Real-Time Monitoring of Glacial Changes Using Artificial Intelligence

Because of the fast changes that climate change is bringing about in glacial environments, real-time monitoring is essential to comprehending and reducing its consequences. In order to observe glacial change in real time, this research study provides a novel method that makes use of artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT). We start by providing a brief overview of the problem's urgency and the shortcomings of the conventional monitoring techniques. The study then goes on to talk about the main elements of our AI and ML-based system, which include data integration from IoT devices and distant sensors, machine learning algorithms, and analysis of satellite images. Researchers can more accurately understand the intricate dynamics of glacier behaviour thanks to the automated detection of glacial movement, changes in ice thickness, and patterns of meltwater made possible by AI and ML models. As we dig further, the article looks at creating an approachable interface that would make real-time glacier data accessible to scholars, decision-makers, and the general public. It also emphasises how early warning systems may help reduce the risks associated with glaciers and provide guidance for plans aimed at adapting to climate change. This multi-faceted approach, from the simplicity of AI and ML implementation to its intricate data analysis capabilities, in conjunction with IoT, represents a significant advancement in our ability to monitor and respond to glacial changes in real-time.