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dc.contributor.authorHiruvinda, MHMH
dc.contributor.authorWedasinghe, N
dc.date.accessioned2026-03-11T06:53:21Z
dc.date.available2026-03-11T06:53:21Z
dc.date.issued2026-01
dc.identifier.urihttps://ir.kdu.ac.lk/handle/345/9065
dc.description.abstractThe rapid expansion of digital gaming has significantly increased concerns regarding childhood gaming addiction, as conventional monitoring approaches continue to rely largely on manual observation, static screen-time restrictions, and delayed parental intervention, which often fail to detect early behavioural, emotional, and psychological indicators of addictive gaming patterns. In response to these limitations, this paper presents a comprehensive review of recent advancements in artificial intelligence (AI)- based monitoring techniques aimed at promoting balanced playtime and supporting educational engagement among children. By synthesizing peer-reviewed research published over the past five years, the study examines how AI-driven behavioural analytics, emotion-aware systems, and predictive learning models contribute to the early identification of gaming addiction risks. The findings highlight that integrating real time behavioural monitoring with psychologically informed AI frameworks significantly improves early risk detection, enables personalized and timely interventions, and enhances parental awareness of children’s digital habits. Furthermore, emerging digital well-being platforms demonstrate strong potential to encourage healthier gaming behaviours through adaptive feedback, continuous monitoring, and child-centered engagement strategies. Despite these promising outcomes, challenges related to data privacy, ethical responsibility, dataset diversity, and the generalizability of AI models across different populations remain important considerations. Nevertheless, the reviewed studies collectively underscore the effectiveness of AI-enhanced monitoring systems in fostering responsible gaming practices and supporting child-centered digital well being. This review provides a strategic foundation for future research focused on developing ethical, adaptive, and scalable AI-driven solutions to mitigate childhood gaming addiction while aligning with broader digital wellness objectives.en_US
dc.language.isoenen_US
dc.subjectchildhood gaming addiction, artificial intelligence, behavioural monitoring, machine learning, digital well-beingen_US
dc.titleA Comprehensive Analysis of Artificial Intelligence-Based Monitoring Techniques to Combat Childhood Gaming Addiction Driving Balanced Playtime and Educational Engagementen_US
dc.typeArticle Abstracten_US
dc.identifier.facultyFOCen_US
dc.identifier.journalFOCSSen_US
dc.identifier.issue6en_US
dc.identifier.pgnos34en_US


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