Proceedings of the Global Innovation and Technology Summit “AAROHAN 3.0”_HSS track (GITS-HSS 2025)

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Exploring How Artificial Intelligence Can Enhance Real-Time Monitoring and Prediction of Public Health Trends

Authors
S. Varalakshmi1, *, Anita Walia1, Roopa Traisa1
1Associate Professor, JAIN (Deemed to Be University), Bangalore, India
*Corresponding author. Email: varareddy27@gmail.com
Corresponding Author
S. Varalakshmi
Available Online 19 April 2026.
DOI
10.2991/978-2-38476-559-1_24How to use a DOI?
Keywords
Artificial Intelligence; Public Health; Real-time Monitoring; Disease Prediction; Public Health Surveillance; Data Integration
Abstract

This study investigates the transformative potential of Artificial Intelligence (AI) in enhancing real-time monitoring and prediction of public health trends. By organizing a survey with participants from the public health, data science and AI sectors, it collected insight from 80 professionals. The purpose was to test the perception of AI in monitoring events, predicting accurately, mixing data sources, giving warning signals quickly and enabling resource use and to present knowledge of challenges in using AI. Data were gathered using an online survey and looked at by descriptive statistics and one-sample t-tests with the midpoint of the Likert scale. Findings indicate a strong positive perception among professionals regarding AI's capabilities across all examined beneficial aspects (effectiveness, accuracy, timeliness, data integration impact, resource allocation benefits), with all associated hypotheses being supported. Meanwhile, it was clear that many people could see issues in implementations that discouraged more widespread adoption. By doing this research, we have highlighted the importance of AI in today’s public health surveillance and given suggestions for the best ways to improve and overcome any obstacles to integrating AI on a large scale in public health globally.

Copyright
© 2026 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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Volume Title
Proceedings of the Global Innovation and Technology Summit “AAROHAN 3.0”_HSS track (GITS-HSS 2025)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
19 April 2026
ISBN
978-2-38476-559-1
ISSN
2352-5398
DOI
10.2991/978-2-38476-559-1_24How to use a DOI?
Copyright
© 2026 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.

Cite this article

risenwbib
TY  - CONF
AU  - S. Varalakshmi
AU  - Anita Walia
AU  - Roopa Traisa
PY  - 2026
DA  - 2026/04/19
TI  - Exploring How Artificial Intelligence Can Enhance Real-Time Monitoring and Prediction of Public Health Trends
BT  - Proceedings of the Global Innovation and Technology Summit “AAROHAN 3.0”_HSS track (GITS-HSS 2025)
PB  - Atlantis Press
SP  - 346
EP  - 361
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-559-1_24
DO  - 10.2991/978-2-38476-559-1_24
ID  - Varalakshmi2026
ER  -