Effective monitoring of river water quality is required for long-term water resource
management. Convolutional Neural Networks and Gated Recurrent Unit-based water quality …

In the quest to reconcile public perception of air pollution with scientific measurements, our
study introduced a pioneering method involving a gradient boost-regression tree model …

Particulate matter (PM) pollution is a major global concern due to its negative impact on
human health. To effectively address this issue, it is crucial to have a reliable and efficient …

This study aims to predict vital soil physical properties, including clay, sand, and silt, which
are essential for agricultural management and environmental protection. Precision …

Abstract Fine particle matter (PM 2.5) pollution is a global environmental problem and has
significant impacts on air quality and human health. Accurate prediction is crucial for …

Our research addresses the imperative need for an efficient air quality monitoring and
forecasting system to mitigate the significant health risks of air pollution. Departing from …

Air quality forecasting is vital for sustainable development in smart cities and is essential to
protect public health through early warning against air pollutants. This article presents a …

Predicting water quality is a significant area of study in the field of smart water technology,
since it may provide valuable assistance in managing and mitigating water pollution. Due to …

Abstract For decades, PM 2.5 (a type of fine particulate matter) in large urban areas has had
a profound negative impact on human health. In this study, spatiotemporal analysis and four …

The present study demonstrates the development of an Android Application that aims to
calculate the allowable bearing pressure for shallow foundations and safe load on pile …