Real-Time Object Recognition for Interactive AR Game Mechanics
William Rodriguez 2025-02-02

Real-Time Object Recognition for Interactive AR Game Mechanics

Thanks to William Rodriguez for contributing the article "Real-Time Object Recognition for Interactive AR Game Mechanics".

Real-Time Object Recognition for Interactive AR Game Mechanics

This paper investigates the ethical concerns surrounding mobile game addiction and its potential societal consequences. It examines the role of game design features, such as reward loops, monetization practices, and social competition, in fostering addictive behaviors among players. The research analyzes current regulatory frameworks across different countries and proposes policy recommendations aimed at mitigating the negative effects of mobile game addiction, with an emphasis on industry self-regulation, consumer protection, and the promotion of healthy gaming habits.

This research explores how storytelling elements in mobile games influence player engagement and emotional investment. It examines the psychological mechanisms that make narrative-driven games compelling, focusing on immersion, empathy, and character development. The study also assesses how mobile game developers can use narrative structures to enhance long-term player retention and satisfaction.

This paper applies Cognitive Load Theory (CLT) to the design and analysis of mobile games, focusing on how game mechanics, narrative structures, and visual stimuli impact players' cognitive load during gameplay. The study investigates how high levels of cognitive load can hinder learning outcomes and gameplay performance, especially in complex puzzle or strategy games. By combining cognitive psychology and game design theory, the paper develops a framework for balancing intrinsic, extraneous, and germane cognitive load in mobile game environments. The research offers guidelines for developers to optimize user experiences by enhancing mental performance and reducing cognitive fatigue.

This research investigates how machine learning (ML) algorithms are used in mobile games to predict player behavior and improve game design. The study examines how game developers utilize data from players’ actions, preferences, and progress to create more personalized and engaging experiences. Drawing on predictive analytics and reinforcement learning, the paper explores how AI can optimize game content, such as dynamically adjusting difficulty levels, rewards, and narratives based on player interactions. The research also evaluates the ethical considerations surrounding data collection, privacy concerns, and algorithmic fairness in the context of player behavior prediction, offering recommendations for responsible use of AI in mobile games.

This systematic review examines existing literature on the effects of mobile gaming on mental health, identifying both beneficial and detrimental outcomes. It provides evidence-based recommendations for stakeholders in the gaming industry and healthcare sectors.

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