TY  - JOUR
AU  - Al-Dois, Hatem
AU  - Nashwan, Farhan
AU  - Rowan, Neil J
AU  - Shoushan, Amnnah Alhabeeb
AU  - O’Brolchain, Niall
AU  - Alsamhi, Saeed Hamood
PY  - 2024
DA  - 2024/12/24
TI  - FlowingLife: AI Enhancing Environmental and Economic Benefits for Aquatic Ecosystems Based on Optimizing Altered Flow Regimes
JO  - Advances in Environmental and Engineering Research
SP  - 028
VL  - 05
IS  - 04
AB  - This proposed FlowingLife framework addresses the challenges of optimizing altered flow regimes in Irish plans and programs to improve Irish aquatic ecosystems' economic and environmental outcomes. The framework uses Artificial Intelligence (AI) techniques to revolutionize flow regime management and decision-making processing, providing sustainable resource allocation, climate change adaptation, and aquatic habitat conservation. The potential of identifying optimization guides thoroughly evaluating Irish Plans, including development plans, river basin management, biodiversity, and climate action. Fish population restoration, protection of biodiversity, optimization of agricultural techniques, and management of water resources are some of the critical uses. AI-empowered FlowingLife framework creates real-time monitoring and assessment in Strategic Environmental Assessments (SEAs), enabling adaptive management. The FlowingLife evaluates and adaptively manages fish populations and flow regimes by combining Deep Learning (DL) for image and sensor analysis, knowledge graphs for intricating ecological linkages, and predictive modeling. The results show that the proposed paradigm using AI improves environmental management and supports evidence-based decision-making, sustainable resource management, and the preservation of Irish aquatic ecosystems.
SN  - 2766-6190
UR  - https://doi.org/10.21926/aeer.2404028
DO  - 10.21926/aeer.2404028
ID  - Al-Dois2024
ER  -