Details

Autor(en) / Beteiligte

• Truskinger, A.
• Haofan Yang
• Wimmer, J.
• Jinglan Zhang
• Williamson, I.
• Roe, P.

Titel

Large Scale Participatory Acoustic Sensor Data Analysis: Tools and Reputation Models to Enhance Effectiveness

Ist Teil von

• 2011 IEEE Seventh International Conference on eScience, 2011, p.150-157

Ort / Verlag

IEEE

Erscheinungsjahr

2011

Quelle

IEEE Xplore

Beschreibungen/Notizen

• Acoustic sensors play an important role in augmenting the traditional biodiversity monitoring activities carried out by ecologists and conservation biologists. With this ability however comes the burden of analysing large volumes of complex acoustic data. Given the complexity of acoustic sensor data, fully automated analysis for a wide range of species is still a significant challenge. This research investigates the use of citizen scientists to analyse large volumes of environmental acoustic data in order to identify bird species. Specifically, it investigates ways in which the efficiency of a user can be improved through the use of species identification tools and the use of reputation models to predict the accuracy of users with unidentified skill levels. Initial experimental results are reported.