Smart E-Healthcare: An IoT, Cloud, and AI-Based Real-Time Patient Monitoring System

DOI

10.2991/978-94-6463-831-8_20How to use a DOI?

Keywords

Real-time health monitoring; Machine learning; Cloud computing; Predictive analytics

Abstract

Recent advancements in the Internet of Things (IoT) and cloud computing have enabled the development of efficient, deployable solutions for remote healthcare monitoring. This paper presents a real-time e-healthcare monitoring system that integrates IoT-enabled sensors, an ESP32 microcontroller, cloud storage, and artificial intelligence (AI)/machine learning (ML) for continuous patient data acquisition and analysis. The system monitors vital signs such as heart rate, body temperature, and oxygen saturation, transmitting data securely to a Firebase cloud database. Healthcare professionals can access real-time data through a web-based interface for timely intervention. The AI/ML component utilizes models like LSTM and Random Forest to detect anomalies and predict health risks with high accuracy. The architecture combines sensor data collection, cloud-based storage, real-time data visualization, and AI-driven predictions in an end-to-end pipeline. Our system achieved a 94% accuracy in detecting heart rate anomalies, maintained an average data transmission latency of five seconds, and demonstrated 99.5% uptime in real-world testing. Unlike previous systems that treat these components in isolation, this work delivers a fully integrated, scalable platform suited for deployment in underserved or rural healthcare environments. By leveraging real-time processing and predictive analytics, the system enhances remote diagnostics, improves patient outcomes, and supports proactive healthcare delivery.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Vedant Raut
AU  - Rohini Tambe
AU  - Devanshu Ukey
AU  - Trupti Kashid
AU  - Jineet Vaishnav
PY  - 2025
DA  - 2025/08/31
TI  - Smart E-Healthcare: An IoT, Cloud, and AI-Based Real-Time Patient Monitoring System
BT  - Proceeding of the 1st International Conference on Lifespan Innovation (ICLI 2025)
PB  - Atlantis Press
SP  - 158
EP  - 166
SN  - 2468-5739
UR  - https://doi.org/10.2991/978-94-6463-831-8_20
DO  - 10.2991/978-94-6463-831-8_20
ID  - Raut2025
ER  -