Sistema IoT para el monitoreo inteligente de la calidad del aire en zonas urbanas de Quito.

Abstract

Abstract: The primary objective of this study is to facilitate public, real-time access to environmental data, overcoming the limitations of hyper-local scope and the high maintenance costs associated with conventional monitoring stations. Methodologically, the development followed the Agile Scrum framework, utilizing a decoupled structure organized into three functional layers. In the physical data-capture phase, an ESP32 board was interfaced with low-cost sensors to collect data on suspended particulate matter, carbon dioxide, and climatic parameters, transmitting these data packets via Wi-Fi to the AWS IoT Core cloud. Data processing and storage were managed through an asynchronous API built with FastAPI, employing a dual-database architecture: MongoDB for administrative management and InfluxDB for continuous data streaming. The user interface was developed using React.js and includes alert mechanisms based on thresholds recommended by the World Health Organization (WHO). Experimental evaluations demonstrated optimal system performance, achieving a score of 82.3 on the System Usability Scale (SUS), meeting certified web accessibility standards, and exhibiting high resilience against vulnerabilities such as NoSQL injection and cross-site scripting (XSS). Consequently, the platform proves its utility as a reliable and scalable technical resource for fostering community engagement and supporting respiratory health initiatives.