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Future Internet
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Internet of Things and Internet of Everything: Current Trends, Challenges,...
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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 (30 August 2023) | Viewed by 12341

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: vehicular networks; delay/disruption-tolerant networks; Internet of Things; smart cities; smart farming
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 (5 papers)

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Research

15 pages, 5002 KiB  
Article
Future of Drug Discovery: The Synergy of Edge Computing, Internet of Medical Things, and Deep Learning
by Mohammad (Behdad) Jamshidi, Omid Moztarzadeh, Alireza Jamshidi, Ahmed Abdelgawad, Ayman S. El-Baz and Lukas Hauer
Future Internet 2023, 15(4), 142; https://doi.org/10.3390/fi15040142 - 07 Apr 2023
Cited by 10 | Viewed by 2288
Abstract
The global spread of COVID-19 highlights the urgency of quickly finding drugs and vaccines and suggests that similar challenges will arise in the future. This underscores the need for ongoing efforts to overcome the obstacles involved in the development of potential treatments. Although [...] Read more.
The global spread of COVID-19 highlights the urgency of quickly finding drugs and vaccines and suggests that similar challenges will arise in the future. This underscores the need for ongoing efforts to overcome the obstacles involved in the development of potential treatments. Although some progress has been made in the use of Artificial Intelligence (AI) in drug discovery, virologists, pharmaceutical companies, and investors seek more long-term solutions and greater investment in emerging technologies. One potential solution to aid in the drug-development process is to combine the capabilities of the Internet of Medical Things (IoMT), edge computing (EC), and deep learning (DL). Some practical frameworks and techniques utilizing EC, IoMT, and DL have been proposed for the monitoring and tracking of infected individuals or high-risk areas. However, these technologies have not been widely utilized in drug clinical trials. Given the time-consuming nature of traditional drug- and vaccine-development methods, there is a need for a new AI-based platform that can revolutionize the industry. One approach involves utilizing smartphones equipped with medical sensors to collect and transmit real-time physiological and healthcare information on clinical-trial participants to the nearest edge nodes (EN). This allows the verification of a vast amount of medical data for a large number of individuals in a short time frame, without the restrictions of latency, bandwidth, or security constraints. The collected information can be monitored by physicians and researchers to assess a vaccine’s performance. Full article
(This article belongs to the Special Issue Internet of Things and Internet of Everything: Current Trends, Challenges, and New Perspectives)
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32 pages, 4198 KiB  
Article
Towards a Reference Architecture for Cargo Ports
by Virginia M. Romero and Eduardo B. Fernandez
Future Internet 2023, 15(4), 139; https://doi.org/10.3390/fi15040139 - 04 Apr 2023
Viewed by 2294
Abstract
Cyber-Physical Systems (CPS) are physical systems whose operations are coordinated, monitored, and controlled by computing and communication functions. These systems are typically heterogeneous, including Internet of Things and information technology subsystems, and can present a myriad of implementation details, making them very complex [...] Read more.
Cyber-Physical Systems (CPS) are physical systems whose operations are coordinated, monitored, and controlled by computing and communication functions. These systems are typically heterogeneous, including Internet of Things and information technology subsystems, and can present a myriad of implementation details, making them very complex systems. An important type of CPS is a maritime container terminal (cargo port), which is a facility where cargo containers are transported between ships and land vehicles for onward transportation and vice versa. A cargo port performs four basic functions: receiving, storing, staging, and loading for both import and export containers. We present here process patterns that describe the functional aspects of cargo ports and a pattern that describes their structural properties (patterns are encapsulated solutions to recurrent problems). These patterns describe semantic aspects found in any cargo port and can be adapted to describe other CPSs. We decompose these process patterns into use cases that describe their interactions with the system. We then integrate the process patterns with structural patterns to assemble a partial reference architecture (RA) that shows the interactions of all the patterns while also indicating the typical stakeholders found in all ports. We validate the proposed reference architecture, highlighting its theoretical and practical value. Software and system designers of cargo ports need to start from a conceptual and abstract view that is subsequently refined to add more details. The use of reference architectures and patterns is an effective way to organize and describe the functional and non-functional aspects of a system, as well as to unify the design of all its aspects. This is, until now, the only published RA for cargo ports, and it can be a useful guideline for the designers of any type of cargo port. Full article
(This article belongs to the Special Issue Internet of Things and Internet of Everything: Current Trends, Challenges, and New Perspectives)
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19 pages, 8034 KiB  
Article
Development of a Vision-Based Unmanned Ground Vehicle for Mapping and Tennis Ball Collection: A Fuzzy Logic Approach
by Masoud Latifinavid and Aydin Azizi
Future Internet 2023, 15(2), 84; https://doi.org/10.3390/fi15020084 - 19 Feb 2023
Cited by 10 | Viewed by 2753
Abstract
The application of robotic systems is widespread in all fields of life and sport. Tennis ball collection robots have recently become popular because of their potential for saving time and energy and increasing the efficiency of training sessions. In this study, an unmanned [...] Read more.
The application of robotic systems is widespread in all fields of life and sport. Tennis ball collection robots have recently become popular because of their potential for saving time and energy and increasing the efficiency of training sessions. In this study, an unmanned and autonomous tennis ball collection robot was designed and produced that used LiDAR for 2D mapping of the environment and a single camera for detecting tennis balls. A novel method was used for the path planning and navigation of the robot. A fuzzy controller was designed for controlling the robot during the collection operation. The developed robot was tested, and it successfully detected 91% of the tennis balls and collected 83% of them. Full article
(This article belongs to the Special Issue Internet of Things and Internet of Everything: Current Trends, Challenges, and New Perspectives)
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17 pages, 3771 KiB  
Article
Digitalization of Distribution Transformer Failure Probability Using Weibull Approach towards Digital Transformation of Power Distribution Systems
by A. M. Sakura R. H. Attanayake and R. M. Chandima Ratnayake
Future Internet 2023, 15(2), 45; https://doi.org/10.3390/fi15020045 - 25 Jan 2023
Cited by 2 | Viewed by 1936
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
(This article belongs to the Special Issue Internet of Things and Internet of Everything: Current Trends, Challenges, and New Perspectives)
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20 pages, 9080 KiB  
Article
A Novel NODE Approach Combined with LSTM for Short-Term Electricity Load Forecasting
by Songtao Huang, Jun Shen, Qingquan Lv, Qingguo Zhou and Binbin Yong
Future Internet 2023, 15(1), 22; https://doi.org/10.3390/fi15010022 - 30 Dec 2022
Cited by 4 | Viewed by 1909
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
(This article belongs to the Special Issue Internet of Things and Internet of Everything: Current Trends, Challenges, and New Perspectives)
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