Leveraging Cloud Infrastructure for Environmental Monitoring in Healthcare: An LSTM Approach with Adam Optimization

Abstract

The healthcare industry is accepted, advanced technology increasingly in practice-with focus on patient 
safety and efficiency in operational management. However, the existing environmental monitoring system in 
a healthcare facility is often characterized by manual inspections and small sensor networks, which do not 
scale well within vast volume real-time data. Traditional methods are unable to provide continuous and real
time visibility resulting in a delayed action to a hazardous condition. Most of these systems cannot integrate 
predictive analysis through machine learning techniques, limiting anticipation of risks. This also leaves them 
useless in merging IoT devices with the cloud infrastructure to accomplish real-time data processing and 
analysis. Thus, the compromise of patient safety and operational efficiency in healthcare environments 
exists. This paper introduces a cloud environmental monitoring system for healthcare that uses IoT sensors, 
Long Short-Term Memory (LSTM) networks, and Adam optimization in real-time monitoring of critical 
environmental parameters such as temperature, humidity, air quality, and CO2 levels. The system uses cloud 
infrastructure to collect, store, and process the data about such environments securely, which would later 
allow alerts being given to healthcare professionals concerning exposure to unsafe conditions. LSTM 
captures long-term characteristics in time-series data, and Adam optimization contributes to efficient model 
training leading to prediction accuracy. The methodology brings out a promising approach showing high 
performance concerning accuracy, precision, recall, and F1-score and will demonstrate that large volumes of 
sensor data can be handled. Real-time classification capabilities and high sensitivity demonstrated by an 
AUC of 0.99 in the ROC curve will view this system as an excellent tool for improving patient safety and 
facility management. Thereby ensuring environmental monitoring in healthcare settings is scalable and 
efficient, if not accurate.