Abstract
In this paper we demonstrate the feasibility of IoT deployment for noise level measurement to time-limited and high-intense, high-volume data, events. Through an iterative process, a prototype solution were designed and implemented in a real-time, privacy-compliant IoT sensor system under tight constraints concerning budget and development time. Our sensor system enables festival management to easily track, document and further, by applying real time big data analytics to the harvested information, have fact-full insights generated for decision making in terms of resolving noise disturbances. The whole approach was demonstrated by the use of lightweight Internet of Things architecture demonstrating how web technologies can be used throughout the technology stack in and IoT big data analytics case.
Original language | English |
---|---|
Title of host publication | Proceedings of 2018 IEEE International Conference on Big Data |
Editors | Naoki Abe, Huan Liu, Calton Pu, Xiaohua Hu, Nesreen Ahmed, Mu Qiao, Yang Song, Donald Kossmann, Bing Liu, Kisung Lee, Jiliang Tang, Jingrui He, Jeffrey Saltz |
Number of pages | 6 |
Place of Publication | Los Alamitos, CA |
Publisher | IEEE |
Publication date | 24 Jan 2019 |
Pages | 5153-5158 |
Article number | 8622406 |
ISBN (Print) | 9781538650363 |
ISBN (Electronic) | 9781538650356, 9781538650349 |
DOIs | |
Publication status | Published - 24 Jan 2019 |
Event | Sixth IEEE International Conference on Big Data. IEEE BigData 2018 - The Westin Seattle, Seattle, United States Duration: 10 Dec 2018 → 13 Dec 2018 Conference number: 6 http://cci.drexel.edu/bigdata/bigdata2018/index.html |
Conference
Conference | Sixth IEEE International Conference on Big Data. IEEE BigData 2018 |
---|---|
Number | 6 |
Location | The Westin Seattle |
Country/Territory | United States |
City | Seattle |
Period | 10/12/2018 → 13/12/2018 |
Internet address |
Keywords
- Internet of things
- Big Data
- Architecture
- Big data analytics
- IoT analytics
- Sound measurement
- Web stack