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 6 (November-December 2025) Submit your research before last 3 days of December to publish your research paper in the issue of November-December.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 7 Issue 6
November-December 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

Advanced neonatal incubator utilizing IoT for continuous monitoring

Author(s) Prof. Udhyami M B, Ms. Sushma L, Ms. Shobhitha N, Ms. Deekshitha T P, Ms. Ariptha M
Country India
Abstract This paper presents an IoT-enabled advanced neonatal incubator system designed for continuous monitoring and autonomous regulation of critical physiological and environmental parameters essential for premature and critically ill newborns. The system integrates multiple sensors to measure temperature, humidity, oxygen concentration, heart rate, and respiratory rate in real time. Sensor data are transmitted wirelessly using IoT communication protocols to a cloud platform, enabling healthcare professionals to remotely access patient information through web- and mobile-based interfaces. Closed-loop automated control mechanisms maintain optimal therapeutic conditions within the incubator, while intelligent alert modules provide immediate notifications whenever monitored parameters deviate from predefined safety thresholds, enabling rapid clinical intervention. Additionally, integrated data-analytics functions support trend visualization and historical data archiving to enhance clinical decision-making. The proposed IoT-based solution addresses key limitations of conventional neonatal incubators by reducing manual monitoring requirements, minimizing human error, improving response time, and enhancing patient safety particularly in resource-constrained healthcare environments—while ensuring comprehensive digital health documentation.
Keywords Neonatal incubator, Internet of Things, continuous monitoring, remote monitoring, automated control, real-time data transmission, healthcare IoT
Field Engineering
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-11-30
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.62214
Short DOI https://doi.org/hbdskq
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 5Cover Page Vol 7 Isu 4Cover Page Vol 7 Isu 3

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