Adaptive Edge Intelligence for Real-Time Healthcare Data Processing: A Hybrid Framework for Immediate Clinical Decision-Making and System Optimization

Sunil Kumar, Kishori Lal Bansal, K. Ruth Isabels, U. D. Prasan, A. Nagamani, Aravinth A.

2025

Abstract

In medicine, where health care data are increasing exponentially and low-latency process is essential, the use of edge computing is rapidly growing. In this paper, we present an adaptive edge intelligence framework for real-time health data analytics and on the spot clinical decision support using light weight machine learning models at network edge. The proposed hybrid structure combines edge and cloud layers to enhance data streaming, minimize latency as well as guarantee high availability in emergencies. In, this work provides an in-depth analysis of existing system configurations, edge-enabling AI nodes, as well as practical healthcare applications, and proves the benefits of edge-influenced processing to guaranteeing patient safety, promoting prompt diagnosis, and achieving fault-tolerant systems in the hectic clinical environment. The framework also mitigates the necessary existing resource constraints, data privacy issues and service sustainability, thereby offering a scalable pattern model for the smart healthcare of next era.

Paper Citation

in Harvard Style

Kumar S., Bansal K., Isabels K., Prasan U., Nagamani A. and A. A. (2025). Adaptive Edge Intelligence for Real-Time Healthcare Data Processing: A Hybrid Framework for Immediate Clinical Decision-Making and System Optimization. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 1: ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 429-435. DOI: 10.5220/0013867200004919

in Bibtex Style

@conference{icrdicct`2525,
author={Sunil Kumar and Kishori Lal Bansal and K. Ruth Isabels and U. D. Prasan and A. Nagamani and Aravinth A.},
title={Adaptive Edge Intelligence for Real-Time Healthcare Data Processing: A Hybrid Framework for Immediate Clinical Decision-Making and System Optimization},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 1: ICRDICCT`25},
year={2025},
pages={429-435},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013867200004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 1: ICRDICCT`25
TI - Adaptive Edge Intelligence for Real-Time Healthcare Data Processing: A Hybrid Framework for Immediate Clinical Decision-Making and System Optimization
SN - 978-989-758-777-1
AU - Kumar S.
AU - Bansal K.
AU - Isabels K.
AU - Prasan U.
AU - Nagamani A.
AU - A. A.
PY - 2025
SP - 429
EP - 435
DO - 10.5220/0013867200004919
PB - SciTePress