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Special Issue "Recent Advances in Sensing and IoT Technologies"

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

Deadline for manuscript submissions: 31 December 2020.

Special Issue Editors

Dr. Raffaele Bruno
Website
Guest Editor
Institute for Informatics and Telematics (IIT), National Research Council of Italy (CNR), via G. Moruzzi, 1, I-56124, Pisa, Italy
Interests: MAC protocols for wireless networks; architectures and protocols for the Internet of things; vehicular networks; 5G networks; smart transportation; smart grids; smart buildings
Dr. Sherali Zeadally
Website
Guest Editor
College of Communication and Information, University of Kentucky, 315 Little Library Building, Lexington, KY 40506-0224, USA
Interests: cybersecurity; privacy; Internet of things; computer networks; mobile computing; energy-efficient networking
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) is a network connecting billions of physical objects and devices that are capable of sensing and sharing data between themselves and the Internet. Hence, one of the core goals of an IoT system is to provide a digital overlay of information over the physical world, in domains such as industries, smart cities, transportation, and energy. Thus, sensing and embedded systems are key enabling technologies for the IoT vision.

The increasing popularity of IoT applications is driving an exponential growth in connected IoT devices and generated data. As a result, the current IoT system architectures and communication technologies are facing significant technical challenges to meet the requirements of connectivity, scalability, and interoperability, as well as to efficiently support the transmission and processing of large volumes of data. Hence, there is a need for new enabling technologies, end-to-end architectures, and data management platforms.

This Special Issue aims to foster the dissemination of high-quality research with emerging ideas, approaches, theories, and practice to resolve the challenging issues related to the development of IoT ecosystems. Comprehensive review papers on the emerging research trends in the IoT domain are highly encouraged.

Topics of interest include, but are not limited to, the following:
  • Sensor technologies and protocols for IoT systems
  • IoT technologies and wireless sensor networks for smart cities and smart homes
  • IoT in 5G and beyond 5G networks
  • Edge, fog, and cloud computing architectures for IoT systems
  • SDN and NFV solutions for IoT systems
  • Mission-critical IoT applications like smart grid, healthcare, connected vehicles, and so on
  • Security, privacy, and trust management in IoT
  • IoT solutions for crowdsourcing and crowd-sensing.
Dr. Raffaele Bruno
Dr. Sherali Zeadally
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 papers will be 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 2000 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.

Published Papers (1 paper)

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Research

Open AccessArticle
Hybrid Deep Learning Predictor for Smart Agriculture Sensing Based on Empirical Mode Decomposition and Gated Recurrent Unit Group Model
Sensors 2020, 20(5), 1334; https://doi.org/10.3390/s20051334 - 29 Feb 2020
Cited by 10
Abstract
Smart agricultural sensing has enabled great advantages in practical applications recently, making it one of the most important and valuable systems. For outdoor plantation farms, the prediction of climate data, such as temperature, wind speed, and humidity, enables the planning and control of [...] Read more.
Smart agricultural sensing has enabled great advantages in practical applications recently, making it one of the most important and valuable systems. For outdoor plantation farms, the prediction of climate data, such as temperature, wind speed, and humidity, enables the planning and control of agricultural production to improve the yield and quality of crops. However, it is not easy to accurately predict climate trends because the sensing data are complex, nonlinear, and contain multiple components. This study proposes a hybrid deep learning predictor, in which an empirical mode decomposition (EMD) method is used to decompose the climate data into fixed component groups with different frequency characteristics, then a gated recurrent unit (GRU) network is trained for each group as the sub-predictor, and finally the results from the GRU are added to obtain the prediction result. Experiments based on climate data from an agricultural Internet of Things (IoT) system verify the development of the proposed model. The prediction results show that the proposed predictor can obtain more accurate predictions of temperature, wind speed, and humidity data to meet the needs of precision agricultural production. Full article
(This article belongs to the Special Issue Recent Advances in Sensing and IoT Technologies)
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