Predictive Healthcare Using Ayurveda and Machine Learning for Sustainable Bharat 2047

Abstract

The rapid increase in chronic diseases, rising healthcare expenditure, unequal access to medical facilities, and growing environmental and demographic pressures have intensified the need for sustainable and preventive healthcare systems in India. Ayurveda, the traditional Indian system of medicine, offers a holistic framework centered on personalized healthcare, lifestyle regulation, preventive wellness, and mind–body balance. Simultaneously, advancements in Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), wearable technologies, cloud computing, and predictive analytics have transformed modern healthcare by enabling intelligent diagnostics, real-time monitoring, and data-driven decision-making. This review paper critically examines the integration of Ayurveda with AI and ML technologies to develop predictive healthcare systems aligned with the vision of Sustainable Bharat 2047. The study synthesizes findings from recent research published between 2019 and 2026 related to AI-driven healthcare, Prakriti assessment, predictive disease modeling, IoT-enabled monitoring systems, digital Ayurveda platforms, and sustainable healthcare ecosystems. The review identifies major technological approaches including Random Forest, Support Vector Machines (SVM), Deep Learning, Natural Language Processing (NLP), fuzzy logic, and sensor-based analytics for personalized healthcare prediction and disease prevention. Critical challenges including lack of standardized Ayurvedic datasets, ethical concerns, algorithmic bias, cultural sensitivity, interoperability, and data privacy are also examined. Finally, the paper proposes a conceptual framework integrating traditional Ayurvedic principles with intelligent digital technologies for future-ready healthcare systems.