Abstract
Abstract Students' health, fitness, and wellbeing depend on various factors, and a better understanding of these factors ensures that students have effective health and wellbeing interventions. Recently, Ambient Intelligence (AmI) and internet of things (IoT) are promising solutions to provide healthcare monitoring and personalized health care to provide efficient, significantly lower medical services. The amount of data created by sensors can pose data inaccessibility and computational challenge in the IoT environment. Hence, in this study, Ambient Intelligence assisted Health Monitoring System (AmIHMS) with IoT devices has been proposed for student health monitoring. Wireless sensor networks (WSNs) are utilized for collecting the data needed by Ami environments. The cloud will handle the increased amount of health data, exchange information in resourceful ways across health care networks, and make Big Data Analytics sustainable. Real-time alerting of student health information with large data is an important exercise that is crucial in the proposed work. The simulation results show that the proposed AmIHMS method enhances reliability, data accessibility, and accuracy compared to popular methods.
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