A Model-Driven Framework for Water Supply Management System (MWS)

Abstract

Water supply management is a difficult and crucial undertaking that demands effective methods and equipment. Multiple models are necessary to address this difficulty. Model-Driven Architecture (MDA) can be used to successfully construct and modify these models, with the potential to dramatically enhance water supply management. This scientific idea has the potential to completely alter how we manage our water supplies, which makes it very interesting. The capacity to model complete water supply networks virtually is one of MDA's ground-breaking features in this domain. We can test and evaluate a wide range of scenarios using these virtual models without having to spend a lot of money or risk putting the real system at risk. We propose a thorough model-driven framework that makes use of MDA principles in this study. The first phase in our methodology's multi-step procedure is to convert the conceptual model into a textual representation. A dedicated transformation engine created with the help of the model-to-text transformation tool Acceleo® facilitates this transformation. As a result, timed automata models replace abstract software models. In the complicated field of water supply management, timed automata are a particularly useful tool for modeling and analyzing the timing behavior of complex systems. We can comprehend and improve the temporal elements of water supply processes by adding timed automata models. We carried out real-time case studies to show how useful and successful our framework is. These case studies validate the efficacy of our approach in simulating water supply management systems. With formal verification techniques, we not only ensure standardization but also lessen the possibility of potential system defects. Additionally, the addition of formal verification offers a mechanism for potential problems' early detection. The total reliability of water supply management systems will significantly rise because of our ability to spot issues early and fix them.