Special Issue "Internet of Things and Internet of Everything: Current Trends, Challenges, and New Perspectives"

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (31 January 2023) | Viewed by 1227

Special Issue Editors

Prof. Dr. Vasco N. G. J. Soares
E-Mail Website
Guest Editor
1. Polytechnic Institute of Castelo Branco, Av. Pedro Álvares Cabral No. 12, 6000-084 Castelo Branco, Portugal
2. Instituto de Telecomunicações, Rua Marquês d’Ávila e Bolama, 6201-001 Covilhã, Portugal
Interests: smart cities; Internet of Things; delay/disruption tolerant networks; vehicular networks
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Juan Francisco De Paz Santana
E-Mail Website
Guest Editor
Expert Systems and Applications Lab, Faculty of Science, University of Salamanca, 37008 Salamanca, Spain
Interests: ambient intelligence; artificial intelligence; multi-agent systems; wireless sensor networks; big data; edge computing; Internet of Things
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of Everything (IoE) arises from the growing Internet of Things (IoT) devices deployment, to describe a more complex system that also encompasses people, data, and processes. It aims to convert collected information into actions, facilitate data-based decision-making, thus improving efficiency, sustainability, and profitability in a wide range of applications and use cases. It also provides new capabilities and richer experiences to people.

This special issue aims at bringing together researchers, academicians, scientists, and students to exchange and share their experiences and research results on the most recent innovations, trends, and concerns as well as practical challenges encountered, and solutions adopted in the fields of the Internet of Everything and Internet of Things. 

The topics of this special issue include, but are not limited to, the following:

  • IoT/IoE Networks
  • IoT/IoE Applications and Services
  • IoT/IoE Architectures
  • IoT/IoE Industry 5.0
  • IoT/IoE Communication Technologies
  • IoT/IoE Edge and Cloud Architectures
  • IoT/IoE Experimental Results and Deployment Scenarios
  • IoT/IoE Recent Trends
  • Human Interaction with IoT/IoE
  • Energy Efficiency and Sustainability in IoT/IoE
  • Big Data and IoT/IoE
  • Artificial Intelligence and IoT/IoE
  • Machine Learning and IoT/IoE
  • Healthcare and IoT/IoE
  • Blockchain and IoT/IoE
  • Security and Privacy for IoT/IoE
  • Interoperability in IoT/IoE
  • Software Engineering for IoT/IoE
  • Intelligent/Smart IoT/IoE
  • Smart Cities and Smart Homes

Prof. Dr. Vasco N. G. J. Soares
Prof. Dr. Juan Francisco De Paz Santana
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. Future Internet is an international peer-reviewed open access monthly 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 1600 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

  • Internet of Things
  • Internet of Everything
  • trends
  • challenges
  • future directions

Published Papers (2 papers)

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Research

Article
Digitalization of Distribution Transformer Failure Probability Using Weibull Approach towards Digital Transformation of Power Distribution Systems
Future Internet 2023, 15(2), 45; https://doi.org/10.3390/fi15020045 - 25 Jan 2023
Viewed by 386
Abstract
Digitalization of the failure-probability modeling of crucial components in power-distribution systems is important for improving risk and reliability analysis for system-maintenance and asset-management practices. This paper aims to implement a Python programming-based Weibull approach for digitalization of distribution-transformer (DT) failures, considering a regional [...] Read more.
Digitalization of the failure-probability modeling of crucial components in power-distribution systems is important for improving risk and reliability analysis for system-maintenance and asset-management practices. This paper aims to implement a Python programming-based Weibull approach for digitalization of distribution-transformer (DT) failures, considering a regional section of DTs in Sri Lanka as a case study. A comprehensive analysis for DT-failure data for six years has been utilized to derive a Weibull distribution analysis for DTs. The interpretation of the resulting beta and alpha parameters of the Weibull analysis for different categories of DTs in the selected region is also presented. The resulting data can be uploaded to computerized maintenance-management systems (CMMS), to adopt conclusions or resolutions reached by the asset and maintenance managers. Ultimately, failure-probability modeling is beneficial for decision-making processes for higher management aiming for the digital transformation of power-distribution systems. Full article
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Article
A Novel NODE Approach Combined with LSTM for Short-Term Electricity Load Forecasting
Future Internet 2023, 15(1), 22; https://doi.org/10.3390/fi15010022 - 30 Dec 2022
Viewed by 539
Abstract
Electricity load forecasting has seen increasing importance recently, especially with the effectiveness of deep learning methods growing. Improving the accuracy of electricity load forecasting is vital for public resources management departments. Traditional neural network methods such as long short-term memory (LSTM) and bidirectional [...] Read more.
Electricity load forecasting has seen increasing importance recently, especially with the effectiveness of deep learning methods growing. Improving the accuracy of electricity load forecasting is vital for public resources management departments. Traditional neural network methods such as long short-term memory (LSTM) and bidirectional LSTM (BiLSTM) have been widely used in electricity load forecasting. However, LSTM and its variants are not sensitive to the dynamic change of inputs and miss the internal nonperiodic rules of series, due to their discrete observation interval. In this paper, a novel neural ordinary differential equation (NODE) method, which can be seen as a continuous version of residual network (ResNet), is applied to electricity load forecasting to learn dynamics of time series. We design three groups of models based on LSTM and BiLSTM and compare the accuracy between models using NODE and without NODE. The experimental results show that NODE can improve the prediction accuracy of LSTM and BiLSTM. It indicates that NODE is an effective approach to improving the accuracy of electricity load forecasting. Full article
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