American Journal of Advanced Multidisciplinary Research and Innovation

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Emerging Technologies for Climate Resilience: Integrating Artificial Intelligence, Remote Sensing, and Sustainable Infrastructure

Author(s) Ken Goldberg
Country United States
Abstract Climate change has intensified the frequency and severity of extreme weather events, sea-level rise, biodiversity loss, water scarcity, and ecosystem degradation, posing significant challenges to sustainable development and human well-being. Building climate resilience requires innovative, technology-driven approaches that enable proactive adaptation, disaster risk reduction, efficient resource management, and evidence-based policymaking. Emerging technologies such as Artificial Intelligence (AI), Remote Sensing, Geographic Information Systems (GIS), Internet of Things (IoT), cloud computing, Digital Twin technology, Big Data Analytics, unmanned aerial vehicles (UAVs), and sustainable infrastructure are transforming climate monitoring, environmental assessment, and resilience planning. AI-driven predictive models analyse vast environmental datasets, while remote sensing technologies provide real-time Earth observation for monitoring land use, vegetation, water resources, urban expansion, and natural disasters. Sustainable infrastructure integrates these digital technologies to improve resilience, optimise resource utilisation, and support climate adaptation strategies.
This study investigates the integration of Artificial Intelligence, Remote Sensing, and sustainable infrastructure for climate resilience using a qualitative and analytical research methodology based on secondary data collected from peer-reviewed journals, government reports, international climate assessments, and multidisciplinary case studies. The study examines technological architectures, interdisciplinary applications, implementation challenges, and future research opportunities. It further analyses the integration of AI with satellite imagery, IoT-based environmental monitoring, Digital Twin technology, blockchain, edge computing, and explainable AI to develop intelligent climate resilience ecosystems.
The findings indicate that AI-powered predictive analytics, remote sensing, and sustainable infrastructure significantly improve climate risk assessment, disaster preparedness, flood forecasting, drought monitoring, precision agriculture, renewable energy management, urban resilience, biodiversity conservation, and ecosystem restoration. These technologies support data-driven environmental governance, resilient infrastructure planning, and adaptive resource management while contributing to the United Nations Sustainable Development Goals (SDGs).
Despite these opportunities, implementation faces challenges related to data quality, cybersecurity, interoperability, infrastructure investment, regulatory coordination, ethical AI governance, digital inequality, and workforce capability. The study concludes that interdisciplinary collaboration, responsible digital innovation, climate-focused policies, and investment in resilient infrastructure are essential for developing intelligent climate resilience systems capable of addressing future environmental challenges.
Keywords Climate Resilience, Artificial Intelligence, Remote Sensing, Sustainable Infrastructure, Geographic Information Systems, Internet of Things, Climate Adaptation, Digital Twin, Environmental Sustainability, Smart Technologies.
Field Engineering
Published In Volume 3, Issue 2, March-April 2021
Published On 2021-03-19
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