This paper offers a comprehensive overview of machine learning (ML) methodologies and
algorithms, highlighting their practical applications in the critical domain of water resource …

With the increased use of automated systems, the Internet of Things (IoT), and sensors for
real-time water quality monitoring, there is a greater requirement for the timely detection of …

Water quality monitoring plays a vital role in the protection of water resources, environmental
management, and decision-making. Artificial intelligence (AI) based on machine learning …

Water quality and scarcity are key topics considered by the Sustainable Development Goals
(SDGs), institutions, policymakers and stakeholders to guarantee human safety, but also …

Since access to clean and safe water is one of life's most basic needs, the exponential
growth of the world's population makes it vital to guarantee a workable framework. Manually …

Monitoring water conditions in real-time is a critical mission to preserve the water ecosystem
in maritime and archipelagic countries, such as Indonesia that is relying on the wealth of …

Creating an adaptive, accurate, and reliable model is a universal problem. Machine learning
models give poor accuracy on unseen data, and therefore, the testing accuracy of the …

Safe drinking water is quite possibly one of the most difficult-to-find issues on our earth
intently influencing the well-being and cleanliness of humanity, animals, and plants. The …

Monitoring of water quality is one of the world's main intentions for countries. Classification
techniques based on support vector machines (SVMs) and artificial neural network (ANN) …

In this paper, a cost-effective and scalable wireless sensor network (WSN) system has been
developed, targeting monitoring and observation applications. The system specifically …