can you summarize the following text in less than 250 words, its an abstract for a research paper:
Access to safe drinking water is a fundamental human right, yet millions of people worldwide lack this essential resource. The primary objective of this study is to develop a machine learning model capable of predicting water drinkability based on a specific set of input parameters.

To achieve this, various water quality parameters and methods were employed to assess water quality from diverse water sources. The collected data were then utilized in training a binary classification model, employing algorithms such as logistic regression, random forests, XGBoost, and SVM. Input features included physical and chemical parameters like pH, turbidity, total dissolved solids, and conductivity, alongside other commonly used parameters in assessing water quality.

The SVM algorithm achieved the highest accuracy rate of 82.3% among all models, demonstrating its ability to predict the binary target column concerning water potability. The most significant parameters in determining water drinkability were pH, total dissolved solids, and hardness.

The model's output can assist in making informed decisions regarding water quality and serve as a valuable tool in improving access to safe drinking water. Moreover, the model's scalability enables deployment online, allowing individuals to assess water quality in their vicinity.

Overall, this project underscores machine learning's potential in addressing critical public health iss