Abstract
In the evolving education landscape, institutions are transitioning to a hybrid model encompassing physical and virtual classes. In this scenario, as working hours and exhausting routines increase, individuals accumulate psychological and physical challenges over time. This change requires students and educators to adjust to changes in teaching and learning routines, leading to moments of stress and anxiety. Cultivating self-awareness about unhealthy habits emerges as a pragmatic strategy to address this issue. In this work, a comprehensive eHealth proposal is developed to provide individuals with pertinent health information, assisting educational agents (students and teachers) in identifying and managing these stressful instances during their daily activities. This proposal acquires, processes, and disseminates vital sign data using IoT devices, supported by a Fog Computing architecture for scalability and adaptability. IoT plays a pivotal role in this eHealth proposal, facilitating the seamless collection and transmission of real-time data from various devices. Connected wearables and sensors enable the continuous monitoring of vital signs, enhancing the accuracy and responsiveness of the system. Heart rate data from educational agents were collected for implementation, allowing the evaluation of system performance. Machine learning models were leveraged to discern behavioral profiles and predict possible irregularities in vital signs. The results confirm the system’s ability to perform its intended functions, giving users quick and accurate insights into their evolving behavioral patterns. Integrating these research perspectives underscores the importance of adaptive systems in navigating the challenges of modern education environments. The incorporation of IoT technology not only enhances data collection but also opens avenues for real-time interventions and personalized feedback, ultimately contributing to a more proactive approach in addressing health-related concerns within the educational context.
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