International Journal Of Imaging

Abstract

Automated Water Quality and Level Monitoring with Hybrid Deep Learning CART Model

Author: Duwarapu Sindhuja , Ankalam Sai Pranaya , Movva Pranay Gopi , M. Nandini Priyanka

Abstract:

Water level monitoring is critical for effective water resource management, flood prevention, and infrastructure safety. Traditional water level monitoring systems primarily rely on static threshold- based mechanisms and simple regression models, which often lack the adaptability and precision required to handle dynamic environmental changes and extreme weather events. The limitations pose challenges such as delayed warnings, inaccurate predictions, and inefficient decision-making in critical situations. The paper presents an innovative automated water level monitoring system that integrates hybrid deep learning classifiers and regression models to process real-time sensor inputs. By combining classification techniques to categorize water levels with regression models for precise numerical predictions, the system achieves a higher degree of accuracy and responsiveness compared to traditional methods. The proposed approach addresses several limitations of conventional systems. Fi