American Journal of Advanced Multidisciplinary Research and Innovation

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Volume 8 Issue 5
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Artificial Intelligence Applications in Environmental Sustainability and Natural Resource Conservation

Author(s) Rana Rand
Country United States
Abstract Artificial Intelligence (AI) is increasingly emerging as a transformative technology for addressing complex environmental challenges and supporting sustainable management of natural resources. Rapid climate change, biodiversity loss, deforestation, water scarcity, soil degradation, pollution, and unsustainable resource consumption have created an urgent need for more efficient and data-driven approaches to environmental management. AI technologies, including machine learning, deep learning, computer vision, remote sensing analytics, predictive modelling, and intelligent decision-support systems, provide new opportunities for monitoring ecosystems, forecasting environmental changes, optimizing resource use, and improving conservation interventions.
This study examines the applications of AI in environmental sustainability and natural resource conservation through a qualitative and comparative analysis of contemporary academic literature, international environmental reports, and technological developments. Particular attention is given to AI applications in biodiversity monitoring, forest conservation, water-resource management, climate-change modelling, agriculture, wildlife protection, pollution detection, and disaster prediction. The study finds that AI can improve the speed, accuracy, and scalability of environmental monitoring while enabling predictive rather than purely reactive conservation strategies. However, AI adoption also presents challenges related to data availability, computational costs, algorithmic bias, privacy, technological inequality, energy consumption, and the lack of technical capacity in many developing regions. The study concludes that AI can become an important component of sustainable environmental governance when combined with ecological knowledge, community participation, responsible data management, and appropriate institutional frameworks.
Keywords Artificial Intelligence, Environmental Sustainability, Natural Resource Conservation, Biodiversity, Climate Change, Machine Learning, Remote Sensing, Ecosystem Management, Environmental Monitoring, Sustainable Development.
Field Engineering
Published In Volume 4, Issue 5, September-October 2022
Published On 2022-10-02
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