A Microservices-Based IoT Analytics Architecture for Real-Time Environmental Monitoring
TL;DR
The proposal integrates continuous collection, stream processing, temporal analytical storage, and interactive visualization via dashboards within a microservices framework within a microservices framework and indicates consistent gains in real-time indicator retrieval, historical time-series exploration, and the execution of analytical tasks.
Abstract
This paper presents an IoT Analytics architecture for real-time environmental monitoring, designed to overcome the limitations of solutions that provide limited support for operational and historical data analysis. The proposal integrates continuous collection, stream processing, temporal analytical storage, and interactive visualization via dashboards within a microservices framework. An end-to-end pipeline was implemented using open-source tools, and an evaluation was conducted in a real-world scenario in the state of Acre, Brazil, in comparison with the platform currently used for air quality monitoring. In the usability evaluation, the proposed solution achieved mean scores between 6.20 and 6.65 (on a Likert scale from 1 to 7), while the reference solution ranged between 2.15 and 2.50. The results indicate consistent gains in real-time indicator retrieval, historical time-series exploration, and the execution of analytical tasks.