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Emerging IoT Technologies for Smart Environments, 3rd Edition
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Emerging IoT Technologies for Smart Environments, 3rd Edition

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

Deadline for manuscript submissions: 25 July 2024 | Viewed by 6733

Special Issue Editors

Prof. Dr. Luigi Patrono

E-Mail Website1 Website2
Guest Editor
Department of Innovation Engineering, University of Salento, Via Monteroni, 73100 Lecce, Italy
Interests: Internet of Things; computer networks; cloud networks; RFID and BLE technologies; localization; smart environments; AAL systems
Special Issues, Collections and Topics in MDPI journals
Dr. Aitor Almeida

E-Mail Website
Guest Editor
DeustoTech-Deusto Foundation, University of Deusto, Av. Universidades 24, 48007 Bilbao, Spain
Interests: social network analysis; data mining; machine learning; pervasive computing; context-aware computing; semantic web
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Cosimo Distante

E-Mail Website
Guest Editor
Institute of Applied Sciences and Intelligent Systems “ScienceApp", Consiglio Nazionale delle Ricerche, c/o Dhitech Campus Universitario Ecotekne, Via Monteroni s/n, 73100 Lecce, Italy
Interests: computer vision; pattern recognition; video surveillance; object tracking; deep learning; audience measurements; visual interaction; human–robot interaction
Special Issues, Collections and Topics in MDPI journals
Dr. Luigi Atzori

E-Mail Website
Guest Editor
Associate Professor, Department of Electric and Electronic Engineering, University of Cagliari, 09123 Cagliari, Italy
Interests: multimedia communications; computer networking (wireless and wireline); QoS management; next-generation network (NGN); wireless sensor networks; Internet of Things
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The next generation of the Internet is expected to interconnect and to make heterogeneous and smart objects interoperable in order to realize the Internet of Things (IoT). It aims to diffuse smart and pervasive environments that are able to offer innovative services in heterogeneous applicative scenarios, such as environmental monitoring, building automation, healthcare, smart cities, smart grids, logistics, and tourism. The combination of emerging wireless communication technologies, cloud-based software architecture, embedded systems, and artificial intelligence systems based on machine learning or deep learning promises that digital transformation will be able to be carried out anywhere.

This Special Issue invites authors to submit original research or review articles that are focused on the Internet of Things and smart environments. Potential topics of interest for this Special Issue include but are not limited to the following:

  • IoT-aware systems based on wireless and wearable devices;
  • Embedded systems in IoT-aware system architectures;
  • Protocol performance analysis in IoT architectures;
  • Smart environments based on IoT Technologies;
  • Mobile applications and rapid prototyping in the IoT;
  • Middleware, semantic web, and ontology in the IoT;
  • Fog computing in the IoT;
  • Innovative AAL systems;
  • Microservices architectures;
  • Innovative solutions for industrial Internet of Things;
  • Big data and data analytics;
  • Intelligent transport systems;
  • Localization systems;
  • Safety and emergency systems based on IoT technologies;
  • Artificial intelligence systems based on machine learning or deep learning;
  • Case studies, field trials, and industrial applications.

Prof. Dr. Luigi Patrono
Dr. Aitor Almeida
Dr. Cosimo Distante
Dr. Luigi Atzori
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.

Published Papers (5 papers)

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23 pages, 1112 KiB  
Article
A Multi-Agent System for Service Provisioning in an Internet-of-Things Smart Space Based on User Preferences
by Katarina Mandaric, Ana Keselj Dilberovic and Gordan Jezic
Sensors 2024, 24(6), 1764; https://doi.org/10.3390/s24061764 - 08 Mar 2024
Viewed by 807
Abstract
The integration of the Internet of Things (IoT) and artificial intelligence (AI) is critical to the advancement of ambient intelligence (AmI), as it enables systems to understand contextual information and react accordingly. While many solutions focus on user-centric services that provide enhanced comfort [...] Read more.
The integration of the Internet of Things (IoT) and artificial intelligence (AI) is critical to the advancement of ambient intelligence (AmI), as it enables systems to understand contextual information and react accordingly. While many solutions focus on user-centric services that provide enhanced comfort and support, few expand on scenarios in which multiple users are present simultaneously, leaving a significant gap in service provisioning. To address this problem, this paper presents a multi-agent system in which software agents, aware of context, advocate for their users’ preferences and negotiate service settings to achieve solutions that satisfy everyone, taking into account users’ flexibility. The proposed negotiation algorithm is illustrated through a smart lighting use case, and the results are analyzed in terms of the concrete preferences defined by the user and the selected settings resulting from the negotiation in regard to user flexibility. Full article
(This article belongs to the Special Issue Emerging IoT Technologies for Smart Environments, 3rd Edition)
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24 pages, 2907 KiB  
Article
A Mathematical Programming Approach for IoT-Enabled, Energy-Efficient Heterogeneous Wireless Sensor Network Design and Implementation
by Ertugrul Taparci, Kardelen Olcay, Melike Ozlem Akmandor, Banu Kabakulak, Baykal Sarioglu and Yigit Daghan Gokdel
Sensors 2024, 24(5), 1457; https://doi.org/10.3390/s24051457 - 23 Feb 2024
Viewed by 522
Abstract
The Internet of Things (IoT) is playing a pivotal role in transforming various industries, and Wireless Sensor Networks (WSNs) are emerging as the key drivers of this innovation. This research explores the utilization of a heterogeneous network model to optimize the deployment of [...] Read more.
The Internet of Things (IoT) is playing a pivotal role in transforming various industries, and Wireless Sensor Networks (WSNs) are emerging as the key drivers of this innovation. This research explores the utilization of a heterogeneous network model to optimize the deployment of sensors in agricultural settings. The primary objective is to strategically position sensor nodes for efficient energy consumption, prolonged network lifetime, and dependable data transmission. The proposed strategy incorporates an offline model for placing sensor nodes within the target region, taking into account the coverage requirements and network connectivity. We propose a two-stage centralized control model that ensures cohesive decision making, grouping sensor nodes into protective boxes. This grouping facilitates shared resource utilization, including batteries and bandwidth, while minimizing box number for cost-effectiveness. Noteworthy contributions of this research encompass addressing connectivity and coverage challenges through an offline deployment model in the first stage, and resolving real-time adaptability concerns using an online energy optimization model in the second stage. Emphasis is placed on the energy efficiency, achieved through the sensor consolidation within boxes, minimizing data transmission hops, and considering energy expenditures in sensing, transmitting, and active/sleep modes. Our simulations on an agricultural farmland highlights its practicality, particularly focusing on the sensor placement for measuring soil temperature and humidity. Hardware tests validate the proposed model, incorporating parameters from the real-world implementation to enhance calculation accuracy. This study provides not only theoretical insights but also extends its relevance to smart farming practices, illustrating the potential of WSNs in revolutionizing sustainable agriculture. Full article
(This article belongs to the Special Issue Emerging IoT Technologies for Smart Environments, 3rd Edition)
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16 pages, 377 KiB  
Article
Security at the Edge for Resource-Limited IoT Devices
by Daniele Canavese, Luca Mannella, Leonardo Regano and Cataldo Basile
Sensors 2024, 24(2), 590; https://doi.org/10.3390/s24020590 - 17 Jan 2024
Viewed by 1078
Abstract
The Internet of Things (IoT) is rapidly growing, with an estimated 14.4 billion active endpoints in 2022 and a forecast of approximately 30 billion connected devices by 2027. This proliferation of IoT devices has come with significant security challenges, including intrinsic security vulnerabilities, [...] Read more.
The Internet of Things (IoT) is rapidly growing, with an estimated 14.4 billion active endpoints in 2022 and a forecast of approximately 30 billion connected devices by 2027. This proliferation of IoT devices has come with significant security challenges, including intrinsic security vulnerabilities, limited computing power, and the absence of timely security updates. Attacks leveraging such shortcomings could lead to severe consequences, including data breaches and potential disruptions to critical infrastructures. In response to these challenges, this research paper presents the IoT Proxy, a modular component designed to create a more resilient and secure IoT environment, especially in resource-limited scenarios. The core idea behind the IoT Proxy is to externalize security-related aspects of IoT devices by channeling their traffic through a secure network gateway equipped with different Virtual Network Security Functions (VNSFs). Our solution includes a Virtual Private Network (VPN) terminator and an Intrusion Prevention System (IPS) that uses a machine learning-based technique called oblivious authentication to identify connected devices. The IoT Proxy’s modular, scalable, and externalized security approach creates a more resilient and secure IoT environment, especially for resource-limited IoT devices. The promising experimental results from laboratory testing demonstrate the suitability of IoT Proxy to secure real-world IoT ecosystems. Full article
(This article belongs to the Special Issue Emerging IoT Technologies for Smart Environments, 3rd Edition)
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21 pages, 644 KiB  
Article
Analysing Edge Computing Devices for the Deployment of Embedded AI
by Asier Garcia-Perez, Raúl Miñón, Ana I. Torre-Bastida and Ekaitz Zulueta-Guerrero
Sensors 2023, 23(23), 9495; https://doi.org/10.3390/s23239495 - 29 Nov 2023
Viewed by 1147
Abstract
In recent years, more and more devices are connected to the network, generating an overwhelming amount of data. This term that is booming today is known as the Internet of Things. In order to deal with these data close to the source, the [...] Read more.
In recent years, more and more devices are connected to the network, generating an overwhelming amount of data. This term that is booming today is known as the Internet of Things. In order to deal with these data close to the source, the term Edge Computing arises. The main objective is to address the limitations of cloud processing and satisfy the growing demand for applications and services that require low latency, greater efficiency and real-time response capabilities. Furthermore, it is essential to underscore the intrinsic connection between artificial intelligence and edge computing within the context of our study. This integral relationship not only addresses the challenges posed by data proliferation but also propels a transformative wave of innovation, shaping a new era of data processing capabilities at the network’s edge. Edge devices can perform real-time data analysis and make autonomous decisions without relying on constant connectivity to the cloud. This article aims at analysing and comparing Edge Computing devices when artificial intelligence algorithms are deployed on them. To this end, a detailed experiment involving various edge devices, models and metrics is conducted. In addition, we will observe how artificial intelligence accelerators such as Tensor Processing Unit behave. This analysis seeks to respond to the choice of a device that best suits the necessary AI requirements. As a summary, in general terms, the Jetson Nano provides the best performance when only CPU is used. Nevertheless the utilisation of a TPU drastically enhances the results. Full article
(This article belongs to the Special Issue Emerging IoT Technologies for Smart Environments, 3rd Edition)
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26 pages, 1288 KiB  
Systematic Review
Wearable Technologies and AI at the Far Edge for Chronic Heart Failure Prevention and Management: A Systematic Review and Prospects
by Angela-Tafadzwa Shumba, Teodoro Montanaro, Ilaria Sergi, Alessia Bramanti, Michele Ciccarelli, Antonella Rispoli, Albino Carrizzo, Massimo De Vittorio and Luigi Patrono
Sensors 2023, 23(15), 6896; https://doi.org/10.3390/s23156896 - 03 Aug 2023
Cited by 3 | Viewed by 2382
Abstract
Smart wearable devices enable personalized at-home healthcare by unobtrusively collecting patient health data and facilitating the development of intelligent platforms to support patient care and management. The accurate analysis of data obtained from wearable devices is crucial for interpreting and contextualizing health data [...] Read more.
Smart wearable devices enable personalized at-home healthcare by unobtrusively collecting patient health data and facilitating the development of intelligent platforms to support patient care and management. The accurate analysis of data obtained from wearable devices is crucial for interpreting and contextualizing health data and facilitating the reliable diagnosis and management of critical and chronic diseases. The combination of edge computing and artificial intelligence has provided real-time, time-critical, and privacy-preserving data analysis solutions. However, based on the envisioned service, evaluating the additive value of edge intelligence to the overall architecture is essential before implementation. This article aims to comprehensively analyze the current state of the art on smart health infrastructures implementing wearable and AI technologies at the far edge to support patients with chronic heart failure (CHF). In particular, we highlight the contribution of edge intelligence in supporting the integration of wearable devices into IoT-aware technology infrastructures that provide services for patient diagnosis and management. We also offer an in-depth analysis of open challenges and provide potential solutions to facilitate the integration of wearable devices with edge AI solutions to provide innovative technological infrastructures and interactive services for patients and doctors. Full article
(This article belongs to the Special Issue Emerging IoT Technologies for Smart Environments, 3rd Edition)
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