Freshwater available for usage is very little, so conservation and efficient usage of water plays a major role, to avoid scarcity of consumable water shortly. To help in saving water, the knowledge of where the water is getting wasted becomes important. The development of the smart city initiative taken by the government helps to preserve the natural resources and avoid unnecessary wastage. A smart water meter management system is designed and analyzed here. In this paper, the anomaly detection using a smart water meter in a house/ building is being analyzed using a few technologies like IoT, Cloud Computing, and ML Algorithms. DBSCAN, Isolation Forest, and K-Means are a few of the unsupervised clustering algorithms that are used to find outliers in the smart water consumption dataset. The goodness measure of each anomaly detection algorithms is represented by the graph showing the outliers in each of the cases.