merge different elements to create a smart worldwide network. This collection brings together cutting-edge research on IoT sensors, wireless sensor networks, and IoT applications across various domains. IoT integrates heterogeneous sensor communication protocols and intelligent data processing techniques, enabling applications in healthcare, automation, smart city monitoring, and other sectors. The growth of IoT-based networks brings lots of challenges in terms of scalability, security, privacy, energy efficiency, and reliability. To address these challenges, the Special Issue invites a combination of innovations in sensing hardware, data fusion, cloud computing, and beyond.

This Special Issue invites novel research and review articles on recent advancements in IoT-based sensor networks. The goal is to highlight both theoretical and practical implementations that push the boundaries of IoT-enabled sensing technologies.

Potential topics include, but are not limited to, the following:

  • Sensor interoperability and standardization in the IoT ecosystem.
  • Blockchain-enabled trust models for IoT sensing.
  • Low-power wide area network (LPWAN) and protocols for large-scale IoT sensing.
  • AI/ML-driven sensing data fusion in IoT applications.
  • IoT in a sustainable environment.
  • Healthcare in an AI-based IoT network.
  • Healthcare and biomedical IoT sensing systems.
  • Digital twins and virtual sensing for IoT applications.
  • Privacy-preserving techniques for sensing IoT data.
  • Distributed AI for edge-based cloud computing in sensor networks.   
  • New designs for low-power sensors.
  • Innovations in sensor fabrication and materials.
  • Hardware security for IoT devices.
  • Integration of edge computing with sensing hardware.

Dr. Saurabh Singh
Dr. Prashant Kumar
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-based networks
  • sensing
  • artificial intelligence
  • blockchain technology
  • wireless sensor network
  • LPWAN

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Published Papers (1 paper)

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Research

19 pages, 3120 KB  
Article
Computer-Vision- and Edge-Enabled Real-Time Assistance Framework for Visually Impaired Persons with LPWAN Emergency Signaling
by Ghadah Naif Alwakid, Mamoona Humayun and Zulfiqar Ahmad
Sensors 2025, 25(22), 7016; https://doi.org/10.3390/s25227016 - 17 Nov 2025
Viewed by 318
Abstract
In recent decades, various assistive technologies have emerged to support visually impaired individuals. However, there remains a gap in terms of solutions that provide efficient, universal, and real-time capabilities by combining robust object detection, robust communication, continuous data processing, and emergency signaling in [...] Read more.
In recent decades, various assistive technologies have emerged to support visually impaired individuals. However, there remains a gap in terms of solutions that provide efficient, universal, and real-time capabilities by combining robust object detection, robust communication, continuous data processing, and emergency signaling in dynamic environments. In many existing systems, trade-offs are made in range, latency, or reliability when applied in changing outdoor or indoor scenarios. In this study, we propose a comprehensive framework specifically tailored for visually impaired people, integrating computer vision, edge computing, and a dual-channel communication architecture including low-power wide-area network (LPWAN) technology. The system utilizes the YOLOv5 deep-learning model for the real-time detection of obstacles, paths, and assistive tools (such as the white cane) with high performance: precision 0.988, recall 0.969, and mAP 0.985. Implementation of edge-computing devices is introduced to offload computational load from central servers, enabling fast local processing and decision-making. The communications subsystem uses Wi-Fi as the primary link, while a LoRaWAN channel acts as a fail-safe emergency alert network. An IoT-based panic button is incorporated to transmit immediate location-tagged alerts, enabling rapid response by authorities or caregivers. The experimental results demonstrate the system’s low latency and reliable operations under varied real-world conditions, indicating significant potential to improve independent mobility and quality of life for visually impaired people. The proposed solution offers cost-effective and scalable architecture suitable for deployment in complex and challenging environments where real-time assistance is essential. Full article
(This article belongs to the Special Issue Technological Advances for Sensing in IoT-Based Networks)
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