Water contamination is a growing concern that poses significant risks to public health and the environment. Developing precise and efficient water quality monitoring systems are crucial to address this issue. This paper introduces an automated real-time monitoring, alarming, and information-sharing system based on the Arduino Internet of Things (IoT) platform and the Bayes Theorem for detecting water contamination. The proposed system utilizes the Arduino IoT platform, cloud server, and data analytics to monitor key water parameters, including pH levels, turbidity, Hardness, Humidity, Temperature, and total dissolved solids (TDS), in real time. By employing the Bayes Theorem, the system can detect, predict, and monitor water contamination accurately and promptly. In the event of potential contamination, the system generates alerts and shares critical information with relevant authorities to take immediate preventive measures. The system has been rigorously tested in various scenarios, demonstrating high accuracy, sensitivity, and reliable prediction of water contaminants. This innovative approach shows great promise in revolutionizing water quality monitoring, ensuring safer water resources, and safeguarding public health.