Issue |
E3S Web Conf.
Volume 125, 2019
The 4th International Conference on Energy, Environment, Epidemiology and Information System (ICENIS 2019)
|
|
---|---|---|
Article Number | 25005 | |
Number of page(s) | 4 | |
Section | Health, Safety, and Environment Information Systems | |
DOI | https://doi.org/10.1051/e3sconf/201912525005 | |
Published online | 28 October 2019 |
Application of Internet of Things (IoT) on air pollution monitoring database system
1 Department of Mechanical Engineering, Institut Sains & Teknologi AKPRIND Yogyakarta - Indonesia
2 Department of Electrical Engineering, Institut Sains & Teknologi AKPRIND Yogyakarta - Indonesia
3 Department of Industrial Engineering, Institut Sains & Teknologi AKPRIND Yogyakarta - Indonesia
* Corresponding author: sudarsono1574@akprind.ac.id
In the present work, a database system of air pollution monitoring is developed using Internet of Things (IoT) technology. The system aims to give structural information and trace of air pollution level at particular monitoring station. The particular monitoring location (node) is connected to IoT/M2M server via GSM network using GPRS feature and display on IoT/M2M application in web form. The database on IoT/M2M contains name, description, and location of the monitoring station, Pollution index and the time when the data are taken. On IoT/M2M, the data are displayed either in a color bar graph or a line graph. The color indicated the index value of the pollution. The data can be accessed via internet on isfuonline.info. The system is tested at laboratory environment to detect CO, SO2, NO2, O3, and PM. The test result shows that the system is worked well. Time required to transfer the monitoring data to the IoT server is about 15 minutes. Meanwhile, response time of the system is 30 minutes.
Key words: Internet of Things (IoT) / air pollution / database system
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.