The Smart Stadium for Smarter Living project provides an end-to-end testbed for IoT innovation through a collaboration between Croke Park Stadium in Dublin, Ireland and Dublin City University, Intel and Microsoft. This enables practical evaluations of IoT solutions in a controlled environment that is small enough to conduct trials but large enough to prove and challenge the technologies. An evaluation of sound monitoring capabilities during the 2016 sporting finals was used to test the capture, transfer, storage and analysis of decibel level sound monitoring. The purpose of the evaluation was to use existing sound level microphones to measure crowd response to pre-determined events for display on big screens at half-time and to test the end-to-end performance of the testbed. While this is not the specific original purpose of the sound level microphones, it provided a useful test case and produced engaging content for the project. Analysis of the data streams showed significant packet loss during the events and further investigations were conducted to understand where and how this loss occurred. This paper describes the smart stadium testbed configuration using Intel gateways linking with the Azure cloud platform and analyses the performance of the system during the sound monitoring evaluation.
Ireland ->
Dublin City University ->
Publication Type = Conference or Workshop Item
Ireland ->
Dublin City University ->
DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing: School of Computing
Ireland ->
Dublin City University ->
Subject = Computer Science: Multimedia systems
Ireland ->
Dublin City University ->
DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing: School of Electronic Engineering
Ireland ->
Dublin City University ->
Status = In Press
Ireland ->
Dublin City University ->
Subject = Computer Science: Computer networks
Ireland ->
Dublin City University ->
DCU Faculties and Centres = Research Initiatives and Centres: INSIGHT Centre for Data Analytics
Tomas Meehan,
Clare Dillon,
Mike Myers,
Niall Moran,
Brian Quinn,
Keith Nolan,
David Prendergast,
Noel E. O'Connor,
Camille Ballas,
Dian Zhang
and 1 others