Modelo de gestión de alertas tempranas para la predicción de riesgos en el contexto de Smart City para la Ciudad de Bogotá D.C.

Abstract

Risk management is made up of three elements: the first is risk awareness, the second is risk reduction, and the third is disaster management. This research focused on the component of risk knowledge and on proposing a model for the management of early warnings in the context of Smart City that allows contributing to the prediction and mitigation of risks in the city of Bogotá DC, for which a risk knowledge model was designed and a business architecture based on TOGAF was proposed that allows understanding, from a business scenario, what the objectives, goals and processes of this component are, as well as allowing the identification of the business focuses to which an organization is dedicated. risk awareness, ten experiments were carried out to test different components of the architectures, where information, modeling, artificial intelligence, and hardware components were tested, so the results show the potential of the model not only for events such as floods and mass movement, but they are also applicable in scenarios of climate change and agricultural risks, expanding the context of applications to different types of events.