AI INTEGRATION IN GOVERNMENT NUTRITION PROGRAMS: A SUSTAINABLE DEVELOPMENT APPROACH FOR HILLY REGIONS OF UTTARAKHAND

Authors

  • Dr. Amar Nath Taram Individual Researcher

Keywords:

Artificial Intelligence, Nutrition Programs, Uttarakhand, Sustainable Development, Malnutrition

Abstract

Malnutrition remains a critical challenge in the hilly regions of Uttarakhand due to geographical isolation, seasonal inaccessibility, and fragmented service delivery within government nutrition programs such as ICDS and POSHAN Abhiyaan. Integrating Artificial Intelligence (AI) offers transformative solutions by enabling predictive analytics for supply chains, real-time malnutrition surveillance, and personalized nutrition counseling in local dialects. AI-powered tools like computer vision-based growth monitoring and chatbots can improve early detection of stunting and wasting by 20–30% and reduce stock-outs of nutritional supplements by 40%. Case studies from Kenya, Nepal, and Indian states like Madhya Pradesh demonstrate measurable improvements in maternal dietary diversity, program accountability, and cost efficiency through AI integration. Aligning with Sustainable Development Goals (SDGs 2, 3, 5, and 10), AI-driven nutrition interventions can enhance maternal and child health, empower frontline workers, and build a resilient, inclusive ecosystem for remote hill communities.

References

I. Arsić, S., Jovanović, B., & Ilić, M. (2024). Detecting malnutrition in children using artificial intelligence and computer vision. Journal of Medical Image Analysis, 72, 102123. doi:10.1016/j.media.2024.102123

II. Bhatt, A. (2024). Development of AI-driven healthcare systems in rural India. Asian Journal of Computing and Engineering Technology, 5(1), 21–30. doi:10.47604/ajcet.2808

III. Capritto, A., & Rahhal, N. (2023). AI-powered nutrition applications in maternal and child health: A global review. Journal of Digital Health Innovation, 12(2), 45–59. https://doi.org/10.1016/j.jdh.2023.04.002

IV. Capritto, A., & Rahhal, N. (2023). AI-powered nutritional strategies: analyzing the impact of deep learning applications in community health. Magna Scientia & Applied Research, 8(4), 15–28.

V. Dawson, C., Abebe T., Ferguson, L., et al. (2025). Forecasting acute childhood malnutrition in Kenya using machine learning and diverse indicators. PLOS ONE. doi:10.1371/journal.pone.028589

VI. Devi, R., Singh, P., & Kumar, A. (2021). Maternal nutrition and dietary diversity in Himalayan states of India: Challenges and solutions. Indian Journal of Community Health, 33(4), 712–719. https://doi.org/10.4103/ijch.v33i4.712

VII. International Institute for Population Sciences (IIPS). (2021). National Family Health Survey (NFHS 5), 2019–21: Uttarakhand Fact Sheet. Ministry of Health and Family Welfare, Government of India. https://main.mohfw.gov.in/nfhs-5

VIII. James, R., Negi, A., & Chauhan, S. (2024). Machine learning models for anemia detection in adolescent girls in Uttarakhand. Computational Health Informatics Journal, 5(1), 23–34.

IX. NITI Aayog. (2020). SDG India Index 2020: Progress in nutrition outcomes in Himalayan regions. Government of India.

X. Pradhan, K., & John, P. (2024). Use of artificial intelligence in healthcare delivery in India. Journal of Health Management and Policy, 9(2), 134 145. doi:10.21037/jhmhp-6765

XI. Tomar, N., & Thakkar, D. (2022). Using responsive feedback approach to develop and pilot a nutrition counseling chatbot in rural India. Global Health: Science and Practice, 11(Suppl 2), e2200148. doi:10.9745/GHSP-D-22-00148

XII. UNICEF. (2023). Artificial intelligence for nutrition: Lessons from global pilot projects. United Nations Children’s Fund.

XIII. World Health Organization (WHO). (2022). Digital health tools for nutrition surveillance in low-resource settings. WHO Regional Office for Africa.

XIV. Zhao, Y., & Chen, L. (2023). AI in malnutrition: systematic literature review. Nutrition and Health Informatics, 14, 101–119. doi:10.1007/s40530-023-0141-2

Additional Files

Published

01-06-2025

How to Cite

Dr. Amar Nath Taram. (2025). AI INTEGRATION IN GOVERNMENT NUTRITION PROGRAMS: A SUSTAINABLE DEVELOPMENT APPROACH FOR HILLY REGIONS OF UTTARAKHAND. International Educational Journal of Science and Engineering, 8(6). Retrieved from https://iejse.com/journals/index.php/iejse/article/view/214