This study presents an AI-driven computational framework for optimizing the orientation and spatial deployment of photovoltaic (PV) systems installed on uneven terrain, with the objective of enhancing energy efficiency and supporting sustainable energy development. The proposed m…
The growing energy demand has increased the number of wind turbines, raising the need to monitor blade health. Since blades are prone to damage that can cause severe failures, early detection is crucial. Machine learning-based monitoring systems can identify and locate cracks wit…
This review explores the use of machine learning (ML) techniques for detecting pests and diseases in crops, which is a significant challenge in agriculture, leading to substantial yield losses worldwide. This study focuses on the integration of ML models, particularly Convolution…
This article presents a systematic review using PRISMA methodology to explore trends in the use of machine and deep learning in diagnosing and detecting Alzheimer’s disease using electroencephalography. This review covers studies published between 2013 and 2023, drawing on three…