Designing a data streaming infrastructure for a smart city crowdsensing platform

Abstract

This article considers the problem of designing data streaming infrastructures for crowdsensing systems. The goal is to propose an infrastructure that would provide a scalable and seamless collection of various data in smart city, such as noise, vibrations, air quality, citizens’ health parameters, etc., streaming collected data into the cloud infrastructure, and preparing it for further analysis. The paper focuses on the aspects of modelling data streams, and the implementation using the Apache Kafka software. The prototype of the proposed system is implemented within the private cloud infrastructure of the Department of e-business, Faculty of Organizational Sciences.