Smart Healthcare: Leveraging IoT and Deep Learning for Real-Time Disease Detection
Abstract
The integration of IoT and deep learning has the potential to revolutionize real-time disease detection in healthcare. This paper explores a smart healthcare system that utilizes IoT sensors to continuously monitor patient vitals and deep learning algorithms to detect early signs of diseases such as sepsis and cardiac events. We present the design and implementation of the system, along with a pilot study conducted in a clinical setting. The results show that the system can provide timely alerts to healthcare providers, potentially saving lives by enabling prompt medical intervention. The paper also discusses the challenges of data accuracy, real-time processing, and system scalability.
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