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Future Internet
Special Issues
Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures
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Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Smart System Infrastructure and Applications".

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 42480

Special Issue Editors

Prof. Dr. Salvatore Carta

E-Mail Website
Guest Editor
Department of Mathematics and Computer Science, University of Cagliari, 09124 Cagliari, Italy
Interests: human-computer interaction; persuasive computing; recommender systems; machine learning; deep neural networks; time series
Special Issues, Collections and Topics in MDPI journals
Dr. Roberto Saia

E-Mail Website
Guest Editor
Department of Mathematics and Computer Science, University of Cagliari, Via Ospedale 72, 09124 Cagliari, Italy
Interests: data mining; machine learning; anomaly detection; recommender systems; security
Special Issues, Collections and Topics in MDPI journals
Dr. Olaf Bergmann

E-Mail Website
Guest Editor
Department of Mathematics and Computer Science, University of Bremen, Bibliothekstr. 5, D-28359 Bremen, Germany
Interests: communication protocols; embedded systems programming; security; Internet of Things; data formats

Special Issue Information

Dear Colleagues,

An ever-growing number of multimedia and Internet technologies have generated many benefits, which have been exploited transversely in many areas of our modern societies. The huge amount of information available through the Internet, combined with the ever-growing number of devices capable of exploiting that information, has outlined a scenario that would have been unimaginable only a few decades ago. All this is thanks to new technologies and infrastructures that can offer reliable broadband connections. Moreover, the growing capability of artificial intelligence to solve new classes of problems creates new potentially disruptive classes of applications. These opportunities stimulate researchers operating in different fields to exploit them to improve the state of the art. This Special Issue will bring together scientists from different areas, to present their recent research findings and to exchange their ideas about the effective exploitation of wireless Internet and multimedia opportunities, in light of recent technological advances, especially in the field of artificial intelligence.

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

  • Wireless data exchange models
  • Wireless multimedia sensor networks
  • Ubiquitous wireless mobile networks and systems
  • Secure communication over wireless environments
  • Wireless network threats and anomaly detection techniques
  • Internet of Things security
  • Wireless Internet security
  • Multimedia information retrieval
  • Multimedia recommendations
  • Multimedia multi-user applications
  • User localization and identification
  • User clustering and profiling
  • Artificial intelligence
  • Machine learning
  • Deep neural networks
  • Big data

Prof. Dr. Salvatore Carta
Dr. Roberto Saia
Dr. Olaf Bergmann
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
  • wireless
  • multimedia
  • artificial intelligence
  • machine learning
  • ubiquitous computing
  • wireless sensor networks
  • Internet of Things
  • security
  • deep neural networks
  • big data

Published Papers (11 papers)

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Editorial

Jump to: Research, Review

3 pages, 157 KiB  
Editorial
Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures
by Roberto Saia, Salvatore Carta and Olaf Bergmann
Future Internet 2021, 13(9), 240; https://0-doi-org.brum.beds.ac.uk/10.3390/fi13090240 - 21 Sep 2021
Viewed by 1723
Abstract
The potential offered by the Internet, combined with the enormous number of connectable devices, offers benefits in many areas of our modern societies, both public and private. The possibility of making heterogeneous devices communicate with each other through the Internet has given rise [...] Read more.
The potential offered by the Internet, combined with the enormous number of connectable devices, offers benefits in many areas of our modern societies, both public and private. The possibility of making heterogeneous devices communicate with each other through the Internet has given rise to a constantly growing scenario, which was unthinkable not long ago. This unstoppable growth takes place thanks to the continuous availability of increasingly sophisticated device features, an ever-increasing bandwidth and reliability of the connections, and the ever-lower consumption of the devices, which grants them long autonomy. This scenario of exponential growth also involves other sectors such as, for example, that of Artificial Intelligence (AI), which offers us increasingly sophisticated approaches that can be synergistically combined with wireless devices and the Internet in order to create powerful applications for everyday life. Precisely for the aforementioned reasons, the community of researchers, year by year, dedicates more time and resources in this direction. It should be observed that this happens in an atypical way concerning the other research fields, and this is because the achieved progress and the developed applications have practical applications in numerous and different domains. Full article
(This article belongs to the Special Issue Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures)

Research

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22 pages, 1743 KiB  
Article
Spiking Neural Network-Based Near-Sensor Computing for Damage Detection in Structural Health Monitoring
by Francesco Barchi, Luca Zanatta, Emanuele Parisi, Alessio Burrello, Davide Brunelli, Andrea Bartolini and Andrea Acquaviva
Future Internet 2021, 13(8), 219; https://0-doi-org.brum.beds.ac.uk/10.3390/fi13080219 - 23 Aug 2021
Cited by 6 | Viewed by 3396
Abstract
In this work, we present an innovative approach for damage detection of infrastructures on-edge devices, exploiting a brain-inspired algorithm. The proposed solution exploits recurrent spiking neural networks (LSNNs), which are emerging for their theoretical energy efficiency and compactness, to recognise damage conditions by [...] Read more.
In this work, we present an innovative approach for damage detection of infrastructures on-edge devices, exploiting a brain-inspired algorithm. The proposed solution exploits recurrent spiking neural networks (LSNNs), which are emerging for their theoretical energy efficiency and compactness, to recognise damage conditions by processing data from low-cost accelerometers (MEMS) directly on the sensor node. We focus on designing an efficient coding of MEMS data to optimise SNN execution on a low-power microcontroller. We characterised and profiled LSNN performance and energy consumption on a hardware prototype sensor node equipped with an STM32 embedded microcontroller and a digital MEMS accelerometer. We used a hardware-in-the-loop environment with virtual sensors generating data on an SPI interface connected to the physical microcontroller to evaluate the system with a data stream from a real viaduct. We exploited this environment also to study the impact of different on-sensor encoding techniques, mimicking a bio-inspired sensor able to generate events instead of accelerations. Obtained results show that the proposed optimised embedded LSNN (eLSNN), when using a spike-based input encoding technique, achieves 54% lower execution time with respect to a naive LSNN algorithm implementation present in the state-of-the-art. The optimised eLSNN requires around 47 kCycles, which is comparable with the data transfer cost from the SPI interface. However, the spike-based encoding technique requires considerably larger input vectors to get the same classification accuracy, resulting in a longer pre-processing and sensor access time. Overall the event-based encoding techniques leads to a longer execution time (1.49×) but similar energy consumption. Moving this coding on the sensor can remove this limitation leading to an overall more energy-efficient monitoring system. Full article
(This article belongs to the Special Issue Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures)
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21 pages, 1372 KiB  
Article
AI-Based Analysis of Policies and Images for Privacy-Conscious Content Sharing
by Francesco Contu, Andrea Demontis, Stefano Dessì, Marco Muscas and Daniele Riboni
Future Internet 2021, 13(6), 139; https://0-doi-org.brum.beds.ac.uk/10.3390/fi13060139 - 21 May 2021
Cited by 2 | Viewed by 2413
Abstract
Thanks to the popularity of personal mobile devices, more and more of the different types of private content, such as images and videos, are shared on social networking applications. While content sharing may be an effective practice to enhance social relationships, it is [...] Read more.
Thanks to the popularity of personal mobile devices, more and more of the different types of private content, such as images and videos, are shared on social networking applications. While content sharing may be an effective practice to enhance social relationships, it is also a source of relevant privacy issues. Unfortunately, users find it difficult to understanding the terms and implications of the privacy policies of apps and services. Moreover, taking privacy decisions about content sharing on social networks is cumbersome and prone to errors that could determine privacy leaks. In this paper, we propose two techniques aimed at supporting the user in taking privacy choices about sharing personal content online. Our techniques are based on machine learning and natural language processing to analyze privacy policies, and on computer vision to assist the user in the privacy-conscious sharing of multimedia content. Experiments with real-world data show the potential of our solutions. We also present ongoing work on a system prototype and chatbot for natural language user assistance. Full article
(This article belongs to the Special Issue Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures)
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18 pages, 4605 KiB  
Article
Estimating PQoS of Video Conferencing on Wi-Fi Networks Using Machine Learning
by Maghsoud Morshedi and Josef Noll
Future Internet 2021, 13(3), 63; https://0-doi-org.brum.beds.ac.uk/10.3390/fi13030063 - 03 Mar 2021
Cited by 2 | Viewed by 2483
Abstract
Video conferencing services based on web real-time communication (WebRTC) protocol are growing in popularity among Internet users as multi-platform solutions enabling interactive communication from anywhere, especially during this pandemic era. Meanwhile, Internet service providers (ISPs) have deployed fiber links and customer premises equipment [...] Read more.
Video conferencing services based on web real-time communication (WebRTC) protocol are growing in popularity among Internet users as multi-platform solutions enabling interactive communication from anywhere, especially during this pandemic era. Meanwhile, Internet service providers (ISPs) have deployed fiber links and customer premises equipment that operate according to recent 802.11ac/ax standards and promise users the ability to establish uninterrupted video conferencing calls with ultra-high-definition video and audio quality. However, the best-effort nature of 802.11 networks and the high variability of wireless medium conditions hinder users experiencing uninterrupted high-quality video conferencing. This paper presents a novel approach to estimate the perceived quality of service (PQoS) of video conferencing using only 802.11-specific network performance parameters collected from Wi-Fi access points (APs) on customer premises. This study produced datasets comprising 802.11-specific network performance parameters collected from off-the-shelf Wi-Fi APs operating at 802.11g/n/ac/ax standards on both 2.4 and 5 GHz frequency bands to train machine learning algorithms. In this way, we achieved classification accuracies of 92–98% in estimating the level of PQoS of video conferencing services on various Wi-Fi networks. To efficiently troubleshoot wireless issues, we further analyzed the machine learning model to correlate features in the model with the root cause of quality degradation. Thus, ISPs can utilize the approach presented in this study to provide predictable and measurable wireless quality by implementing a non-intrusive quality monitoring approach in the form of edge computing that preserves customers’ privacy while reducing the operational costs of monitoring and data analytics. Full article
(This article belongs to the Special Issue Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures)
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10 pages, 1979 KiB  
Article
A Classifier to Detect Informational vs. Non-Informational Heart Attack Tweets
by Ola Karajeh, Dirar Darweesh, Omar Darwish, Noor Abu-El-Rub, Belal Alsinglawi and Nasser Alsaedi
Future Internet 2021, 13(1), 19; https://0-doi-org.brum.beds.ac.uk/10.3390/fi13010019 - 16 Jan 2021
Cited by 11 | Viewed by 2775
Abstract
Social media sites are considered one of the most important sources of data in many fields, such as health, education, and politics. While surveys provide explicit answers to specific questions, posts in social media have the same answers implicitly occurring in the text. [...] Read more.
Social media sites are considered one of the most important sources of data in many fields, such as health, education, and politics. While surveys provide explicit answers to specific questions, posts in social media have the same answers implicitly occurring in the text. This research aims to develop a method for extracting implicit answers from large tweet collections, and to demonstrate this method for an important concern: the problem of heart attacks. The approach is to collect tweets containing “heart attack” and then select from those the ones with useful information. Informational tweets are those which express real heart attack issues, e.g., “Yesterday morning, my grandfather had a heart attack while he was walking around the garden.” On the other hand, there are non-informational tweets such as “Dropped my iPhone for the first time and almost had a heart attack.” The starting point was to manually classify around 7000 tweets as either informational (11%) or non-informational (89%), thus yielding a labeled dataset to use in devising a machine learning classifier that can be applied to our large collection of over 20 million tweets. Tweets were cleaned and converted to a vector representation, suitable to be fed into different machine-learning algorithms: Deep neural networks, support vector machine (SVM), J48 decision tree and naïve Bayes. Our experimentation aimed to find the best algorithm to use to build a high-quality classifier. This involved splitting the labeled dataset, with 2/3 used to train the classifier and 1/3 used for evaluation besides cross-validation methods. The deep neural network (DNN) classifier obtained the highest accuracy (95.2%). In addition, it obtained the highest F1-scores with (73.6%) and (97.4%) for informational and non-informational classes, respectively. Full article
(This article belongs to the Special Issue Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures)
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30 pages, 621 KiB  
Article
A Local Feature Engineering Strategy to Improve Network Anomaly Detection
by Salvatore Carta, Alessandro Sebastian Podda, Diego Reforgiato Recupero and Roberto Saia
Future Internet 2020, 12(10), 177; https://0-doi-org.brum.beds.ac.uk/10.3390/fi12100177 - 21 Oct 2020
Cited by 27 | Viewed by 3479
Abstract
The dramatic increase in devices and services that has characterized modern societies in recent decades, boosted by the exponential growth of ever faster network connections and the predominant use of wireless connection technologies, has materialized a very crucial challenge in terms of security. [...] Read more.
The dramatic increase in devices and services that has characterized modern societies in recent decades, boosted by the exponential growth of ever faster network connections and the predominant use of wireless connection technologies, has materialized a very crucial challenge in terms of security. The anomaly-based intrusion detection systems, which for a long time have represented some of the most efficient solutions to detect intrusion attempts on a network, have to face this new and more complicated scenario. Well-known problems, such as the difficulty of distinguishing legitimate activities from illegitimate ones due to their similar characteristics and their high degree of heterogeneity, today have become even more complex, considering the increase in the network activity. After providing an extensive overview of the scenario under consideration, this work proposes a Local Feature Engineering (LFE) strategy aimed to face such problems through the adoption of a data preprocessing strategy that reduces the number of possible network event patterns, increasing at the same time their characterization. Unlike the canonical feature engineering approaches, which take into account the entire dataset, it operates locally in the feature space of each single event. The experiments conducted on real-world data showed that this strategy, which is based on the introduction of new features and the discretization of their values, improves the performance of the canonical state-of-the-art solutions. Full article
(This article belongs to the Special Issue Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures)
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14 pages, 1239 KiB  
Article
Autonomous Navigation of a Solar-Powered UAV for Secure Communication in Urban Environments with Eavesdropping Avoidance
by Hailong Huang and Andrey V. Savkin
Future Internet 2020, 12(10), 170; https://0-doi-org.brum.beds.ac.uk/10.3390/fi12100170 - 10 Oct 2020
Cited by 9 | Viewed by 2812
Abstract
This paper considers the navigation of a solar-powered unmanned aerial vehicle (UAV) for securing the communication with an intended ground node in the presence of eavesdroppers in urban environments. To complete this task, the UAV needs to not only fly safely in the [...] Read more.
This paper considers the navigation of a solar-powered unmanned aerial vehicle (UAV) for securing the communication with an intended ground node in the presence of eavesdroppers in urban environments. To complete this task, the UAV needs to not only fly safely in the complex urban environment, but also take into account the communication performance with the intended node and eavesdroppers. To this end, we formulate a multi-objective optimization problem to plan the UAV path. This problem jointly considers the maximization of the residual energy of the solar-powered UAV at the end of the mission, the maximization of the time period in which the UAV can securely communicate with the intended node and the minimization of the time to reach the destination. We pay attention to the impact of the buildings in the urban environments, which may block the transmitted signals and also create some shadow region where the UAV cannot harvest energy. A Rapidly-exploring Random Tree (RRT) based path planning scheme is presented. This scheme captures the nonlinear UAV motion model, and is computationally efficient considering the randomness nature. From the generated tree, a set of possible paths can be found. We evaluate the security of the wireless communication, compute the overall energy consumption as well as the harvested amount for each path and calculate the time to complete the flight. Compared to a general RRT scheme, the proposed method enables a large time window for the UAV to securely transmit data. Full article
(This article belongs to the Special Issue Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures)
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22 pages, 295 KiB  
Article
Social Media, Quo Vadis? Prospective Development and Implications
by Laura Studen and Victor Tiberius
Future Internet 2020, 12(9), 146; https://doi.org/10.3390/fi12090146 - 28 Aug 2020
Cited by 24 | Viewed by 6219
Abstract
Over the past two decades, social media have become a crucial and omnipresent cultural and economic phenomenon, which has seen platforms come and go and advance technologically. In this study, we explore the further development of social media regarding interactive technologies, platform development, [...] Read more.
Over the past two decades, social media have become a crucial and omnipresent cultural and economic phenomenon, which has seen platforms come and go and advance technologically. In this study, we explore the further development of social media regarding interactive technologies, platform development, relationships to news media, the activities of institutional and organizational users, and effects of social media on the individual and the society over the next five to ten years by conducting an international, two-stage Delphi study. Our results show that enhanced interaction on platforms, including virtual and augmented reality, somatosensory sense, and touch- and movement-based navigation are expected. AIs will interact with other social media users. Inactive user profiles will outnumber active ones. Platform providers will diversify into the WWW, e-commerce, edu-tech, fintechs, the automobile industry, and HR. They will change to a freemium business model and put more effort into combating cybercrime. Social media will become the predominant news distributor, but fake news will still be problematic. Firms will spend greater amounts of their budgets on social media advertising, and schools, politicians, and the medical sector will increase their social media engagement. Social media use will increasingly lead to individuals’ psychic issues. Society will benefit from economic growth and new jobs, increased political interest, democratic progress, and education due to social media. However, censorship and the energy consumption of platform operators might rise. Full article
(This article belongs to the Special Issue Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures)

Review

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26 pages, 3426 KiB  
Review
Survey of Localization for Internet of Things Nodes: Approaches, Challenges and Open Issues
by Sheetal Ghorpade, Marco Zennaro and Bharat Chaudhari
Future Internet 2021, 13(8), 210; https://0-doi-org.brum.beds.ac.uk/10.3390/fi13080210 - 16 Aug 2021
Cited by 40 | Viewed by 6891
Abstract
With exponential growth in the deployment of Internet of Things (IoT) devices, many new innovative and real-life applications are being developed. IoT supports such applications with the help of resource-constrained fixed as well as mobile nodes. These nodes can be placed in anything [...] Read more.
With exponential growth in the deployment of Internet of Things (IoT) devices, many new innovative and real-life applications are being developed. IoT supports such applications with the help of resource-constrained fixed as well as mobile nodes. These nodes can be placed in anything from vehicles to the human body to smart homes to smart factories. Mobility of the nodes enhances the network coverage and connectivity. One of the crucial requirements in IoT systems is the accurate and fast localization of its nodes with high energy efficiency and low cost. The localization process has several challenges. These challenges keep changing depending on the location and movement of nodes such as outdoor, indoor, with or without obstacles and so on. The performance of localization techniques greatly depends on the scenarios and conditions from which the nodes are traversing. Precise localization of nodes is very much required in many unique applications. Although several localization techniques and algorithms are available, there are still many challenges for the precise and efficient localization of the nodes. This paper classifies and discusses various state-of-the-art techniques proposed for IoT node localization in detail. It includes the different approaches such as centralized, distributed, iterative, ranged based, range free, device-based, device-free and their subtypes. Furthermore, the different performance metrics that can be used for localization, comparison of the different techniques, some prominent applications in smart cities and future directions are also covered. Full article
(This article belongs to the Special Issue Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures)
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23 pages, 1873 KiB  
Review
Site Experience Enhancement and Perspective in Cultural Heritage Fruition—A Survey on New Technologies and Methodologies Based on a “Four-Pillars” Approach
by Agnese Augello, Ignazio Infantino, Giovanni Pilato and Gianpaolo Vitale
Future Internet 2021, 13(4), 92; https://0-doi-org.brum.beds.ac.uk/10.3390/fi13040092 - 04 Apr 2021
Cited by 9 | Viewed by 3043
Abstract
This paper deals with innovative fruition modalities of cultural heritage sites. Based on two ongoing experiments, four pillars are considered, that is, User Localization, Multimodal Interaction, User Understanding and Gamification. A survey of the existing literature regarding one or more [...] Read more.
This paper deals with innovative fruition modalities of cultural heritage sites. Based on two ongoing experiments, four pillars are considered, that is, User Localization, Multimodal Interaction, User Understanding and Gamification. A survey of the existing literature regarding one or more issues related to the four pillars is proposed. It aims to put in evidence the exploitation of these contributions to cultural heritage. It is discussed how a cultural site can be enriched, extended and transformed into an intelligent multimodal environment in this perspective. This new augmented environment can focus on the visitor, analyze his activity and behavior, and make his experience more satisfying, fulfilling and unique. After an in-depth overview of the existing technologies and methodologies for the fruition of cultural interest sites, the two experiments are described in detail and the authors’ vision of the future is proposed. Full article
(This article belongs to the Special Issue Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures)
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18 pages, 3161 KiB  
Review
From Mirrors to Free-Space Optical Communication—Historical Aspects in Data Transmission
by Magdalena Garlinska, Agnieszka Pregowska, Karol Masztalerz and Magdalena Osial
Future Internet 2020, 12(11), 179; https://0-doi-org.brum.beds.ac.uk/10.3390/fi12110179 - 22 Oct 2020
Cited by 33 | Viewed by 5781
Abstract
Fast communication is of high importance. Recently, increased data demand and crowded radio frequency spectrum have become crucial issues. Free-Space Optical Communication (FSOC) has diametrically changed the way people exchange information. As an alternative to wire communication systems, it allows efficient voice, video, [...] Read more.
Fast communication is of high importance. Recently, increased data demand and crowded radio frequency spectrum have become crucial issues. Free-Space Optical Communication (FSOC) has diametrically changed the way people exchange information. As an alternative to wire communication systems, it allows efficient voice, video, and data transmission using a medium like air. Due to its large bandwidth, FSOC can be used in various applications and has therefore become an important part of our everyday life. The main advantages of FSOC are a high speed, cost savings, compact structures, low power, energy efficiency, a maximal transfer capacity, and applicability. The rapid development of the high-speed connection technology allows one to reduce the repair downtime and gives the ability to quickly establish a backup network in an emergency. Unfortunately, FSOC is susceptible to disruption due to atmospheric conditions or direct sunlight. Here, we briefly discuss Free-Space Optical Communication from mirrors and optical telegraphs to modern wireless systems and outline the future development directions of optical communication. Full article
(This article belongs to the Special Issue Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures)
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