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All Journal Journal of Computation Physics and Earth Science
Raihan Ihwan, Muhammad Faiz
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Physics

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Integrasi AI/ML pada Edge Computing untuk Prediksi Cuaca yang Lebih Akurat Raihan Ihwan, Muhammad Faiz
Journal of Computation Physics and Earth Science (JoCPES) Vol 2 No 1 (2022): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53842/sphgkp71

Abstract

The integration of Artificial Intelligence (AI) and Machine Learning (ML) into edge computing systems presents a promising avenue for achieving highly accurate weather predictions. By leveraging real-time data collection, processing, and analysis capabilities directly on edge devices, this paper outlines a practical framework for improving predictive accuracy. We explore the challenges, advantages, and methodologies of deploying ML models on edge devices for weather forecasting applications. This study incorporates recent advancements in edge computing and AI algorithms, supported by a case study that demonstrates real-world implementation and results.
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