Due to the increasing demand for water supply of urban areas, treatment and supply plants are becoming important to ensure availability and quality of this essential resource for human health. Enabling technologies of Industry 4.0 have the potential to improve performances of treatment plants. In this paper, after reviewing contributions in scientific literature on I4.0 technologies in dam operations, a study carried out on a Brazilian dam is presented and discussed. The main purpose of the study is to evaluate the economic, environmental, and social advantages achieved through the adoption of Artificial Intelligence (AI) in dam operations. Unlike automation that just respond to commands, AI uses a large amount of data training to make computers able to take the best decision. The current study involved a company that managed six reservoirs for treatment systems supplying water to almost ten million people at the metropolitan area of São Paulo City. Results of the study show that AI adoption could lead to economic gain in figures around US$ 51,000.00 per year, as well as less trips between sites and less overtime extra costs on the main operations. Increasing gates maneuvers agility result in significant environmental gains with savings of about 4.32 billion L of water per year, enough to supply 73,000 people. Also, decreasing operational vehicle utilization results in less emissions. Finally, the AI implementation improved the safety of dam operations, resulting in social benefits such as the flood risk mitigation in cities and the health and safety of operators.

This work is aimed at demonstrating the advantages that AI can bring to dam management and which parameters and calculations are important to make the simulations more realistic. To this end, a computational approach that combines a Multilayer Perceptron Artificial Neural Network (MLP-ANN) and Monte Carlo Simulation (MCS) method was developed and tested in simulations of floodgate operation using data collected from one of the biggest sanitation companies in the world. The conducted systematic review and simulations allowed to demonstrate the contributions of this study to the scientific literature and organizational practice, mainly because it shows that the application of the proposed approach can eliminates the need for manual operations in dams, including those aimed at preventing disasters and water wastage.