2026· CITA-DW· pp. 16-29· 0 citations· 37 references
Computer Science
TL;DR
It is demonstrated that a solution using consumer-grade components can effectively detect leaks with acceptable performance, paving the way for modernization of water infrastructure adapted to the Beninese context.
Lack of water is a major challenge in agriculture to guarantee food supply stability. Smallholder farming communities (SFCs) often hesitate to embrace digital solutions due to high costs, implementation complexities, and faulty sensors. To address this, we developed a low-cost (~USD 260), open-source "Intelligent Irrig...
B. Muthu· Natural Resources for Human...· 0 citations
This survey explores recent innovations in IoT-based Water Quality Monitoring Systems (IoT-WQMS) integrated with Machine Learning (ML) and Deep Learning (DL) to enable real-time, automated water quality assessment.
Kumar S. Ashok, Radhakrishnan C. V.· International Journal of Sci...· 0 citations
An end-to-end Internet of Things framework designed for real-time water quality monitoring and predictive pollution modeling and a hybrid machine learning architecture—combining Long Short-Term Memory (LSTM) networks for time-series forecasting and Random Forest models for anomaly classification—is proposed.
Parvathy Krishna V, G. S, Sahala Mehrin et al.· International Journal of Tec...· 0 citations
In modern agriculture, the quality of irrigation water plays a crucial role in determining crop productivity and soil health. With increasing reliance on precision farming methods, there is a growing need for intelligent systems that can continuously monitor and predict water quality to ensure safe and efficient usage....
M. Parvathi· Natural Resources for Human...· 0 citations
A novel hybrid multimodal approach called RF–LSTM–ANN which combines the Random Forest model for feature selection, the Long Short-Term Memory (LSTM) model for temporal dependency modeling and the Artificial Neural Network model for nonlinear binary classification is suggested.
The rapid expansion of offshore wind farms has introduced significant challenges to operation and maintenance (O&M), particularly under harsh marine environments where reliable electromagnetic information transmission and constrained wireless communication resources directly affect intelligent monitoring performance. T...
Yanqing Ouyang, W. Liang· Advanced Electromagnetics· 0 citations
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