A Data Streaming Architecture for Air Quality Monitoring in Smart Cities

Abstract

This paper aims to present a modeling approach for the seamless data streaming process from smart IoT systems to Apache Kafka, leveraging the MQTT protocol. The paper begins by discussing the concept of real-time data streaming, emphasizing the need to transfer data from IoT/edge devices and sensors to Apache Kafka in a timely manner. The second part consists of a literature overview that shows the analysis and systematization of different types of architectures in the broad sense of crowdsensing, followed by specific architectures regarding edge and cloud computing. The methodology section will propose an infrastructure and data streaming architecture for smart environment services, such as air quality monitoring. Lastly, a discussion about results and future development will be shown in the last two sections. The proposed integration approach offers several advantages, including efficient and scalable data streaming, real-time analytics, and enhanced data processing capabilities.