The escalating demand for freshwater, driven by population growth and recurrent water crises, has heightened its significance. Despite California experiencing ample rainfall this year, water conservation has emerged as a critical concern. Facing steep water bills, Californians are actively seeking strategies to reduce their water consumption. In response, I am in the process of developing an AI/ML model that can analyze continuous water usage data, identifying distinct patterns associated with various activities. This data will facilitate the computation of detailed statistics on water consumption per appliance and activity, empowering individuals with insights into the distribution of their monthly bills based on appliance usage like showers, dishwashers, and laundry. The goal is to equip people with knowledge to make more informed decisions, promoting both cost savings and environmental sustainability. Through the utilization of machine learning algorithms, this project aims to offer a comprehensive breakdown of expenditures on different water-consuming activities, such as showering, dish cleaning, and laundry.