Using Machine Learning on Testing IoT Applications: a systematic mapping

In the educational sector, Internet of Things (IoT) is poised to redefine learning environments by facilitating interactive and personalized experiences tailored to individual learner needs. Additionally, it offers transformative solutions for managing educational infrastructures, optimizing resources, and enhancing administrative efficiency. This study provides a comprehensive examination of IoT's development, definitions, and emerging trends, with a specific focus on its applications within the educational domain. Utilizing a methodological framework based on an analysis of academic literature, the research traces the evolution of IoT-related studies and assesses its implications for teaching and learning. The findings reveal a significant surge in IoT-related publications since 2010, underscoring its applicability across diverse sectors, including education. In this context, IoT technologies are shown to enrich learning experiences by offering adaptive, student-centered approaches while improving the operational efficiency of educational institutions. Despite its transformative potential, the study also highlights persistent challenges, such as technical limitations, data privacy concerns, and ethical considerations, which require careful attention to ensure responsible and equitable implementation. As IoT adoption continues to expand, the research underscores its potential to reshape the educational landscape and contribute to a more connected and technologically advanced future.

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Using Machine Learning on Testing IoT Applications: a systematic mapping

Cited by 3 publications

References 44 publications

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Internet of Things in Education: Transforming Learning Environments, Enhancing Pedagogy, and Optimizing Resource Management

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