AI integration

Background: The rapid evolution from 4G to 5G has transformed the telecommunications landscape, but as technological demands continue to grow, the shift toward 6G is gaining attention. 6G aims to address the limitations of 5G, such as latency and bandwidth constraints, while introducing new capabilities like terahertz communication and ubiquitous AI integration. Objective: This article explores the development roadmap of 6G, highlighting its applications across industries and addressing key challenges in its deployment. Methods: A comprehensive review of current literature on 5G advancements and emerging 6G technologies was conducted. Comparative analyses were performed on the theoretical frameworks of 6G’s core capabilities, including network architecture, spectrum management, and AI integration. Results: The study identified key applications for 6G, such as smart cities, autonomous transportation, healthcare, and industrial automation. It also highlighted the anticipated improvements in data transmission speed, reliability, and connectivity. Conclusion: 6G represents a pivotal evolution in telecommunications, offering transformation in numerous sectors. However, challenges such as infrastructure development, regulatory frameworks, and energy efficiency must be addressed.

Background: Telecommunication infrastructure requires regular maintenance and upkeep for its networks’ matrices, but existing approaches have been associated with issues such as time consumption and concern costs, as well as safety hazards. Newer developments in drone technology present progressive opportunity through the improvement of current maintenance processes by means of automation, predictability, and real time computation. Objective: The article seeks to assess whether the use of drone in telecommunication maintenance enhances the operational productivity through increasing the efficiency, reducing cost, safety, environmental and scalability and in different terrains. Methods: The methods followed included the conduct of experimental surveys with drone operations in five different telecommunication settings. These areas of interest were inspection efficiency, the accuracy of condition-based maintenance, signal received signal power, delay reduction through edge computing, and energy consumption. Sophisticated numerical computations, like Kalman filters and various frameworks of edge computing, were used in this context to draw analytical insights on the collected data. Results: The methods that used drones lowered the time needed for inspections by ¾ and cut the expenses by 49.3% and increased safety and quality of the coverage. Predictive maintenance was found to have achieved 89.7% accuracy with the system response time being 246ms at different site. The results of energy consumption model depicted the errors under 2% confirming this approach’s suitability for operational planning. Conclusion: By evaluating the applicability of drones in telecoms maintenance, the paper shows that the notion of drones in this context is promising both now and in the future. These results signal existing and potential applications of drones is to incorporate drone technology into infrastructural management solutions to address emerging needs in the industry.

Listening comprehension remains a persistent challenge for non-English major students, often due to passive learning approaches, limited interactive engagement, and ineffective assessment methods. Traditional formative assessment lacks real-time feedback and adaptive mechanisms, hindering students’ ability to monitor progress and develop effective listening strategies. To address these drawbacks, the current study examines the implementation of an AI-integrated gamified formative assessment in enhancing listening comprehension among the 38 first-semester students at Universitas PGRI Delta Sidoarjo, a private university in East Java, Indonesia. Employing a sequential mixed-methods approach, data were collected from a closed-ended questionnaire measuring dimensions of engagement, motivation, and self-regulation, alongside structured interviews with six selected students to gain deeper insights. The findings reveal that the AI-integrated gamified platform fosters a more interactive and engaging learning experience, with students demonstrating increased autonomy and strategic listening behaviors. The instant feedback and adaptive challenges contributed to improved comprehension, particularly in recognizing key information and inferring meaning from context. However, some participants expressed difficulties in adapting to the dynamic nature of the platform, citing cognitive overload and challenges in managing time constraints within the game-based environment. Additionally, variations in AI-generated feedback quality occasionally led to confusion in interpreting certain listening tasks. These findings suggest that while AI-integrated gamification enhances listening comprehension, further refinements in feedback accuracy and cognitive load management are essential to optimize its pedagogical impact. The study provides critical insights for educators and developers in designing AI-driven gamified assessment tools that effectively support listening comprehension development for non-English majors.