The management of water as a natural resource is not well understood so far as basic principles are concerned and natural processes of water storage and stream flow are complex and are not always easy to measure accurately.
Water makes up about 70% of the earth’s floor and is one of the most vital sources essential to maintaining life. Speedy urbanization and industrialization have led to a deterioration of water best at an alarming fee, ensuing in harrowing illnesses. Water high- quality has been conventionally estimated through expensive and time-ingesting lab and statistical analyses, which render the cutting-edge belief of real-time tracking moot. The alarming results of bad water nice necessitate an alternative approach that is quicker and inexpensive. With this motivation, this study explores a sequence of supervised device mastering algorithms to estimate the water high-quality. The proposed methodology achieves affordable accuracy the use of a minimum number of parameters to validate the possibility of its use in real time water first-class detection systems. It demonstrates the overall maintenance and management of the water quality and quantity inside a plant using modern technologies. It based on the systematic working process to reduce the man power and cost maintenance for the industrialization development.