Title :
Practical Analysis of Big Acoustic Sensor Data for Environmental Monitoring
Author :
Truskinger, Anthony ; Cottman-Fields, Mark ; Eichinski, Philip ; Towsey, Michael ; Roe, Paul
Author_Institution :
QUT Ecoacoustics Res. Group, Queensland Univ. of Technol., Brisbane, QLD, Australia
Abstract :
Monitoring the environment with acoustic sensors is an effective method for understanding changes in ecosystems. Through extensive monitoring, large-scale, ecologically relevant, datasets can be produced that can inform environmental policy. The collection of acoustic sensor data is a solved problem, the current challenge is the management and analysis of raw audio data to produce useful datasets for ecologists. This paper presents the applied research we use to analyze big acoustic datasets. Its core contribution is the presentation of practical large-scale acoustic data analysis methodologies. We describe details of the data workflows we use to provide both citizen scientists and researchers practical access to large volumes of ecoacoustic data. Finally, we propose a work in progress large-scale architecture for analysis driven by a hybrid cloud-and-local production-grade website.
Keywords :
Big Data; Web sites; acoustic devices; cloud computing; data analysis; environmental science computing; sensors; audio data; big acoustic sensor data analysis; data workflows; ecoacoustic data; ecologists; ecosystems; environmental monitoring; environmental policy; hybrid cloud-and-local production-grade Website; large-scale acoustic data analysis methodologies; large-scale architecture; large-scale ecologically relevant datasets; Acoustic sensors; Acoustics; Big data; Computer architecture; Optimization; Random access memory; acoustic sensing; bioacoustics; cloud infrastructure; data analysis; ecoacoustics; scalable analysis;
Conference_Titel :
Big Data and Cloud Computing (BdCloud), 2014 IEEE Fourth International Conference on
Conference_Location :
Sydney, NSW
DOI :
10.1109/BDCloud.2014.29