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Telecom
Special Issues
Digitalization, Information Technology and Social Development
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Digitalization, Information Technology and Social Development

A special issue of Telecom (ISSN 2673-4001).

Deadline for manuscript submissions: 31 March 2025 | Viewed by 8667

Special Issue Editor

Dr. Przemysław Falkowski-Gilski

E-Mail Website
Guest Editor
Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Narutowicza 11/12, 80-233 Gdansk, Poland
Interests: audio; broadcasting; coding; compression; digitization; mobile technologies; multimedia; positioning; signal processing; speech processing; video; wireless communication
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Currently, we live in a digital society filled with cutting-edge ICT solutions. Mobile devices, apps, e-services, etc., are available at any time and everywhere. As we speak, more and more branches of both business and governance are migrating to the digital domain. Digitization itself is present in the broadcasting industry such as radio and television, as well as various multimedia-based services. With the aid of mobile devices, applications, and related technologies, we desire to stay healthy or monitor the parameters of our relatives, including young people and the elderly, as well as ourselves. Nowadays, some technologies seem to be limited only to use by their creators.

However, there are still parts of our planet that suffer from digital division. Access to the latest modern-day solutions may be limited because of numerous factors, including access to education, labor markets, etc. With the aid of academics and professionals, the quality of life of such individuals can be improved.

In this Special Issue, we invite the scientific community to publish works focused on digitalization, information technology, and social development.

Original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Bridging the digital divide;
  • Broadcasting and communication systems;
  • E-business, e-commerce, and e-governance;
  • E-health and telemedicine;
  • Media digitization;
  • Quality of life;
  • Smart cities, schools, and education.

I look forward to receiving your contributions.

Dr. Przemysław Falkowski-Gilski
Guest Editor

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. Telecom is an international peer-reviewed open access quarterly 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 1200 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

  • broadcasting
  • communication systems
  • digital divide
  • e-business
  • e-commerce
  • e-governance
  • e-health
  • media digitization
  • quality of life
  • smart cities
  • smart education
  • smart schools
  • telemedicine

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (6 papers)

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Research

20 pages, 4387 KiB  
Article
Mechanisms for Securing Autonomous Shipping Services and Machine Learning Algorithms for Misbehaviour Detection
by Marwan Haruna, Kaleb Gebremichael Gebremeskel, Martina Troscia, Alexandr Tardo and Paolo Pagano
Telecom 2024, 5(4), 1031-1050; https://doi.org/10.3390/telecom5040053 - 15 Oct 2024
Viewed by 783
Abstract
Technological developments within the maritime sector are resulting in rapid progress that will see the commercial use of autonomous vessels, known as Maritime Autonomous Surface Ships (MASSs). Such ships are equipped with a range of advanced technologies, such as IoT devices, artificial intelligence [...] Read more.
Technological developments within the maritime sector are resulting in rapid progress that will see the commercial use of autonomous vessels, known as Maritime Autonomous Surface Ships (MASSs). Such ships are equipped with a range of advanced technologies, such as IoT devices, artificial intelligence (AI) systems, machine learning (ML)-based algorithms, and augmented reality (AR) tools. Through such technologies, the autonomous vessels can be remotely controlled from Shore Control Centres (SCCs) by using real-time data to optimise their operations, enhance safety, and reduce the possibility of human error. Apart from the regulatory aspects, which are under definition by the International Maritime Organisation (IMO), cybersecurity vulnerabilities must be considered and properly addressed to prevent such complex systems from being tampered with. This paper proposes an approach that operates on two different levels to address cybersecurity. On one side, our solution is intended to secure communication channels between the SCCs and the vessels using Secure Exchange and COMmunication (SECOM) standard; on the other side, it aims to secure the underlying digital infrastructure in charge of data collection, storage and processing by relying on a set of machine learning (ML) algorithms for anomaly and intrusion detection. The proposed approach is validated against a real implementation of the SCC deployed in the Livorno seaport premises. Finally, the experimental results and the performance evaluation are provided to assess its effectiveness accordingly. Full article
(This article belongs to the Special Issue Digitalization, Information Technology and Social Development)
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21 pages, 4750 KiB  
Article
Empowering a Broadband Communications Course with a Unified Module on 5G and Fixed 5G Networks
by Dimitris Uzunidis, Gerasimos Pagiatakis, Ioannis Moscholios and Michael Logothetis
Telecom 2024, 5(3), 907-927; https://doi.org/10.3390/telecom5030045 - 4 Sep 2024
Viewed by 696
Abstract
Telecommunications profoundly impacts all major aspects of our everyday life. As a consequence, student instruction typically includes a series of specialized courses, each addressing a distinct telecommunication area, separating wireless from fixed (optical) communications. This creates the problem of knowledge fragmentation, hindering the [...] Read more.
Telecommunications profoundly impacts all major aspects of our everyday life. As a consequence, student instruction typically includes a series of specialized courses, each addressing a distinct telecommunication area, separating wireless from fixed (optical) communications. This creates the problem of knowledge fragmentation, hindering the student’s perception of the topic since, at the service level, the applications and services offered to the users seem “virtually” independent from the underlying infrastructure. In this paper, to address this problem, we designed, analyzed, and implemented a 6 h course module on the five generations of wireless and fixed networks, which was presented as an integral part of the undergraduate course “Broadband Communications”, which was offered at the Dept. of Electrical and Electronic Engineering, School of Pedagogical and Technological Education (ASPETE), Athens, Greece. The main targets of this module are the following. Firstly, it aims to familiarize students with the fixed generations taxonomy, defined by the ETSI Industry Specification Group (ISG) F5G. This taxonomy serves as a foundation for understanding the evolution of telecommunications technologies. Secondly, the module seeks to integrate the acquired knowledge of the students in their previous telecommunication-related courses. During their curriculum, this knowledge was divided into two separate parts: wireless and fixed (optical). By coupling these two areas, students can develop a deeper understanding of the field. Lastly, the module aims to explore cutting-edge technologies and advancements in the telecommunications industry. In this way, it prepares students to enter the professional world during the fifth-generation era. Additionally, it provides them with valuable insights into the ongoing research and development in the field of 6G. Overall, this module serves as a comprehensive platform for students to enhance their understanding of telecommunications, from the foundational concepts to the latest advancements. To evaluate the impact of this module, the students were asked to fill out a questionnaire that included seven questions upon module completion. This questionnaire was completed successfully by 32 students in the previous academic year and by 16 students in this academic year. Moreover, a 20-question multiple choice quiz was offered to the students, allowing us to probe more into the typical errors and misconceptions about the topic. Full article
(This article belongs to the Special Issue Digitalization, Information Technology and Social Development)
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18 pages, 406 KiB  
Article
Toward Sustainable Development: Exploring the Value and Benefits of Digital Twins
by Paweł Weichbroth, Krystian Jandy and Jozef Zurada
Telecom 2024, 5(3), 774-791; https://doi.org/10.3390/telecom5030039 - 12 Aug 2024
Viewed by 1186
Abstract
The complexity and number of data streams generated by internal processes exceed the capabilities of most current simulation environments. Consequently, there is a need for the development of more advanced solutions that can handle any number of simultaneous simulations. One of the most [...] Read more.
The complexity and number of data streams generated by internal processes exceed the capabilities of most current simulation environments. Consequently, there is a need for the development of more advanced solutions that can handle any number of simultaneous simulations. One of the most promising ideas to address these and other challenges is the concept of a Digital Twin (DT), which refers to a digital representation or a virtual model designed to accurately reflect an intended or actual physical product, system, or process (i.e., a physical twin). As a Digital Twin spans the life-cycle of its physical twin, its development and application can bring considerable benefits to organizations seeking to improve existing processes as well as implement new ones. However, few studies have comprehensively examined the value and benefits of Digital Twins. To fill this gap, this study aims to provide a better understanding of this technology by reviewing the contemporary literature, with a particular focus on the documented case studies, as well as reported business and industrial deployments. The results obtained show that Digital Twins have proven beneficial for maintenance, cost reduction, optimization, simulation performance, monitoring, product life-cycle understanding, assessment validation, performance evaluation, product design, and safety and risk mitigation. In addition, when considering the human factor, DTs can facilitate education and training, team collaboration, and decision making. Undeniably, Digital Twins are a game changer for safer, faster, and more sustainable development. Full article
(This article belongs to the Special Issue Digitalization, Information Technology and Social Development)
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26 pages, 15291 KiB  
Article
The Scale-Up of E-Commerce in Romania Generated by the Pandemic, Automation, and Artificial Intelligence
by Andreea Nistor and Eduard Zadobrischi
Telecom 2024, 5(3), 680-705; https://doi.org/10.3390/telecom5030034 - 30 Jul 2024
Viewed by 1470
Abstract
This study examines the significant growth of e-commerce in Romania, which has surpassed the rates of expansion observed in other more developed countries of the European Union. Based on market analysis by sector-specific companies, the Romanian e-commerce market has reached over €6.5 billion. [...] Read more.
This study examines the significant growth of e-commerce in Romania, which has surpassed the rates of expansion observed in other more developed countries of the European Union. Based on market analysis by sector-specific companies, the Romanian e-commerce market has reached over €6.5 billion. This rapid growth trajectory is expected to continue, driven by various factors, including the impact of the COVID-19 pandemic and the natural evolution of the market. The main purpose of this study is to assess the expansion of the e-commerce market in Romania, identify the key factors behind this growth, and project future market values. Data for this analysis has been collected from industry reports, market analysis, and relevant statistical databases. The study uses a quantitative approach, utilizing financial data and growth rates to forecast future market trends. The dataset includes financial figures from e-commerce sales, digital services such as bill payments, and airline and hotel bookings from 2018 to 2023. Projections for 2024 and beyond were derived from this historical data. In 2019, the e-commerce market in Romania was valued at €4.68 billion, representing a significant increase compared to previous years. By 2020, amid the pandemic, the market value increased to €5.5 billion, marking a 38.4% increase from the previous year. Forecasts for 2024 estimate that the market will exceed €8 billion. In addition, when related digital services are included, the total market value could exceed €10 billion, illustrating the substantial economic impact of the online sector and the growth potential. This study highlights the dynamic nature of the e-commerce landscape in Romania and underlines the significant economic opportunities it presents. Full article
(This article belongs to the Special Issue Digitalization, Information Technology and Social Development)
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19 pages, 1474 KiB  
Article
Bi-GRU-APSO: Bi-Directional Gated Recurrent Unit with Adaptive Particle Swarm Optimization Algorithm for Sales Forecasting in Multi-Channel Retail
by Aruna Mogarala Guruvaya, Archana Kollu, Parameshachari Bidare Divakarachari, Przemysław Falkowski-Gilski and Hirald Dwaraka Praveena
Telecom 2024, 5(3), 537-555; https://doi.org/10.3390/telecom5030028 - 1 Jul 2024
Viewed by 1098
Abstract
In the present scenario, retail sales forecasting has a great significance in E-commerce companies. The precise retail sales forecasting enhances the business decision making, storage management, and product sales. Inaccurate retail sales forecasting can decrease customer satisfaction, inventory shortages, product backlog, and unsatisfied [...] Read more.
In the present scenario, retail sales forecasting has a great significance in E-commerce companies. The precise retail sales forecasting enhances the business decision making, storage management, and product sales. Inaccurate retail sales forecasting can decrease customer satisfaction, inventory shortages, product backlog, and unsatisfied customer demands. In order to obtain a better retail sales forecasting, deep learning models are preferred. In this manuscript, an effective Bi-GRU is proposed for accurate sales forecasting related to E-commerce companies. Initially, retail sales data are acquired from two benchmark online datasets: Rossmann dataset and Walmart dataset. From the acquired datasets, the unreliable samples are eliminated by interpolating missing data, outlier’s removal, normalization, and de-normalization. Then, feature engineering is carried out by implementing the Adaptive Particle Swarm Optimization (APSO) algorithm, Recursive Feature Elimination (RFE) technique, and Minimum Redundancy Maximum Relevance (MRMR) technique. Followed by that, the optimized active features from feature engineering are given to the Bi-Directional Gated Recurrent Unit (Bi-GRU) model for precise retail sales forecasting. From the result analysis, it is seen that the proposed Bi-GRU model achieves higher results in terms of an R2 value of 0.98 and 0.99, a Mean Absolute Error (MAE) of 0.05 and 0.07, and a Mean Square Error (MSE) of 0.04 and 0.03 on the Rossmann and Walmart datasets. The proposed method supports the retail sales forecasting by achieving superior results over the conventional models. Full article
(This article belongs to the Special Issue Digitalization, Information Technology and Social Development)
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20 pages, 5844 KiB  
Article
Smart Detection System of Safety Hazards in Industry 5.0
by Stavroula Bourou, Apostolos Maniatis, Dimitris Kontopoulos and Panagiotis A. Karkazis
Telecom 2024, 5(1), 1-20; https://doi.org/10.3390/telecom5010001 - 22 Dec 2023
Cited by 3 | Viewed by 2377
Abstract
Safety management is a priority to guarantee human-centered manufacturing processes in the context of Industry 5.0, which aims to realize a safe human–machine environment based on knowledge-driven approaches. The traditional approaches for safety management in the industrial environment include staff training, regular inspections, [...] Read more.
Safety management is a priority to guarantee human-centered manufacturing processes in the context of Industry 5.0, which aims to realize a safe human–machine environment based on knowledge-driven approaches. The traditional approaches for safety management in the industrial environment include staff training, regular inspections, warning signs, etc. Despite the fact that proactive measures and procedures have exceptional importance in the prevention of safety hazards, human–machine–environment coupling requires more sophisticated approaches able to provide automated, reliable, real-time, cost-effective, and adaptive hazard identification in complex manufacturing processes. In this context, the use of virtual reality (VR) can be exploited not only as a means of human training but also as part of the methodology to generate synthetic datasets for training AI models. In this paper, we propose a flexible and adjustable detection system that aims to enhance safety management in Industry 5.0 manufacturing through real-time monitoring and identification of hazards. The first stage of the system contains the synthetic data generation methodology, aiming to create a synthetic dataset via VR, while the second one concerns the training of AI object detectors for real-time inference. The methodology is evaluated by comparing the performance of models trained on both real-world data from a publicly available dataset and our generated synthetic data. Additionally, through a series of experiments, the optimal ratio of synthetic and real-world images is determined for training the object detector. It has been observed that even with a small amount of real-world data, training a robust AI model is achievable. Finally, we use the proposed methodology to generate a synthetic dataset of four classes as well as to train an AI algorithm for real-time detection. Full article
(This article belongs to the Special Issue Digitalization, Information Technology and Social Development)
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