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

Publikation: Kapitel i bog/rapport/konferenceprocesKonferencebidrag i proceedingsForskningpeer review

Resumé

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.
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.
SprogEngelsk
TitelProceedings of 2018 IEEE International Conference on Big Data
RedaktørerNaoki 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
Antal sider6
Udgivelses stedLoa Alamos, CA
ForlagIEEE
Dato24 jan. 2019
Sider5136-5141
ISBN (Trykt)9781538650363
ISBN (Elektronisk)9781538650356, 9781538650349
DOI
StatusUdgivet - 24 jan. 2019
Begivenhed2018 IEEE International Conference on Big Data - The Westin Seattle, Seattle, USA
Varighed: 10 dec. 201813 dec. 2018
Konferencens nummer: 6
http://cci.drexel.edu/bigdata/bigdata2018/index.html

Konference

Konference2018 IEEE International Conference on Big Data
Nummer6
LokationThe Westin Seattle
LandUSA
BySeattle
Periode10/12/201813/12/2018
Internetadresse

Bibliografisk note

CBS Bibliotek har ikke adgang til materialet

Emneord

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

Citer dette

Grønli, T-M., Flesch, B., Mukkamala, R. R., Vatrapu, R., Klavestad, S., & Bergner, H. (2019). Internet of Things Big Data Analytics: The Case of Noise Level Measurements at the Roskilde Music Festival. I N. Abe, H. Liu, C. Pu, X. Hu, N. Ahmed, M. Qiao, Y. Song, D. Kossmann, B. Liu, K. Lee, J. Tang, J. He, ... J. Saltz (red.), Proceedings of 2018 IEEE International Conference on Big Data (s. 5136-5141). Loa Alamos, CA: IEEE. DOI: 10.1109/BigData.2018.8622406
Grønli, Tor-Morten ; Flesch, Benjamin ; Mukkamala, Raghava Rao ; Vatrapu, Ravi ; Klavestad, Sindre ; Bergner, Herman. / Internet of Things Big Data Analytics : The Case of Noise Level Measurements at the Roskilde Music Festival. Proceedings of 2018 IEEE International Conference on Big Data. red. / 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. Loa Alamos, CA : IEEE, 2019. s. 5136-5141
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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.",
keywords = "Internet of things, Big Data, Architecture, Big data analytics, IoT analytics, Sound measurement, Web stack, Internet of things, Big Data, Architecture, Big data analytics, IoT analytics, Sound measurement, Web stack",
author = "Tor-Morten Gr{\o}nli and Benjamin Flesch and Mukkamala, {Raghava Rao} and Ravi Vatrapu and Sindre Klavestad and Herman Bergner",
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year = "2019",
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Grønli, T-M, Flesch, B, Mukkamala, RR, Vatrapu, R, Klavestad, S & Bergner, H 2019, Internet of Things Big Data Analytics: The Case of Noise Level Measurements at the Roskilde Music Festival. i N Abe, H Liu, C Pu, X Hu, N Ahmed, M Qiao, Y Song, D Kossmann, B Liu, K Lee, J Tang, J He & J Saltz (red), Proceedings of 2018 IEEE International Conference on Big Data. IEEE, Loa Alamos, CA, s. 5136-5141, 2018 IEEE International Conference on Big Data, Seattle, USA, 10/12/2018. DOI: 10.1109/BigData.2018.8622406

Internet of Things Big Data Analytics : The Case of Noise Level Measurements at the Roskilde Music Festival. / Grønli, Tor-Morten; Flesch, Benjamin; Mukkamala, Raghava Rao; Vatrapu, Ravi; Klavestad, Sindre; Bergner, Herman.

Proceedings of 2018 IEEE International Conference on Big Data. red. / 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. Loa Alamos, CA : IEEE, 2019. s. 5136-5141.

Publikation: Kapitel i bog/rapport/konferenceprocesKonferencebidrag i proceedingsForskningpeer review

TY - GEN

T1 - Internet of Things Big Data Analytics

T2 - The Case of Noise Level Measurements at the Roskilde Music Festival

AU - Grønli,Tor-Morten

AU - Flesch,Benjamin

AU - Mukkamala,Raghava Rao

AU - Vatrapu,Ravi

AU - Klavestad,Sindre

AU - Bergner,Herman

N1 - CBS Library does not have access to the material

PY - 2019/1/24

Y1 - 2019/1/24

N2 - 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.

AB - 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.

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KW - Sound measurement

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KW - Big Data

KW - Architecture

KW - Big data analytics

KW - IoT analytics

KW - Sound measurement

KW - Web stack

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DO - 10.1109/BigData.2018.8622406

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SN - 9781538650363

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BT - Proceedings of 2018 IEEE International Conference on Big Data

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CY - Loa Alamos, CA

ER -

Grønli T-M, Flesch B, Mukkamala RR, Vatrapu R, Klavestad S, Bergner H. Internet of Things Big Data Analytics: The Case of Noise Level Measurements at the Roskilde Music Festival. I Abe N, Liu H, Pu C, Hu X, Ahmed N, Qiao M, Song Y, Kossmann D, Liu B, Lee K, Tang J, He J, Saltz J, red., Proceedings of 2018 IEEE International Conference on Big Data. Loa Alamos, CA: IEEE. 2019. s. 5136-5141. Tilgængelig fra, DOI: 10.1109/BigData.2018.8622406