Internet of Things Architecture for Handling Stream Air Pollution Data

被引:3
|
作者
Kersting, Joschka [1 ]
Geierhos, Michaela [1 ]
Jung, Hanmin [2 ]
Kim, Taehong [2 ]
机构
[1] Univ Paderborn, Heinz Nixdorf Inst, Furstenallee 11, D-33102 Paderborn, Germany
[2] Korea Inst Sci & Technol Informat, Sci Data Res Ctr, Daejeon, South Korea
来源
IOTBDS: PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON INTERNET OF THINGS, BIG DATA AND SECURITY | 2017年
关键词
Wireless Sensor Network; Internet of Things; Stream Data; Air Pollution; DSMS; Real-time Data Processing;
D O I
10.5220/0006354801170124
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:117 / 124
页数:8
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