A prototype of the crowdsensing system for pollution monitoring in a smart city based on data streaming

This paper proposes a prototype of the crowdsensing system for pollution monitoring in a smart city based on data streaming. The first part of the paper analyses concepts, characteristics, and platforms for data streaming. The Apache Kafka solution for data flow management is described. The paper proposes infrastructure for data streaming from the IoT crowdsensing sys-tems for monitoring pollution in smart cities. Crowdsensing services included in this system enable the monitoring of pollution parameters in smart cities. Collected pollution data in the smart city (traffic vibrations, noise, allergens, and air pollution) can be conducted using the Internet of Things (microcom-puters, microcontrollers, sensors, etc.) and mobile devices, sent to the Apache Kafka cluster using the MQTT protocol, and then data can be streamed via the web application to end users. Active parts in collecting pol-lution data have citizens. All collected data can be processed, analyzed, and streamed using the proposed data streaming infrastructure for smart city crowdsensing systems.