Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
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All Journal Gameology and Multimedia Expert
Jamy Kohistani, Ahmad
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Computer Science & IT

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AI Driven Avatars in Virtual Reality: A Systematic Literature Review on Intelligent Agents for Enhancing Human-Computer Interaction Jamy Kohistani, Ahmad; Momand, Shahenshah; Fawad Zhwak, Ahmad
Gameology and Multimedia Expert Vol. 2 No. 4 (2025): Gameology and Multimedia Expert - October 2025
Publisher : Department of Informatics Faculty of Engineering Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/game.v2i4.24167

Abstract

Artificial intelligence (AI)-driven avatars within virtual reality (VR) environments have become pivotal in advancing human-computer interaction (HCI) by offering immersive, interactive, and personalized experiences. This systematic literature review examines 20 peer-reviewed studies published between 2020 and 2025, sourced from leading academic databases including IEEE Xplore, ACM Digital Library, Scopus, SpringerLink, and ScienceDirect. The review focuses on the state-of-the-art AI techniques and technologies employed in developing intelligent avatars, their impact on user interaction, and the challenges faced in real-world applications. Employing thematic analysis, the study identifies key trends such as the use of deep learning, natural language processing, and embodied conversational agents, alongside issues of privacy, ethical considerations, and computational constraints. Results reveal that while AI-driven avatars significantly enhance VR experiences across domains such as education, healthcare, and entertainment, challenges around scalability and user acceptance persist. This review concludes by outlining future research directions to improve avatar adaptability, ethical frameworks, and multimodal interaction capabilities. These insights aim to guide researchers and practitioners toward developing more effective and user-centered AI avatars in virtual environments.
Advancing Web-Based Information Systems Performance via Edge Computing: A Comprehensive Systematic Review Wajid Fazil, Abdul; Ghairat, Atiqullah; Jamy Kohistani, Ahmad
Gameology and Multimedia Expert Vol. 2 No. 4 (2025): Gameology and Multimedia Expert - October 2025
Publisher : Department of Informatics Faculty of Engineering Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/game.v2i4.24189

Abstract

Web-based information systems (WBIS) are increasingly vital across sectors like healthcare, smart cities, and industrial automation. However, traditional cloud computing struggles to meet the low-latency and high-performance demands of these applications due to network delays and bandwidth limitations. Edge computing offers a solution by processing data closer to the source, improving responsiveness and efficiency. This study aims to explore how edge computing can optimize the performance of WBIS by evaluating different edge architectures, task offloading strategies, and performance optimization frameworks. The goal is to identify effective methods for reducing latency, improving response times, and enhancing resource management in distributed edge environments. A systematic literature review was conducted, focusing on peer-reviewed articles published between 2017 and 2025. Four major academic databases were searched using targeted keywords related to edge computing and WBIS. Articles were screened and selected based on inclusion criteria emphasizing relevance, recency, and quality. Data from the final selection of studies were synthesized thematically to identify trends, techniques, and gaps. Findings indicate that hierarchical, distributed, and hybrid edge architectures significantly reduce latency and bandwidth usage. Task offloading strategies like dynamic offloading and reinforcement learning enhance scalability and computational efficiency. Performance frameworks that integrate modular edge-cloud coordination and predictive resource management improve real-time data processing and system responsiveness. Edge computing effectively addresses the limitations of traditional cloud models by enabling localized processing and intelligent resource management in WBIS. Continued research is needed to tackle challenges related to heterogeneity, security, and real-world deployment. The study provides a foundation for developing scalable, high-performance edge-enabled web applications.
Co-Authors Fawad Zhwak, Ahmad Ghairat, Atiqullah Momand, Shahenshah Wajid Fazil, Abdul