International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Volume 7 Issue 2
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Synergizing Artificial Intelligence and Traditional Ecological Knowledge for Water Resource Optimization

Author(s) VIJAY RANJIT SAWANT
Country India
Abstract Addressing global water scarcity requires the integration of Artificial Intelligence (AI) with Traditional Ecological Knowledge (TEK), as demonstrated by the Artificial Intelligence-Traditional Ecological Knowledge Synergy System (AI-TEKSS). This innovative system utilizes AI’s machine learning capabilities to analyze water usage patterns, climatic impacts, and human influences on water cycles, while incorporating centuries-old TEK to ensure practices are ecologically sound and culturally relevant. This approach fosters an adaptive management strategy that is both efficient and sustainable, highlighting the importance of blending indigenous wisdom with modern technological advancements for future-oriented water management solutions. By bridging AI's analytical power with TEK's environmental insights, AI-TEKSS offers a transdisciplinary model aimed at overcoming the water challenges of the 21st century. This model promotes a convergence of innovation and tradition, aiming to optimize global water resources in a manner that respects both the analytical strengths of AI and the sustainable principles inherent in TEK, thereby paving the way for a balanced and inclusive approach to water resource management
Keywords AI-TEKSS, Transdisciplinary Approach, Adaptive Management, Machine Learning, Water Scarcity
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 2, March-April 2025
Published On 2025-03-05
DOI https://doi.org/10.36948/ijfmr.2025.v07i02.38236
Short DOI https://doi.org/g895gt
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