Authors : Jaisy James

Volume/Issue : Volume 11 - 2026, Issue 4 - April

Google Scholar : https://tinyurl.com/mt32kyze

Scribd : https://tinyurl.com/35xu85zy

DOI : https://doi.org/10.38124/ijisrt/26apr2005

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Child mortality remains a major public health challenge in tribal regions such as Attappadi, Kerala. Factors like malnutrition, anemia, lack of timely medical intervention, and poor healthcare accessibility contribute significantly to child deaths. Traditional healthcare systems often fail to provide real-time monitoring and early detection of high-risk conditions.This research proposes an Artificial Intelligence (AI)-based Smart Healthcare Monitoring System that integrates IoT devices, machine learning algorithms, and cloud-based analytics to monitor child health continuously. The system predicts risk levels using health parameters such as weight, hemoglobin level, and nutritional status. The proposed solution aims to reduce child mortality through early intervention, improved healthcare decision-making, and real-time alert systems.

Keywords : Artificial Intelligence, Child Mortality, Attappadi, Healthcare Monitoring, Machine Learning, Malnutrition Detection.

References :

1. 1. World Health Organization (WHO), Child Mortality Reports
   2. IEEE Journals on IoT-based Healthcare Systems
   3. Research papers on Machine Learning in Healthcare
   4. Government of Kerala Health Department Reports
   5. AI-based Disease Prediction Studies