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Journal articles on the topic 'Telecommunications AI'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Seshadri, V. "AI in Telecommunications." IEEE Expert 11, no. 1 (1996): 36. http://dx.doi.org/10.1109/mex.1996.482955.

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Maddipudi, Sreenu. "The Role of Artificial Intelligence in Data Migration for Telecommunications." International Scientific Journal of Engineering and Management 04, no. 02 (2025): 1–7. https://doi.org/10.55041/isjem02254.

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The telecommunications industry has witnessed rapid digital transformation in recent years, with data migration playing a critical role in adapting to new technologies and improving service delivery. As organizations move from legacy systems to modern cloud-based architectures, the complexity and scale of data migration processes increase. Traditional migration methods often face challenges such as downtime, data integrity issues, and the need for manual intervention. Artificial Intelligence (AI) has emerged as a transformative solution, offering automated, intelligent, and scalable approaches

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Nagappan Nagappan Palaniappan. "Intelligent Network Management: Integration of AI/ML Technologies in Modern Telecommunications Infrastructure." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 1 (2025): 2938–46. https://doi.org/10.32628/cseit251112310.

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This article examines the transformative impact of artificial intelligence and machine learning technologies on modern telecommunications infrastructure, with a particular focus on network traffic optimization. It presents a comprehensive analysis of how AI-driven solutions are revolutionizing predictive maintenance protocols, real-time traffic management, and anomaly detection in telecommunication networks. Through an exploration of reinforcement learning applications in dynamic routing and quality of service optimization, this article demonstrates significant improvements in network reliabil

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Philip Olaseni Shoetan, Olukunle Oladipupo Amoo, Enyinaya Stefano Okafor, and Oluwabukunmi Latifat Olorunfemi. "SYNTHESIZING AI'S IMPACT ON CYBERSECURITY IN TELECOMMUNICATIONS: A CONCEPTUAL FRAMEWORK." Computer Science & IT Research Journal 5, no. 3 (2024): 594–605. http://dx.doi.org/10.51594/csitrj.v5i3.908.

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As the telecommunications sector increasingly relies on interconnected digital infrastructure, the proliferation of cyber threats poses significant challenges to security and operational integrity. This review presents a conceptual framework for understanding and harnessing the potential of artificial intelligence (AI) in fortifying cybersecurity within the telecommunications industry. The framework integrates the transformative capabilities of AI with the unique demands of cybersecurity in telecommunications, aiming to enhance threat detection, mitigation, and response strategies. It encompas

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Singh, Puneet. "Leveraging AI for Advanced Troubleshooting in Telecommunications: Enhancing Network Reliability, Customer Satisfaction, and Social Equity." Journal of Science & Technology (JST) 2, no. 2 (2021): 99–138. https://doi.org/10.5281/zenodo.14830020.

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The integration of Artificial Intelligence (AI) in telecommunications is poised to revolutionize the industry's approach to troubleshooting, offering a transformative solution to the persistent challenges of network reliability, customer satisfaction, and social equity. This paper delves into the application of AI-driven methodologies in proactively predicting, identifying, and resolving network issues, thereby significantly enhancing the performance and dependability of telecommunication networks. The research begins with a thorough examination of the current landscape in telecommunications,

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Hosni, Salah Al, and Harun Şeşen. "Artificial Intelligence and Strategic Performance in Telecommunications: A Pathway to Achieving Sustainable Development Goals (SDGS)." Journal of Lifestyle and SDGs Review 5, no. 4 (2025): 06121. https://doi.org/10.47172/2965-730x.sdgsreview.v5.n04.pe06121.

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Objective: The objective of this study is to investigate the role of artificial intelligence (AI) in strategic management within the telecommunications industry in Oman, with the aim of understanding how AI integration enhances competitive advantage and strategic performance. Theoretical Framework: The study is grounded in the unified theory of acceptance and use of technology (UTAUT), which explains technology adoption through factors like performance expectancy, effort expectancy, and facilitating conditions. Method: A quantitative approach was employed, utilizing structured questionnaires t

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BUSAYO, Temitayo, Olusola IGBEKOYI, Oluyinka OLUWAGBADE, Yinka ADEWARA, Muyiwa DAGUNDURO, and Yinka BOLUWAJI. "Artificial Intelligence and Service Quality of Telecommunication Firms in Nigeria." Journal of Economics, Finance and Accounting Studies 5, no. 3 (2023): 203–14. http://dx.doi.org/10.32996/jefas.2023.5.3.16.

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Globally, artificial intelligence (AI) technology spans various industries, but relatively little attention is given to the use of AI technologies by telecommunication industries. This study evaluated the effect of AI on the service quality of telecommunications companies in Nigeria, specifically the effect of data mining, machine learning, and chatbots on the service quality of these firms. The research employed a survey research design, and its population was heterogeneous. A sample size of 400 participants was chosen using Taro Yamane's formula, and the Cronbach alpha test yielded an averag

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Samuel Olaoluwa Folorunsho, Olubunmi Adeolu Adenekan, Chinedu Ezeigweneme, Ike Chidiebere Somadina, and Patrick Azuka Okeleke. "Developing smart cities with telecommunications: Building connected and sustainable urban environments." Engineering Science & Technology Journal 5, no. 8 (2024): 2492–519. http://dx.doi.org/10.51594/estj.v5i8.1441.

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The rapid urbanization experienced globally has necessitated the development of smart cities, integrating advanced telecommunications to create connected and sustainable urban environments. This review paper explores the pivotal role of telecommunications in the evolution of smart cities, highlighting its impact on enhancing connectivity, improving public services, and fostering sustainable development. By leveraging Internet of Things (IoT) technologies, telecommunications infrastructure facilitates real-time data exchange and efficient resource management, essential for smart city operations

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Vemuri, Naveen, Naresh Thaneeru, and Venkata Manoj Tatikonda. "AI-Driven Predictive Maintenance in the Telecommunications Industry." Journal of Science & Technology 3, no. 2 (2022): 21–45. http://dx.doi.org/10.55662/jst.2022.3201.

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The rapid evolution of the telecommunications industry has heightened the demand for uninterrupted connectivity and network reliability. In this context, the integration of Artificial Intelligence (AI) in the form of predictive maintenance emerges as a pivotal solution. This research explores the impact of AI-driven predictive maintenance on the telecommunications sector, aiming to enhance network reliability and performance. The telecommunications industry serves as the backbone of global communication, and the importance of maintaining a robust and reliable network infrastructure cannot be o

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Eltayib, Nuha Hassan Elmubasher. "The Application of Artificial Intelligence on Customer Relationship Management (CRM) in the Sultanate of Oman Telecommunications Sector." British Journal of Marketing Studies 12, no. 2 (2024): 60–90. http://dx.doi.org/10.37745/bjms.2013/vol12n26090.

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Organizing and sustaining customer relationships is vital to a business in achieving its aims in terms of profit and surviving in a competitive environment. Today's global market and the rapid progression of technology, particularly the internet and computer, have placed companies in a position where they must use technology to sustain their competitive advantage. Objective of the study is to scrutinize the application of artificial intelligence in customer relationship management in Oman telecommunication sector. Since the implementation of AI in telecommunication sector around the world has

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Chukwurah, Naomi, Olumese Anthony Abieba, Noah Ayanbode, Olanrewaju Oluwaseun Ajayi, and Andrew Ifesinachi Daraojimba. "Inclusive Cybersecurity Practices in AI-Enhanced Telecommunications: A Conceptual Framework." International Journal of Multidisciplinary Research and Growth Evaluation. 5, no. 1 (2024): 1357–63. https://doi.org/10.54660/.ijmrge.2024.5.1.1357-1363.

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In the rapidly evolving landscape of telecommunications, the integration of Artificial Intelligence (AI) presents both unprecedented opportunities and profound challenges. As AI becomes increasingly pervasive in telecommunications systems, ensuring inclusive cybersecurity practices is paramount to safeguarding individuals, organizations, and societies against emerging threats. This review introduces a conceptual framework for inclusive cybersecurity practices within AI-enhanced telecommunications environments. The framework outlined in this study is designed to address the complex intersection

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James Paul Onoja and Olakunle Abayomi Ajala. "Synergizing AI and telecommunications for global development: A framework for achieving scalable and sustainable development." Computer Science & IT Research Journal 5, no. 12 (2024): 2703–14. https://doi.org/10.51594/csitrj.v5i12.1776.

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The integration of artificial intelligence (AI) and telecommunications is revolutionizing approaches to global development by creating scalable and sustainable solutions to critical challenges. This paper explores the synergy between AI technologies—such as machine learning and predictive analytics—and telecommunications infrastructure, including 5G and the Internet of Things (IoT). It highlights the transformative applications of this convergence in healthcare, education, agriculture, and disaster management, showcasing how these innovations enhance access, efficiency, and outcomes. While the

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Rishika Sen, Shrihari Vasudevan, Ricardo Britto, and Mj Prasath. "Ascertaining trustworthiness of AI systems in telecommunications." ITU Journal on Future and Evolving Technologies 5, no. 4 (2024): 503–14. https://doi.org/10.52953/wibx7049.

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With the rapid uptake of Artificial Intelligence (AI) in the Telecommunications (Telco) industry and the pivotal role AI is expected to play in future generation technologies (e.g., 5G, 5G Advanced and 6G), establishing the trustworthiness of AI used in Telco becomes critical. Trustworthy Artificial Intelligence (TWAI) guidelines need to be implemented to establish trust in AI-powered products and services by being compliant to these guidelines. This paper focuses on measuring compliance to such guidelines. This paper proposes a Large Language Model (LLM)-driven approach to measure TWAI compli

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Ilchenko, Mykhailo. "NEXT-GEN TELECOM AI: MASTERING PROMPT ENGINEERING FOR INNOVATION." Information and Telecommunication Sciences, no. 1 (June 24, 2025): 22–29. https://doi.org/10.20535/2411-2976.12025.22-29.

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Background. Since 2021, prompt engineering has emerged as a cornerstone of artificial intelligence (AI), revolutionising telecommunications by 2023 through optimised large language models (LLMs). Objective. This review synthesises existing research to evaluate prompt engineering’s transformative role in telecommunications, emphasising practical applications, technical challenges, and future directions. Methods. This analysis draws on 2021–2025 literature from 31 sources, including IEEE journals, ACM Transactions on Information Systems, NeurIPS proceedings, and arXiv preprints, examining prompt

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Samuel Olaoluwa Folorunsho, Olubunmi Adeolu Adenekan, Chinedu Ezeigweneme, Ike Chidiebere Somadina, and Patrick Azuka Okeleke. "Optimizing network performance and quality of service with AI-driven solutions for future telecommunications." International Journal of Frontiers in Engineering and Technology Research 7, no. 1 (2024): 073–92. http://dx.doi.org/10.53294/ijfetr.2024.7.1.0041.

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This paper investigates the application of AI-driven solutions to enhance network performance and Quality of Service (QoS) in future telecommunications. As the demand for higher bandwidth and seamless connectivity grows, traditional network management approaches face significant challenges in meeting these requirements. The study aims to address these challenges by leveraging artificial intelligence (AI) technologies, such as machine learning, neural networks, and predictive analytics. The research methodology involves a comprehensive review of current literature, case studies, and experimenta

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Kambhampati, Ravi Theja. "AI Telco Research: Advancements in Telecommunications Scientific Discovery." International Journal for Research in Applied Science and Engineering Technology 12, no. 9 (2024): 1514–19. http://dx.doi.org/10.22214/ijraset.2024.64339.

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This article explores the transformative impact of Artificial Intelligence (AI) on telecommunications research and development. It examines how the integration of AI technologies is revolutionizing various aspects of the industry, including network optimization, spectrum management, and scientific discovery. The article highlights the synergy between human expertise and AI capabilities in enhancing research processes, improving data analysis, and driving innovation. Key areas of focus include AI-powered data analysis, network behavior simulation, signal processing enhancements, and the evolvin

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Silitonga, Joe Laksamana. "A Review of AI-Driven Predictive Maintenance in Telecommunications." International Journal of Information System and Innovative Technology 3, no. 2 (2024): 25–31. https://doi.org/10.63322/tsq25y55.

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The telecommunications industry is rapidly evolving, driven by the increasing reliance on artificial intelligence (AI) to enhance network reliability and efficiency. Predictive maintenance (PdM) powered by AI has emerged as a crucial strategy for minimizing unexpected downtimes and optimizing service quality. Traditional reactive maintenance approaches often lead to inefficiencies, operational delays, and increased costs. This paper provides a comprehensive review of AI-driven predictive maintenance in telecommunications, categorizing existing research based on AI methodologies, applications,

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18

Pothen, Vivek Aby. "Strategic Azure Cloud Migration for Telecom: Best Practices and Emerging Trends." European Journal of Computer Science and Information Technology 13, no. 19 (2025): 79–92. https://doi.org/10.37745/ejcsit.2013/vol13n197992.

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The migration of telecommunications infrastructure to cloud platforms, particularly Microsoft Azure, represents a transformative shift in how telecommunications providers manage and optimize their networks. This comprehensive article explores the imperatives driving cloud adoption in telecommunications, examining the substantial improvements in operational efficiency, cost reduction, and service reliability achieved through strategic migration initiatives. The article investigates hybrid cloud adoption strategies, the implementation of advanced Azure technologies including AI-powered analytics

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Mohamed Abdul Kadar Mohamed Jabarullah. "PredictNet: AI-enabled predictive maintenance system for telecommunications infrastructure reliability." World Journal of Advanced Research and Reviews 15, no. 3 (2022): 631–39. https://doi.org/10.30574/wjarr.2022.15.3.0954.

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This paper introduces PredictNet, a novel AI-enabled predictive maintenance system designed specifically for telecommunications infrastructure. The research addresses the critical challenge of maintaining reliability in increasingly complex telecom networks while reducing operational costs. Using machine learning algorithms and real-time sensor data, PredictNet demonstrates superior performance in predicting equipment failures before they occur. The system was implemented and tested on a mid-sized telecommunications network over a 12-month period, achieving 92.7% prediction accuracy with a mea

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Ajay Averineni. "Innovations in cloud migration strategies for large telecom systems." World Journal of Advanced Research and Reviews 26, no. 2 (2025): 1164–74. https://doi.org/10.30574/wjarr.2025.26.2.1788.

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This article explores innovative cloud migration strategies for large telecommunication systems facing the complex challenge of modernizing legacy infrastructure while maintaining critical services. The telecommunications industry confronts unique migration obstacles including stringent availability requirements, intricate system interdependencies, massive data volumes, and regulatory compliance mandates. Through detailed exploration of emerging architectural approaches—hybrid cloud designs, microservices transformation, and containerization techniques—the article highlights how leading provid

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Researcher. "AI-DRIVEN PREDICTIVE MAINTENANCE: REVOLUTIONIZING TELECOMMUNICATIONS NETWORK MANAGEMENT." International Journal of Research In Computer Applications and Information Technology (IJRCAIT) 7, no. 2 (2024): 1735–43. https://doi.org/10.5281/zenodo.14266137.

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Emphasizing the change from reactive to proactive maintenance techniques, this article investigates the transforming effect of artificial intelligence-driven predictive maintenance systems in the telecommunications sector. By means of a review of present implementations and industry practices, it is examined how artificial intelligence algorithms interpret network operational data to forecast possible failures, optimize maintenance schedules, and improve network dependability. The integration of machine learning models for pattern detection in network performance measurements, equipment sensor

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Pidpalyi, Oleksandr. "Future prospects: AI and machine learning in cloud-based SIP trunking." Вісник Черкаського державного технологічного університету 29, no. 1 (2024): 24–35. http://dx.doi.org/10.62660/bcstu/1.2024.24.

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The relevance of the study lies in the consideration of artificial intelligence and machine learning as one of the most important technologies that determine the future of the telecommunications industry. Integration of artificial intelligence and machine learning into cloud-based Session Initiative Protocol trunking solutions can potentially significantly improve the efficiency, performance, and security of these solutions. The purpose of the study was to analyse the possibilities of integrating artificial intelligence and machine learning in cloud-based Session Initiation Protocol trunking s

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Christoff, Nicole, Nikolay N. Neshov, Krasimir Tonchev, and Agata Manolova. "Application of a 3D Talking Head as Part of Telecommunication AR, VR, MR System: Systematic Review." Electronics 12, no. 23 (2023): 4788. http://dx.doi.org/10.3390/electronics12234788.

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In today’s digital era, the realms of virtual reality (VR), augmented reality (AR), and mixed reality (MR) collectively referred to as extended reality (XR) are reshaping human–computer interactions. XR technologies are poised to overcome geographical barriers, offering innovative solutions for enhancing emotional and social engagement in telecommunications and remote collaboration. This paper delves into the integration of (AI)-powered 3D talking heads within XR-based telecommunication systems. These avatars replicate human expressions, gestures, and speech, effectively minimizing physical co

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Venu Madhav Nadella. "AI/ML-Driven Service Assurance: 2024 Breakthroughs Transforming Telecom Operations." Journal of Computer Science and Technology Studies 7, no. 4 (2025): 01–07. https://doi.org/10.32996/jcsts.2025.7.4.1.

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This article explores the transformative impact of artificial intelligence and machine learning technologies on telecommunications service assurance. The industry is experiencing a paradigm shift from reactive to predictive and prescriptive approaches to network management, enabled by three key technological breakthroughs: generative AI, causal inference, and federated learning. Major telecommunications providers are implementing Large Language Models to automate incident resolution processes, reducing resolution times and improving remediation quality. Simultaneously, causal AI is advancing p

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Kirti, Vasdev. "GeoAI in Telecommunications: The Future of Location-Based AI in Network Management." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 12, no. 3 (2024): 1–8. https://doi.org/10.5281/zenodo.14535566.

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GeoAI, the integration of Geographic Information Systems (GIS) and Artificial Intelligence (AI), is transforming telecommunications by enabling location-based insights for advanced network management. This paper explores the theoretical foundations of GeoAI, its applications in telecommunications, and the challenges it faces. Case studies highlight how GeoAI optimizes network deployment, improves maintenance, and enhances user experience. Detailed diagrams and tables illustrate the concepts and practical implementations. Finally, the paper discusses future prospects, including 5G network manag

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Balba, Neil, Oliver Junio, and Roda Sanares. "Leveraging Information Technology for Sustainable Business Growth: A Strategic Approach to Digital Transformation in SMEs." Asia Pacific Journal of Management and Sustainable Development 12, no. 3 (2024): 174–79. https://doi.org/10.70979/ejvu5338.

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This study investigates the transformative role of Artificial Intelligence (AI) in improving customer experience and business performance across various industries. As AI technologies continue to advance, their application in customer service, operational optimization, and decision-making has shown significant potential in reshaping business strategies. This research explores how AI tools, such as machine learning, predictive analytics, and automated customer service systems, contribute to enhancing customer satisfaction, driving revenue growth, and reducing operational costs. Through a mixed-

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Gadkari, Bhooshan Ravikumar. "LEVERAGING AI FOR SECURING TELECOMMUNICATIONS NETWORKS: A TECHNICAL ANALYSIS." INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATIONS AND INFORMATION TECHNOLOGY 8, no. 1 (2025): 1685–99. https://doi.org/10.34218/ijrcait_08_01_123.

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Alomari, Khaled Abdel Kader, and Rhma Omar Ahmad Hindawi. "The role of artificial intelligence in managerial decision-making: Does emotional intelligence matter?" International Journal of ADVANCED AND APPLIED SCIENCES 12, no. 8 (2025): 63–69. https://doi.org/10.21833/ijaas.2025.08.006.

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This study aimed to explore the role of artificial intelligence (AI) in managerial decision-making, with emotional intelligence acting as a moderating factor, in the context of the Jordan Telecommunications Company (Orange). A quantitative research approach was employed. The sample consisted of managers, executive directors, and department heads within the company, with a total of 170 participants. Questionnaires were distributed to all participants, and 155 valid responses were received and analyzed. The findings revealed that AI dimensions significantly influenced managerial decision-making,

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Faritha Banu, J., S. Neelakandan, B. T. Geetha, V. Selvalakshmi, A. Umadevi, and Eric Ofori Martinson. "Artificial Intelligence Based Customer Churn Prediction Model for Business Markets." Computational Intelligence and Neuroscience 2022 (September 29, 2022): 1–14. http://dx.doi.org/10.1155/2022/1703696.

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The introduction of artificial intelligence (AI) and machine learning (ML) technologies in recent years has resulted in improved company performance. Customer churn forecast is a difficult problem in many corporate sectors, particularly the telecommunications industry. Because customer churns have a direct impact on a company's total revenue, telecommunications firms have begun to develop 76 models to reduce churns at an earlier stage. Previous research has revealed that AI and ML models are effective CCP solutions. According to this viewpoint, this study proposes a unique AI-based CCP model f

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Abanihi, V.K., and K.E. Ukhurebor. "Artificial Intelligence in Radio Communication: A Facile Overview from the Nigerian Perspective." Nigerian Research Journal of Engineering and Environmental Sciences 08, no. 01 (2023): pp. 127–133. https://doi.org/10.5281/zenodo.8094505.

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<em>Recent advancements in communication technologies employ and use artificial intelligence (AI) algorithms to provide quality network services and efficiency to the end user. AI has evolved and progressed in virtually every aspect of human endeavour since its inception a few decades ago. Likewise, radio communication in the telecommunications sector has gained momentum in AI applications to solve problems encountered with network operations. This paper therefore aims at providing a precise overview of AI advancement in radio communication and the challenges of AI implementation in radio comm

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Dai, Jing. "Enhancing Corporate Innovation Through Artificial Intelligence Adoption: A Study of Chinese Telecommunications Companies." International Journal of Science and Business 38, no. 1 (2024): 18–34. http://dx.doi.org/10.58970/ijsb.2402.

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This study explores the impact mechanism of artificial intelligence (AI) adoption intensity on corporate innovation performance within the context of the digital economy. Using a sample of Chinese telecommunications companies, the research investigates how AI adoption intensity influences innovation performance. Empirical analysis reveals a significant positive relationship between AI adoption intensity and innovation performance. Furthermore, AI availability, encompassing mobile, interactive, and autonomous aspects, is found to partially mediate this relationship. The study underscores the ro

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Nneka Adaobi Ochuba, Favour Oluwadamilare Usman, Enyinaya Stefano Okafor, Olatunji Akinrinola, and Olukunle Oladipupo Amoo. "PREDICTIVE ANALYTICS IN THE MAINTENANCE AND RELIABILITY OF SATELLITE TELECOMMUNICATIONS INFRASTRUCTURE: A CONCEPTUAL REVIEW OF STRATEGIES AND TECHNOLOGICAL ADVANCEMENTS." Engineering Science & Technology Journal 5, no. 3 (2024): 704–15. http://dx.doi.org/10.51594/estj.v5i3.866.

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Predictive analytics is transforming the maintenance and reliability of satellite telecommunications infrastructure, offering proactive solutions to prevent downtime and enhance operational efficiency. This conceptual review explores key strategies and technological advancements driving the adoption of predictive analytics in this field. The integration of IoT devices and sensors enables real-time monitoring, providing valuable data on equipment performance and environmental conditions. Advanced algorithms, such as AI and ML, analyze this data to predict equipment failures and optimize mainten

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Saikat Choudhury. "Zero-Touch Slicing: Revolutionizing 5G Network Management through AI and Automation." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 6 (2024): 2394–402. https://doi.org/10.32628/cseit2410612437.

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Zero-Touch Slicing represents a revolutionary approach in modern telecommunications networks, particularly in 5G and future 6G systems, leveraging artificial intelligence and machine learning for automated network management. This comprehensive article explores the fundamental architecture, implementation strategies, and real-world applications of Zero-Touch Slicing. The article examines how AI-driven automation transforms traditional network management through predictive analytics, automated decision-making, and closed-loop optimization. It evaluates the technology's impact across enterprise

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Bikkasani, Dileesh, and Malleswar Yerabolu. "AI-Driven 5G Network Optimization: A Comprehensive Review of Resource Allocation, Traffic Management, and Dynamic Network Slicing." American Journal of Artificial Intelligence 8, no. 2 (2024): 55–62. https://doi.org/10.11648/j.ajai.20240802.14.

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The rapid advancement of 5G networks, coupled with the increasing complexity of resource management, traffic handling, and dynamic service demands, underscores the necessity for more intelligent network optimization techniques. This paper comprehensively reviews AI-driven methods applied to 5G network optimization, focusing on resource allocation, traffic management, and network slicing. Traditional models face limitations in adapting to the dynamic nature of modern telecommunications, while AI techniques—particularly machine learning (ML) and deep reinforcement learning (DRL)—offer scalable a

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Koukaras, Christos, Paraskevas Koukaras, Dimosthenis Ioannidis, and Stavros G. Stavrinides. "AI-Driven Telecommunications for Smart Classrooms: Transforming Education Through Personalized Learning and Secure Networks." Telecom 6, no. 2 (2025): 21. https://doi.org/10.3390/telecom6020021.

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Advances in telecommunications and artificial intelligence (AI) are reshaping modern educational spaces. Drawing upon diverse resources, this systematic literature review examines how these new advances including 5G, Internet of Things (IoT), and AI-based analytics can transform conventional classrooms into adaptive, secure, and highly interactive environments. Real-time data collection and personalized feedback systems are found to significantly enhance engagement and accessibility for diverse learner populations. Furthermore, emerging security architectures, such as zero-trust frameworks and

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Benyahi, Ilham. "A Methodology for Emergent Telecommunication Technology Experiments Based on Virtual Environment and AI Techniques." INTERNATIONAL JOURNAL OF MANAGEMENT & INFORMATION TECHNOLOGY 3, no. 2 (2013): 01–05. http://dx.doi.org/10.24297/ijmit.v3i2.1360.

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Advanced telecommunications technologies innovations evolve quickly and are often considered as a main component of critical and emerging applications such as Intelligent Transportation Systems (ITS) and Smart Grid (energy systems). The need of rapid deployment of these technologies requires their testing to assess their performance and if necessary seek appropriate configurations that optimize the QoS (Quality Of Service) of associated applications. Existing simulation tools for testing these technologies remain limited when it comes to appraise their innovations involving additional knowledg

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Samuel Olaoluwa Folorunsho, Olubunmi Adeolu Adenekan, Chinedu Ezeigweneme, Ike Chidiebere Somadina, and Patrick Azuka Okeleke. "Ensuring Cybersecurity in telecommunications: Strategies to protect digital infrastructure and sensitive data." Computer Science & IT Research Journal 5, no. 8 (2024): 1855–83. http://dx.doi.org/10.51594/csitrj.v5i8.1448.

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This review paper aims to address the critical issue of cybersecurity in the telecommunications sector, focusing on strategies to protect digital infrastructure and sensitive data. The objectives of the study are to identify current cybersecurity threats, evaluate existing protective measures, and propose comprehensive strategies to enhance the security of telecommunications networks. The methodology involves a thorough review of industry reports, regulatory frameworks, scholarly articles, and case studies to provide an in-depth understanding of the current cybersecurity landscape. Key finding

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Rajeev Gandhi, S., and B. Vasudevan. "AI BASED GRAPH THEORY METHOD AND PROCESS." International Journal of Advanced Research 13, no. 01 (2025): 317–23. https://doi.org/10.21474/ijar01/20196.

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Graph theory is a fundamental branch of mathematics with applications across various domains including computer science, telecommunications, and social networks. In recent years, artificial intelligence (AI) has revolutionized traditional graph theory methodologies by introducing novel computational techniques and algorithms. the integration of AI in graph theory, focusing on key methodologies such as deep learning, reinforcement learning, and evolutionary algorithms. We analyse how AI enhances graph theory through automated theorem proving, optimization of graph algorithms, and predictive mod

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Mokale, Mahesh. "Scalable Data Management Strategies for Telecommunications Enterprises." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 05, no. 12 (2021): 1–8. https://doi.org/10.55041/ijsrem11159.

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In the current technological landscape marked by the widespread adoption of 5G networks, the proliferation of Internet of Things (IoT) devices, and the ever-growing need for real-time data processing, telecommunications enterprises are encountering unprecedented challenges in managing and scaling their vast volumes of data. The digital age has brought about a transformative surge in the volume, variety, and velocity of data, compelling telecom companies to reevaluate and enhance their data management strategies to remain competitive. This surge is not limited to just an increase in the number

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Muthivhi, Musiwalo Ernest. "The future of work in the age of the fourth industrial revolution: Implications for the South African telecommunications industry." International Journal of Applied Science and Research 06, no. 02 (2022): 144–51. http://dx.doi.org/10.56293/ijasr.2022.5515.

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The Fourth Industrial Revolution (4IR) has introduced significant changes to the global telecommunications industry including South Africa. As a result of innovations and changes in digital technology, the South African telecommunications industry is actively adopting the latest applications and processes of digital technology for rendering efficient voice, data and text messaging services to clients. These changes present opportunities for growth in marketshare to telecommunications operators. The paper presents a summary of the main impact of 4IR on the South African telecommunications indus

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Wiese, Thomas L. "Predictive Maintenance Using Artificial Intelligence in Critical Infrastructure: A Decision-Making Framework." International Journal of Engineering, Business and Management 8, no. 4 (2024): 01–04. http://dx.doi.org/10.22161/ijebm.8.4.1.

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Critical infrastructure supports essential services across energy, transportation, water management, and telecommunications sectors. The degradation or failure of assets in these sectors can have serious economic and safety consequences. Predictive maintenance (PdM), driven by artificial intelligence (AI), has emerged as a transformative approach to optimize maintenance activities and prevent failures. This paper reviews current AI-based PdM applications in critical infrastructure and presents a decision-making framework for evaluating when AI should be used. By addressing technical capabiliti

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Olajide Soji Osundare, Chidiebere Somadina Ike, Ololade Gilbert Fakeyede, and Adebimpe Bolatito Ige. "Resilience and recovery technologies in financial telecommunications network." Engineering Science & Technology Journal 3, no. 2 (2022): 136–53. http://dx.doi.org/10.51594/estj.v3i2.1522.

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In the increasingly interconnected world of financial telecommunications, the resilience and recovery of networks are critical to ensuring uninterrupted services and maintaining the integrity of financial transactions. This paper explores the technologies and strategies employed to enhance the resilience and recovery capabilities of financial telecommunications networks, focusing on the prevention and mitigation of disruptions caused by cyberattacks, natural disasters, and system failures. Key technologies, such as Distributed Denial of Service (DDoS) protection, redundant network architecture

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Alabi, Abidemi Adeleye, Sikirat Damilola Mustapha, and Afees Olanrewaju Akinade. "Leveraging Advanced Technologies for Efficient Project Management in Telecommunications." International Journal of Multidisciplinary Research and Growth Evaluation 6, no. 1 (2025): 318–27. https://doi.org/10.54660/.ijmrge.2025.6.1.318-327.

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In the fast-paced and highly competitive telecommunications industry, efficient project management is crucial to maintaining operational excellence and achieving strategic objectives. Advanced technologies are increasingly being leveraged to enhance project management practices, driving improvements in efficiency, accuracy, and adaptability. This paper explores how cutting-edge tools and methodologies are revolutionizing project management in telecommunications, leading to more effective planning, execution, and control of projects. One of the primary technologies transforming project manageme

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Muttaqin, Widang, Maya Silvi Lydia, and Fahmi Fahmi. "CLUSTERING ROTATIONAL CHURN OF TELECOMMUNICATIONS CUSTOMERS USING A DATA-CENTRICAI APPROACH." JURTEKSI (Jurnal Teknologi dan Sistem Informasi) 10, no. 4 (2024): 773–80. https://doi.org/10.33330/jurteksi.v10i4.3304.

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Abstract: In the current era of very fast technological development, customer churn is a serious challenge, especially in the competitive telecommunications industry. Churn refers to customers who stop using a service or move to another provider, and can be categorized into three types: Active Churn, Passive Churn, and Rotational Churn. Rotational Churn, which is difficult to predict be- cause the reasons for stopping are unclear, is the main focus of this research. This research aims to group Rotational Churn customers using a Data-Centric AI approach. This approach emphasizes improving data

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Ibrahim Adedeji Adeniran, Christianah Pelumi Efunniyi, Olajide Soji Osundare, and Angela Omozele Abhulimen. "Implementing machine learning techniques for customer retention and churn prediction in telecommunications." Computer Science & IT Research Journal 5, no. 8 (2024): 2011–25. http://dx.doi.org/10.51594/csitrj.v5i8.1489.

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This review paper explores the application of machine learning techniques in predicting customer churn and enhancing customer retention within the telecommunications industry. The paper begins by discussing the significance of customer churn, its causes, and the limitations of traditional churn prediction methods. It then delves into machine learning algorithms, including decision trees, support vector machines, and ensemble methods. It highlights their effectiveness in handling large and complex datasets typical of the telecom sector. The discussion extends to the challenges faced in data qua

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Alzyoud, Adel Ali Yassin. "NAVIGATING THE FUTURE: ARTIFICIAL INTELLIGENCE'S GROWING INFLUENCE ON DECISION MAKING." International Journal of Membrane Science and Technology 10, no. 4 (2023): 2188–94. http://dx.doi.org/10.15379/ijmst.v10i4.2382.

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Purpose: The purpose of this study article is to investigate the impact of AI (system capability, user behavior, training and development, and expert availability) on decision making in Bahrain telecommunications company. Theoretical framework: The deployment of AI systems has expanded tremendously in recent years, and decision making is no exception to its disruptive potential (Jones et al., 2022). AI algorithms and technologies are being used by organizations and individuals to assist and improve decision-making processes. To fully reap the benefits of AI, however, a thorough knowledge of th

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KHAN, PAREESHA. "Role of Ai in Personalizing Customer Experience." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem50817.

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1. Introduction In today’s technology-driven marketplace, customer experience (CX) is a primary differentiator for businesses. Artificial Intelligence (AI) has emerged as a transformative force in enhancing how companies understand, serve, and engage with customers. This project aims to analyse the role of AI in delivering personalized experiences across sectors like e-commerce, banking, hospitality, retail, and telecommunications. 2. Objectives of the Study · To examine how AI tools enhance customer experience through personalization. · To explore various AI technologies used by businesses fo

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Mokale, Mahesh. "Developing Advanced Tooling for Data Governance in Media and Telecommunications." Journal of Software Engineering and Simulation 8, no. 12 (2012): 32–38. https://doi.org/10.35629/3795-08123238.

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Data governance is a fundamental aspect of modern media and telecommunications industries, ensuring compliance with stringent regulatory frameworks, enhancing data security, and optimizing data utilization for business insights. With the unprecedented surge in data volume, diversity, and complexity, traditional governance approaches are no longer sufficient to manage the evolving landscape of digital operations. Organizations must adopt advanced tooling that integrates artificial intelligence (AI), machine learning (ML), automation, and cloud-based technologies to establish scalable, efficient

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Liu, Jinmei, Hua Yuan, Xue Lin, and Nianqiang Li. "Teaching Reform of “Telecommunication Electronic Circuits” Based on the Integration of Artificial Intelligence and Human Wisdom." International Journal of Education, Culture and Society 10, no. 2 (2025): 120–25. https://doi.org/10.11648/j.ijecs.20251002.17.

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As an important compulsory course for the students who major in telecommunications engineering, the Telecommunication Electronic Circuits (High-Frequency Electronic Circuits) course confronts two major challenges: high knowledge complexity and limited resources for practical engineering training. In order to overcome the challenges and promote teaching effects, we utilize the scheme of integrating artificial intelligence (AI) technology with human wisdom in teaching the Telecommunication Electronic Circuits course. The scheme combines the advantages of both AI technology and human wisdom. AI t

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De Percy, Michael. "The Digital Economy is the ‘New Normal’." Journal of Telecommunications and the Digital Economy 13, no. 2 (2025): iii—iv. https://doi.org/10.18080/jtde.v13n2.1303.

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This editorial introduces a new issue of the Journal of Telecommunications and the Digital Economy, exploring the growth of the digital economy post-COVID-19. The pandemic accelerated online interactions, revealing a lag in social norms despite decades-old technologies. Developed nations integrate AI into shopping, while developing countries advance rapidly, yet design principles remain rooted in tradition. The contributions in this issue underscore the human element in technology adoption and the Journal’s role in bridging telecommunications’ legacy with today’s digital challenges, enriching

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