Imagine you ask an intelligent system to play your favorite music, audiobooks, or TV shows. It learns your preferences and suggests content you might enjoy based on your past choices. Imagine the system detects an unusual change in your vital signs through wearable sensors, it automatically alerts caregivers or emergency services and provides them with relevant health data. From assisting in healthcare to enhancing daily living, these technologies are hot topics for research. In this regard, machine learning is being explored quite profoundly to make the systems more intelligent and more intuitive. In a real-world smart assisted living facility, where numerous sensors are deployed to monitor behavior, environmental conditions, and health status, it is preferred that the collected data be stored in controlled, private storage systems rather than commercial devices or cloud services. This approach can better safeguard user privacy and enhance data security.

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Real-Time Applications

  • Md Zia Uddin

摘要

Imagine you ask an intelligent system to play your favorite music, audiobooks, or TV shows. It learns your preferences and suggests content you might enjoy based on your past choices. Imagine the system detects an unusual change in your vital signs through wearable sensors, it automatically alerts caregivers or emergency services and provides them with relevant health data. From assisting in healthcare to enhancing daily living, these technologies are hot topics for research. In this regard, machine learning is being explored quite profoundly to make the systems more intelligent and more intuitive. In a real-world smart assisted living facility, where numerous sensors are deployed to monitor behavior, environmental conditions, and health status, it is preferred that the collected data be stored in controlled, private storage systems rather than commercial devices or cloud services. This approach can better safeguard user privacy and enhance data security.