International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 1 (January-February 2025) Submit your research before last 3 days of February to publish your research paper in the issue of January-February.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 7 Issue 1
January-February 2025

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

DevOps-Driven Real-Time Health Analytics: A Scalable Framework for Wearable IoT Data

Author(s) Jesu Marcus Immanuvel Arockiasamy
Country United States
Abstract The rapid adoption of wearable health devices and IoT sensors has given us real-time health monitoring like never before, with opportunities for early disease detection, personalized treatment, and proactive healthcare interventions. However, scalability, latency, security, and regulatory compliance pose significant challenges. This white paper explores how DevOps methodologies – including continuous integration and continuous deployment (CI/CD) pipelines, machine learning operations (MLOps), cloud-native architectures, and security automation (DevSecOps) – enable real-time health data streaming and analytics. A cardiac monitoring case study included in this paper illustrates measurable benefits, including sub-second anomaly detection, 95% accuracy, and a fivefold improvement in data processing throughput. Furthermore, the scalable framework is adaptable to other medical conditions, such as EEG-based early stroke detection. By adopting DevOps best practices, healthcare providers can accelerate AI-driven insights, streamline compliance, and improve patient outcomes at scale.
Keywords DevOps, DevSecOps, Healthcare Analytics, IoT, Wearables
Field Computer > Data / Information
Published In Volume 7, Issue 1, January-February 2025
Published On 2025-02-21
Cite This DevOps-Driven Real-Time Health Analytics: A Scalable Framework for Wearable IoT Data - Jesu Marcus Immanuvel Arockiasamy - IJFMR Volume 7, Issue 1, January-February 2025. DOI 10.36948/ijfmr.2025.v07i01.37358
DOI https://doi.org/10.36948/ijfmr.2025.v07i01.37358
Short DOI https://doi.org/g85szr
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 7 Isu 1Cover Page Vol 6 Isu 6Cover Page Vol 6 Isu 5

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9687-828-838 editor@ijfmr.com