DocumentCode :
3461450
Title :
Managing and Analysing Big Audio Data for Environmental Monitoring
Author :
Jinglan Zhang ; Kai Huang ; Cottman-Fields, Mark ; Truskinger, Anthony ; Roe, Paul ; Shufei Duan ; Xueyan Dong ; Towsey, Michael ; Wimmer, Jason
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Queensland Univ. of Technol., Brisbane, QLD, Australia
fYear :
2013
fDate :
3-5 Dec. 2013
Firstpage :
997
Lastpage :
1004
Abstract :
Environmental monitoring is becoming critical as human activity and climate change place greater pressures on biodiversity, leading to an increasing need for data to make informed decisions. Acoustic sensors can help collect data across large areas for extended periods making them attractive in environmental monitoring. However, managing and analysing large volumes of environmental acoustic data is a great challenge and is consequently hindering the effective utilization of the big dataset collected. This paper presents an overview of our current techniques for collecting, storing and analysing large volumes of acoustic data efficiently, accurately, and cost-effectively.
Keywords :
data analysis; environmental monitoring (geophysics); geophysics computing; acoustic sensors; big audio data analysis; big audio data management; biodiversity; climate change; environmental monitoring; human activity; Acoustic sensors; Acoustics; Birds; Environmental monitoring; acoustic data analysis; acoustic sensing; big data management and processing; citizen science; eScience; environmental monitoring; visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Science and Engineering (CSE), 2013 IEEE 16th International Conference on
Conference_Location :
Sydney, NSW
Type :
conf
DOI :
10.1109/CSE.2013.146
Filename :
6755327
Link To Document :
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