Managing and Analysing Big Audio Data for Environmental Monitoring

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.

Ecoacoustics: A Quantitative Approach to Investigate the Ecological Role of Environmental Sounds

“…This poses problems for data reduction and analysis [130,131]. This fact forces us to concentrate on adapting methodologies to reduce the dimension of such big data and to improve their visualization [132].…”

Paradigm Shift in Big Data SuperComputing: DataFlow vs. ControlFlow

“…Future trends in the development of the DataFlow paradigm can be found in [20]. For comparison purposes, future trends in the ControlFlow paradigm can be found in [21]. …”

“…The viewpoint presented in this paper sheds more light on the recent development of the DataFlow computing concept (more details can be found in [20][21][22]). The DataFlow computing paradigm requires new ways of thinking and new ways of programming.…”

Unsupervised dictionary extraction of bird vocalisations and new tools on assessing and visualising bird activity

“…As technology advances, automatic recording units (ARUs) are becoming cheaper, smaller, more power efficient allowing for larger coverage of temporal and spatial scales. Analysis of this data can provide insights about the existence or not of species and their counts can be potentially associated with their threatened status and the general health of the habitat (Zhang et al, 2013). The collection of massive volumes of possibly disparate data requires their organisation, preservation and examination that due to its size requires to be automatic but under the supervision of specialised ornithologists.…”