Published on: May 2026
AI-DRIVEN DIGITAL HEALTHCARE AND WELLNESS SYSTEM WITH AYURVEDA
Vedansh Meena
Sheetal Mandloi
Indore Institute of Science and Technology, Indore, Madhya Pradesh, India
Article Status
Available Documents
Abstract
The proposed system combines data collected from wearable sensors, smart health devices, electronic health records, laboratory reports, and patient lifestyle information to create a comprehensive health profile for each individual. Machine Learning (ML) and Deep Learning (DL) models are used to analyze multimodal health data, identify patterns, predict health risks, and recommend customized wellness plans. The platform also incorporates an Ayurvedic knowledge base containing Dosha and Prakriti-related rules to support personalized dietary, lifestyle, and behavioral guidance.
To ensure privacy and secure data management, the architecture adopts a federated learning approach in which sensitive patient data remains on local devices while only model updates are shared. Explainable AI (XAI) techniques such as SHAP and LIME are integrated to improve transparency and help users and healthcare professionals understand the reasoning behind AI-generated recommendations. The proposed framework further supports interoperability using healthcare standards such as FHIR and complies with major healthcare regulations including HIPAA, GDPR, and India’s National Digital Health Mission (NDHM).
This study outlines the overall system architecture, AI methodologies, data requirements, implementation strategy, and evaluation framework for the proposed platform. In addition to technical performance metrics such as prediction accuracy and explainability, the system will also be evaluated using clinical outcomes, user engagement, and wellness improvement indicators. The research highlights the potential of combining traditional Ayurvedic knowledge with modern AI technologies to build a secure, scalable, and patient-centered digital healthcare ecosystem.
How to Cite this Paper
Meena, V. (2026). AI-Driven Digital Healthcare and Wellness System with Ayurveda. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(05). https://doi.org/10.55041/ijcope.v2i5.801
Meena, Vedansh. "AI-Driven Digital Healthcare and Wellness System with Ayurveda." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 05, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i5.801.
Meena, Vedansh. "AI-Driven Digital Healthcare and Wellness System with Ayurveda." International Journal of Creative and Open Research in Engineering and Management 02, no. 05 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i5.801.
References
[1] NITI Aayog, “National Digital Health Mission Strategy Overview,” Government of India, 2023.[2] World Health Organization, Ethics and Governance of Artificial Intelligence for Health, Geneva, Switzerland, 2021.
[3] World Health Organization, “Digital Health,” WHO Health Topics, 2024.
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[5] Government of India, “Ayushman Bharat Digital Mission,” Ministry of Health and Family Welfare, 2023.
[6] A. Kumar and P. Verma, “Explainable Artificial Intelligence in Healthcare Systems,” International Journal of AI Research, vol. 8, no. 2, pp. 55–68, 2023.
[7] HL7 International, “FHIR Healthcare Interoperability Standards,” 2023.
[8] R. Prasher et al., “An Ayurgenomics Approach: Prakriti-Based Drug Discovery and Development for Personalized Care,” Frontiers in Pharmacology, vol. 13, 2022.
[9] National Center for Complementary and Integrative Health, “Ayurvedic Medicine: In Depth,” NIH, 2023.
[10] P. Joshi and M. Sharma, “AI-Based Personalized Wellness Systems Using Ayurveda,” Journal of Digital Healthcare, vol. 5, no. 1, pp. 45–59, 2024.
Ethical Compliance & Review Process
- •All submissions are screened under plagiarism detection.
- •Review follows editorial policy.
- •Authors retain copyright.
- •Peer Review Type: Double-Blind Peer Review
- •Published on: May 28 2026
This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. You are free to share and adapt this work for non-commercial purposes with proper attribution.

