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Advancing Environmental Modeling: Integrating AI, Big Data, and Predictive Analytics for Sustainable Solutions
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Author(s): S. Revathi (SRM Institute of Science and Technology, India), P. Pushpa (Easwari Engineering College, India), S. Saranya (Easwari Engineering College, India), V. Rekha (Panimalar Engineering College, India), S. P. Santhoshkumar (Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India), Anto Gracious L. A. (R.M.K. College of Engineering and Technology, India)and V. Sathya (Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India)
Copyright: 2025
Pages: 26
Source title:
AI Methods for Environmental Protection and Resource Conservation
Source Author(s)/Editor(s): Monia Ben Ltaifa (College of Community in Abqaiq, King Faisal University, Saudi Arabia)and Abdelkader Mohamed Sghaier Derbali (Taibah University, Saudi Arabia)
DOI: 10.4018/979-8-3373-3246-8.ch002
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Abstract
Environmental modeling has a major importance in analyzing the changes in the environment, climate, and resource allocation. The current environmental models with the use of new technologies such as AI, machine learning, big data, and IoT improves the precision of climate change predictions, emissions, protection of species, and prevention of calamites. These models use data and information generated in real-time and computer models to arrive at policy recommendations. However, there are some limitations like data uncertainty, computational complexity, and the gaps between the existing and implemented policies that reduce their efficiency. Future research needs to address the issues of combining different types of AI, continuous monitoring of the AI-driven processes, and sharing of AI models due to the concerns related to the accessibility and accuracy of the results. At the international level, the development of environmental modeling hence requires interventions from interdisciplinary fields as the policy frameworks.
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