Internet of Things Big Data Analytics: The Case of Noise Level Measurements at the Roskilde Music Festival

Tor-Morten Grønli, Benjamin Flesch, Raghava Rao Mukkamala, Ravi Vatrapu, Sindre Klavestad, Herman Bergner

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


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 languageEnglish
Title of host publicationProceedings of 2018 IEEE International Conference on Big Data
EditorsNaoki 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 pages6
Place of PublicationLos Alamitos, CA
Publication date24 Jan 2019
Article number8622406
ISBN (Print)9781538650363
ISBN (Electronic)9781538650356, 9781538650349
Publication statusPublished - 24 Jan 2019
EventSixth IEEE International Conference on Big Data. IEEE BigData 2018 - The Westin Seattle, Seattle, United States
Duration: 10 Dec 201813 Dec 2018
Conference number: 6


ConferenceSixth IEEE International Conference on Big Data. IEEE BigData 2018
LocationThe Westin Seattle
Country/TerritoryUnited States
Internet address


  • Internet of things
  • Big Data
  • Architecture
  • Big data analytics
  • IoT analytics
  • Sound measurement
  • Web stack

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