Internet of Things Architecture for Handling Stream Air Pollution Data

Joschka Kersting, Michaela Geierhos, Hanmin Jung, Taehong Kim

2017

Abstract

In this paper, we present an IoT architecture which handles stream sensor data of air pollution. Particle pollution is known as a serious threat to human health. Along with developments in the use of wireless sensors and the IoT, we propose an architecture that flexibly measures and processes stream data collected in real-time by movable and low-cost IoT sensors. Thus, it enables a wide-spread network of wireless sensors that can follow changes in human behavior. Apart from stating reasons for the need of such a development and its requirements, we provide a conceptual design as well as a technological design of such an architecture. The technological design consists of Kaa and Apache Storm which can collect air pollution information in real-time and solve various problems to process data such as missing data and synchronization. This enables us to add a simulation in which we provide issues that might come up when having our architecture in use. Together with these issues, we state reasons for choosing specific modules among candidates. Our architecture combines wireless sensors with the Kaa IoT framework, an Apache Kafka pipeline and an Apache Storm Data Stream Management System among others. We even provide open-government data sets that are freely available.

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Paper Citation


in Harvard Style

Kersting J., Geierhos M., Jung H. and Kim T. (2017). Internet of Things Architecture for Handling Stream Air Pollution Data . In Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS, ISBN 978-989-758-245-5, pages 117-124. DOI: 10.5220/0006354801170124


in Bibtex Style

@conference{iotbds17,
author={Joschka Kersting and Michaela Geierhos and Hanmin Jung and Taehong Kim},
title={Internet of Things Architecture for Handling Stream Air Pollution Data},
booktitle={Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,},
year={2017},
pages={117-124},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006354801170124},
isbn={978-989-758-245-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,
TI - Internet of Things Architecture for Handling Stream Air Pollution Data
SN - 978-989-758-245-5
AU - Kersting J.
AU - Geierhos M.
AU - Jung H.
AU - Kim T.
PY - 2017
SP - 117
EP - 124
DO - 10.5220/0006354801170124