Enhanced Security in Patient Isolation Management with IoT and LSTM Model

Abstract

Strong patient isolation management systems are now required to improve hospital security and patient safety due to the rise in infections connected to healthcare. This paper presents an advanced system that uses the Long Short-Term Memory (LSTM) model and the Internet of Things (IoT) to manage patient isolation. The system incorporates IoT-enabled sensors to continuously monitor temperature, humidity, and occupancy in isolation wards. For analysis, these real-time data streams are sent to a cloud-based platform. Because of its ability to process sequential data, the LSTM model anticipates possible violations of isolation protocols and promptly generates alerts. Integrating IoT real-time monitoring capabilities with LSTM's predictive power allows this system to lower infection rates while greatly improving patient security. This system's effectiveness in upholding strict isolation standards and its potential for wider applications in healthcare settings is demonstrated by its implementation and validation.

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