AI-Powered Edge Computing for Environmental Monitoring: A Cloud-Integrated Approach
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Environmental assessment is deemed more important as climate change, bio-diversity and resource conservation continue to present several challenges. Another is that traditional monitoring approaches may not give timely, relevant data especially when the environment is distant or rapidly changing. The present work aims to discuss the implementation of artificial intelligence-facilitated edge computing and cloud support as an innovative paradigm in environmental analysis. Edge computing helps to perform the data processing at the edge to help minimize latency time, and applying AI helps make the system more precise and helps with prediction. In this process, cloud integration becomes an enabler of these activities in the form of scalable storage, collaborative analytics, and in the form of control.
This is an applied research mapping the possible applications and pointing success stories of these technologies: detection of wildfire in Australia, flood in South East Asia, and wildlife monitoring in African savannas. It also talks about essential issues that need to be solved like security, power usage,e, and access, and provides information on how they can be solved. Future trends and innovation are also discussed in the paper to understand the significance of public-private partnership collaboration to promote AI-edge solutions in environmental monitoring.
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