Optimization of water consumption using dynamic quota based smart water management system

Water is a vital resource for life and for the economy. Nowadays, one of the most serious challenges to solve is to manage water scarcity. As the importance of water usage optimization in monetary point of view is not that pronounced, we lack the incentive to invest in implementing technologically advanced systems for organized distribution of water. This paper describes the development of a meticulous water distribution system at a city level that will guarantee a continuous supply of water, overcoming some major issues like unaccounted supply to entities and Non-Revenue Water (NRW). A centralized control room equipped with a local computing machine and a Human Machine Interface (HMI) to monitor and control the city's water system is proposed. A smart tariff system should be exercised with an IoT-enabled mobile-friendly web portal developed for accessing various water usage statistics accompanied with an option of paying water bills online. In this volumetric, limit based model, the quota assigned to each entity is decided dynamically based on various supply and demand parameters including the availability of water with changing seasons. Adaptive learning through machine learning algorithms was used for the same. Unbilled, unauthorized consumption, apparent losses (water theft and metering inaccuracies) and transportation losses was curbed by monitoring from a remote location via IoT. Higher degree of theft and leakage was concluded using loss detection technique using the differential flow data. Here, a novel, cost-effective, realtime monitorable and controllable system is proposed with an analysis on a model simulation being performed for optimal water distribution.