Abstract:
Sri Lanka is an island rich in biodiversity, faces mounting environmental
challenges including climate change impacts and natural disasters. The ecological
management system of Sri Lanka has traditionally relied on conventional
methods, which fall short in addressing the complexities of contemporary
environmental issues. This study explores how Artificial Intelligence (AI) can be
leveraged to enhance ecological resilience in Sri Lanka’s adaptive environmental
management systems contextually. The research problem is to determine how AI
can address these limitations and improve the adaptivity, resilience of
environmental management systems in Sri Lanka. The objective of the research
is to access the potential of AI in enhance ecological resilience in Sri Lanka by
analyzing its application in adaptive environmental management systems, it
involves data integration, predictive modeling and real -time monitoring to
support better decision-making processes. The study consists a mix research
methodology. Qualitative case studies such as; “2017 Kegalle floods”, Ongoing
deforestation issues in the “Sinha Raja Forest Reserve” were used and as
quantitative data it includes with AI models used in environmental monitoring
and management with focusing on remote sensing data, machine learning
algorithms and their application in floods and other issues. Data sources include
government reports, academic journals too. It was founded that the integration of
AI in environmental management systems of Sri Lanka have yielded notable
improvements like; flood prediction and response (AI in after math of 2017
Kegalle floods demonstrated 30% improvement in prediction accuracy compared
to traditional methods), deforestation monitoring and real time monitoring.
Conclude the study highlights that AI holds a significant enhancing ecological
resilience in Sri Lanka and future efforts should focus on expanding AI
applications, integrating local knowledge for fully realize the benefits of AI in
sustainable environmental management practices.
