Monitoramento hidrometeorológico frente a ocorrência de desastres naturais: concepção e implementação de uma API REST para um sistema de gerenciamento de dados

Abstract

Given the challenges posed by climate change, real-time hydrometeorological monitoring plays a crucial role in combating and mitigating the effects of hydrological natural disasters. In Brazil, the Agencia Nacional das Águas e Saneamento Básico (ANA) is responsible for monitoring points of interest of the Union through the use of Plataforma de Coleta de Dados (PCDs). These PCDs are tasked with the continuous monitoring of hydrological variables and climatological elements; the collected data must be transmitted to a central unit responsible for processing, organizing, and disseminating the information obtained from the monitored data. In small municipalities, it is common for monitoring to be carried out by other government organizations, private sectors, and federal higher education institutions; however, in many cases the data collection is performed manually, requiring the presence of specialized technicians. Technologies such as General Packet Radio Service (GPRS), the HyperText Transfer Protocol (HTTP), and the implementation of an Application Programming Interface (API) based on the Representational State Transfer (REST) architecture – REST API – have proven efficient in the design of Web Systems for real-time data transmission. Thus, the present work aims to elucidate the process of developing a REST API through domain-driven modeling using the Django and Django REST frameworks. The first section introduces the context of the work, followed by an exposition of the objectives. The concepts of Systems Architecture (SA) and Systems Design (SD) are presented, addressing different perspectives on the scale at which a computer system operates. After presenting the general concepts of SA and SD, fundamental concepts of the REST architecture are introduced, with the primary objective of returning data structured in JSON format, along with an explanation of how the Django REST framework (DRF) functions. Next, the domain-driven modeling methodology is presented, outlining its main concepts. Within the domain context, topics such as the hydrological cycle, watershed, hydrology, hydrological monitoring networks, and the management of hydrological disasters are discussed. The study culminates in elucidating the process of implementing the REST API for a hydrometeorological data management system, employing domain-driven modeling and performance tests under different scenarios regarding data quantity and structure.