Synergizing Artificial Intelligence and Traditional Ecological Knowledge for Water Resource Optimization

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

Authors

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2025-03-05
DOI
https://doi.org/10.36948/ijfmr.2025.v07i02.38236
Primary Topic
Water resources management and optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

Synergizing Artificial Intelligence and Traditional Ecological Knowledge for Water Resource Optimization

Vivek Sawant
International Journal For Multidisciplinary Research
Water resources management and optimization
article

Synergizing Artificial Intelligence and Traditional Ecological Knowledge for Water Resource Optimization

Vivek Sawant
article en

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

International Journal For Multidisciplinary ResearchVol. 7(2)
Openalex Percentile: Top 92%
Water resources management and optimization
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