Project Simulation, Validation and Deployment with DEVS. IoT Framework for Blooms Monitoring and Alert

Harmful Algal and Cyanobacterial Blooms (HABs) constitute a relevant public health and ecological hazard due to their frequent production of toxic metabolites, which is increased by the current vulnerability of water resources to environmental changes such as global warming, population growth, and eutrophication. These blooms have been typically assessed by combining predictive models with manual collection. However, these processes are generally independent and do not provide data with sufficient resolution to apply proactive policies. In this work, we propose a novel and integrative framework to straightforwardly combine the conception, design, and deployment of advanced Early-Warning Systems (EWSs) that will allow us to automate all the processes involved in HABs detection and management and apply proactive policies. The framework is built upon solid Modeling and Simulation (M&S) principles, through Model Based Systems Engineering (MBSE) as the driving methodology and Discrete Event System Specification (DEVS) as the M&S formalism.