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Feature Papers in the 'Sensor Networks' Section 2024
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Feature Papers in the 'Sensor Networks' Section 2024

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

Deadline for manuscript submissions: 31 December 2024 | Viewed by 535

Special Issue Editors

Prof. Dr. Yuh-Shyan Chen

E-Mail Website
Guest Editor
Department of Computer Science and Information Engineering, National Taipei University, No. 151, University Rd., San Shia District, New Taipei City 23741, Taiwan
Interests: wireless sensor networks; fog computing for sensors; software-defined sensors; sensors with 5G/6G; Internet of Things
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Wei Yi

E-Mail Website
Guest Editor
School of Information and Communication Engineering, University of Electronics Science and Technology of China, Chengdu 611731, China
Interests: multi-target tracking; sensor networks; resources management; multi-sensor information fusion
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce that the “Sensor Networks” Section is now compiling a collection of papers submitted by the Section’s Editorial Board Members (EBMs) and outstanding scholars in this research field. We welcome contributions and recommendations from EBMs.

The Section covers theoretical and experimental problems, especially considering the rise of Internet of things (IoT) applications that allow several devices to connect in a smart way. In general, this Section aims to provide researchers with a platform on which to publish their scientific work that can influence the scientific community as well as the general public.

We would also like to take this opportunity to call on more excellent scholars to join the Sensor Networks Section so that we can work together to further develop this exciting field of research.

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

  • Smart sensor networks;
  • Power consumption/energy-harvesting sensor networks;
  • Energy-autonomous and low-power systems for the IoT;
  • Machine learning on sensors;
  • Cross-layer optimization;
  • Wireless sensor networks;
  • Routing protocols in sensor networks;
  • Embedded networked sensors;
  • Software-defined networks;
  • Underwater sensor networks;
  • Distributed sensor networks;
  • Ad hoc networks;
  • Industrial sensor networks;
  • Sensor network security, privacy, and threat detection;
  • Data calibration and fault tolerance;
  • Sensor network data fusion and data aggregation;
  • Sensor node localization;
  • Medium access control (MAC) protocols for sensor networks;
  • Artificial intelligence in sensor networks;
  • Edge computing in wireless sensor networks;
  • AI/ML for integrated sensing and communication;
  • Applications of sensor networks in area monitoring, healthcare monitoring, habitat monitoring, environmental/Earth sensing, etc.;
  • Advanced and intelligent sensor applications.

Prof. Dr. Yuh-Shyan Chen
Prof. Dr. Wei Yi
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. 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

  • sensor networks
  • wireless sensor networks
  • sensing and communication
  • IoT

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Published Papers (1 paper)

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Research

20 pages, 1614 KiB  
Article
Energy-Efficient Edge and Cloud Image Classification with Multi-Reservoir Echo State Network and Data Processing Units
by E. J. López-Ortiz, M. Perea-Trigo, L. M. Soria-Morillo, J. A. Álvarez-García and J. J. Vegas-Olmos
Sensors 2024, 24(11), 3640; https://doi.org/10.3390/s24113640 - 4 Jun 2024
Abstract
In an era dominated by Internet of Things (IoT) devices, software-as-a-service (SaaS) platforms, and rapid advances in cloud and edge computing, the demand for efficient and lightweight models suitable for resource-constrained devices such as data processing units (DPUs) has surged. Traditional deep learning [...] Read more.
In an era dominated by Internet of Things (IoT) devices, software-as-a-service (SaaS) platforms, and rapid advances in cloud and edge computing, the demand for efficient and lightweight models suitable for resource-constrained devices such as data processing units (DPUs) has surged. Traditional deep learning models, such as convolutional neural networks (CNNs), pose significant computational and memory challenges, limiting their use in resource-constrained environments. Echo State Networks (ESNs), based on reservoir computing principles, offer a promising alternative with reduced computational complexity and shorter training times. This study explores the applicability of ESN-based architectures in image classification and weather forecasting tasks, using benchmarks such as the MNIST, FashionMnist, and CloudCast datasets. Through comprehensive evaluations, the Multi-Reservoir ESN (MRESN) architecture emerges as a standout performer, demonstrating its potential for deployment on DPUs or home stations. In exploiting the dynamic adaptability of MRESN to changing input signals, such as weather forecasts, continuous on-device training becomes feasible, eliminating the need for static pre-trained models. Our results highlight the importance of lightweight models such as MRESN in cloud and edge computing applications where efficiency and sustainability are paramount. This study contributes to the advancement of efficient computing practices by providing novel insights into the performance and versatility of MRESN architectures. By facilitating the adoption of lightweight models in resource-constrained environments, our research provides a viable alternative for improved efficiency and scalability in modern computing paradigms. Full article
(This article belongs to the Special Issue Feature Papers in the 'Sensor Networks' Section 2024)
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