There has been increasing interest in using automated bioacoustics analysis to monitor the environment. This involves using computational approaches to identify animals and other environmental phenomena from the sounds that they generate. The volume of data being recorded for bioacoustics analyses is increasing, as the scale of environmental surveys is increasing. This presents significant computational demands to perform analyses. These large-scale analyses cannot be performed at feasible speeds using traditional computing approaches. This research proposes AcoustiCloud: a system framework which represents bioacoustics processes as workflows and executes these across a Cloud-based system. It enables fast and efficient bioacoustics analysis for a variety of scenarios. The proposed system considers characteristics specific to bioacoustics processes resulting in fast execution times and high scalability. An implemented prototype is found to execute a bioacoustics workflow with 10 min of audio over 10 times faster than Pegasus, a widely used Workflow Management System.

Item Type:	Refereed Article
Keywords:	bioacoustics, system architecture, distributed computing, cloud computing, workflow management, big data
Research Division:	Information and Computing Sciences
Research Group:	Distributed computing and systems software
Research Field:	Distributed systems and algorithms
Objective Division:	Environmental Management
Objective Group:	Terrestrial systems and management
Objective Field:	Terrestrial biodiversity
UTAS Author:	Brown, AS (Mr Alexander Brown)
UTAS Author:	Garg, S (Dr Saurabh Garg)
UTAS Author:	Montgomery, J (Dr James Montgomery)
ID Code:	139656
Year Published:	2020
Web of Science® Times Cited:	2
Deposited By:	Information and Communication Technology
Deposited On:	2020-06-24
Last Modified:	2022-08-29
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