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

doi:10.1109/BigData.2018.8622406

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

Institut for Digitalisering

Høyskolen Kristiania

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

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.

Originalsprog	Engelsk
Titel	Proceedings of 2018 IEEE International Conference on Big Data
Redaktører	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
Antal sider	6
Udgivelsessted	Los Alamitos, CA
Forlag	IEEE
Publikationsdato	24 jan. 2019
Sider	5153-5158
Artikelnummer	8622406
ISBN (Trykt)	9781538650363
ISBN (Elektronisk)	9781538650356, 9781538650349
DOI	https://doi.org/10.1109/BigData.2018.8622406
Status	Udgivet - 24 jan. 2019
Begivenhed	Sixth IEEE International Conference on Big Data. IEEE BigData 2018 - The Westin Seattle, Seattle, USA Varighed: 10 dec. 2018 → 13 dec. 2018 Konferencens nummer: 6 http://cci.drexel.edu/bigdata/bigdata2018/index.html

Konference

Konference	Sixth IEEE International Conference on Big Data. IEEE BigData 2018
Nummer	6
Lokation	The Westin Seattle
Land/Område	USA
By	Seattle
Periode	10/12/2018 → 13/12/2018
Internetadresse	http://cci.drexel.edu/bigdata/bigdata2018/index.html

Emneord

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

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10.1109/BigData.2018.8622406Licens: Ikke-specificeret

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Citationsformater

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. 5153-5158). Artikel 8622406 IEEE. https://doi.org/10.1109/BigData.2018.8622406

Grønli, Tor-Morten ; Flesch, Benjamin ; Mukkamala, Raghava Rao et al. / 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. Los Alamitos, CA : IEEE, 2019. s. 5153-5158

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

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",

year = "2019",

month = jan,

day = "24",

doi = "10.1109/BigData.2018.8622406",

language = "English",

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booktitle = "Proceedings of 2018 IEEE International Conference on Big Data",

publisher = "IEEE",

address = "United States",

note = "Sixth IEEE International Conference on Big Data. IEEE BigData 2018 ; Conference date: 10-12-2018 Through 13-12-2018",

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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., 8622406, IEEE, Los Alamitos, CA, s. 5153-5158, Sixth IEEE International Conference on Big Data. IEEE BigData 2018, Seattle, Washington, USA, 10/12/2018. https://doi.org/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 et al.
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. Los Alamitos, CA: IEEE, 2019. s. 5153-5158 8622406.

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

TY - GEN

T1 - Internet of Things Big Data Analytics

T2 - Sixth IEEE International Conference on Big Data. IEEE BigData 2018

AU - Grønli, Tor-Morten

AU - Flesch, Benjamin

AU - Mukkamala, Raghava Rao

AU - Vatrapu, Ravi

AU - Klavestad, Sindre

AU - Bergner, Herman

N1 - Conference code: 6

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.

KW - Internet of things

KW - Big Data

KW - Architecture

KW - Big data analytics

KW - IoT analytics

KW - Sound measurement

KW - Web stack

KW - Internet of things

KW - Big Data

KW - Architecture

KW - Big data analytics

KW - IoT analytics

KW - Sound measurement

KW - Web stack

U2 - 10.1109/BigData.2018.8622406

DO - 10.1109/BigData.2018.8622406

M3 - Article in proceedings

SN - 9781538650363

SP - 5153

EP - 5158

BT - Proceedings of 2018 IEEE International Conference on Big Data

A2 - Abe, Naoki

A2 - Liu, Huan

A2 - Pu, Calton

A2 - Hu, Xiaohua

A2 - Ahmed, Nesreen

A2 - Qiao, Mu

A2 - Song, Yang

A2 - Kossmann, Donald

A2 - Liu, Bing

A2 - Lee, Kisung

A2 - Tang, Jiliang

A2 - He, Jingrui

A2 - Saltz, Jeffrey

PB - IEEE

CY - Los Alamitos, CA

Y2 - 10 December 2018 through 13 December 2018

ER -

Grønli TM, 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. Los Alamitos, CA: IEEE. 2019. s. 5153-5158. 8622406 doi: 10.1109/BigData.2018.8622406