Synergizing Artificial Intelligence and Traditional Ecological Knowledge for Water Resource Optimization
Year: 2025
Type: article
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
Author: VIJAY RANJIT SAWANT -
Language: English
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4408955642