i-manager Publications

AI Driven Biotechnology for Climate Resilient Agriculture, Healthcare and Food System

Divyansh Bajpai*, Manoj Mishra**, Beer Singh***, Khadim Moin Siddiqui****, Prianshu Singh*****, Mohd Ahmad******, Pankaj Gupta*******, Shashank Singh********, Sanjay Mishra*********

*-**, *****-*******, ********* Department of Biotechnology, SR Institute of Management and Technology, Bakshi ka Talab, Lucknow, Uttar Pradesh, India.

***-**** Department of Electronics and Communication Engineering, SR Institute of Management and Technology, Bakshi ka Talab, Lucknow, Uttar Pradesh, India.

******** Department of Computer Science and Engineering, SR Institute of Management and Technology, Bakshi ka Talab, Sitapur Road, Lucknow, Uttar Pradesh, India.

Periodicity:September - December'2025
DOI : https://doi.org/10.26634/jls.4.3.22548

Abstract

Artificial intelligence is emerging as a game-changer for farmers coping with the escalating challenges of climate change, as AI models can predict and mitigate its wide-ranging impacts on agriculture while providing advanced decision-support tools. As environmental issues intensify, artificial intelligence integration is shifting the landscape toward climate-resilient agriculture. To address the complexities of climate unpredictability, this overview discusses how artificial intelligence assists farmers in making adaptive decisions. The advantages of artificial intelligence and climate research working together to identify climate-related risks—such as extreme weather, altered precipitation patterns, and emerging pest threats—are examined, along with its impact on smallholder and rural farmers to enhance overall resilience. A thorough analysis is conducted on the potential benefits and challenges of widespread artificial intelligence adoption across diverse agricultural contexts. Artificial intelligence-powered technologies combining computer vision, deep learning, reinforcement learning, and predictive analytics enable accurate climate forecasting, early disease detection, and efficient resource utilization. Furthermore, reinforcement learning and Internet of Things (IoT) integration support smart irrigation systems and adaptive decision-making under unpredictable climate conditions. This overview provides a comprehensive analysis of artificial intelligence and machine learning applications in precision agriculture, climate-smart farming, and sustainable land management.

Keywords

Agriculture, Artificial Intelligence, Deep Learning, Healthcare, Food System, Reinforcement Learning.

How to Cite this Article?

Bajpai, D., Mishra, M., Singh, B., Siddiqui, K. M., Singh, P., Ahmad, M., Gupta, P., Singh, S., and Mishra, S. (2025). AI Driven Biotechnology for Climate Resilient Agriculture, Healthcare and Food System. i-manager’s Journal on Life Sciences, 4(3), 38-49. https://doi.org/10.26634/jls.4.3.22548

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AI Driven Biotechnology for Climate Resilient Agriculture, Healthcare and Food System

Abstract

Keywords

How to Cite this Article?

References

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