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Internet of Things Architecture for Handling Stream Air Pollution Data

Topics: Data Analysis and Visualization for Smart City, Green Systems and Transport Systems; Data Management for Large Data; Energy, Environment and Natural Science Applications; Framework (conceptual, logical or software); Intelligent Systems for IoT and Services Computing ; Internet of Things; Sensor, Wireless Technologies, APIs; System Design and Architecture

Authors: Joschka Kersting 1 ; Michaela Geierhos 1 ; Hanmin Jung 2 and Taehong Kim 2

Affiliations: 1 University of Paderborn, Germany ; 2 Korea Institutue of Science and Technology Information, Korea, Republic of

Keyword(s): Wireless Sensor Network, Internet of Things, Stream Data, Air Pollution, DSMS, Real-time Data Processing.

Related Ontology Subjects/Areas/Topics: Data Communication Networking ; Enterprise Information Systems ; Internet of Things ; Sensor Networks ; Software Agents and Internet Computing ; Software and Architectures ; Telecommunications

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. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
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 - IoTBDS; ISBN 978-989-758-245-5; ISSN 2184-4976, SciTePress, pages 117-124. DOI: 10.5220/0006354801170124

@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 - IoTBDS},
year={2017},
pages={117-124},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006354801170124},
isbn={978-989-758-245-5},
issn={2184-4976},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security - IoTBDS
TI - Internet of Things Architecture for Handling Stream Air Pollution Data
SN - 978-989-758-245-5
IS - 2184-4976
AU - Kersting, J.
AU - Geierhos, M.
AU - Jung, H.
AU - Kim, T.
PY - 2017
SP - 117
EP - 124
DO - 10.5220/0006354801170124
PB - SciTePress