Publisher's Synopsis
An Artificial Intelligence (AI) model for the prediction of faecal coliform bacteria in ground water is a computational tool that uses machine learning algorithms to analyze water quality data and predict the concentration of faecal coliform bacteria in ground water. Faecal coliform bacteria are a type of bacteria commonly found in the intestines of warm-blooded animals, and their presence in ground water can indicate contamination from human or animal waste, which can be harmful to human health.
The AI model for prediction of faecal coliform bacteria in ground water may utilize various data sources, including water quality measurements such as pH, temperature, dissolved oxygen, turbidity, and conductivity, as well as geographic and environmental factors such as land use, soil type, and hydrogeology. The model may be trained using historical water quality data, along with other relevant data sources, to learn patterns and relationships between water quality variables and the concentration of faecal coliform bacteria in ground water.
Once the AI model is trained, it can be used to predict the concentration of faecal coliform bacteria in ground water based on current or future water quality measurements. This information can be used by water managers, policymakers, and other stakeholders to identify potential sources of contamination, implement mitigation measures, and protect human health and the environment.
