CyberInfrastructure for the Analysis of Ecological Acoustic Sensor Data: A Use Case Study in Grid Deployment

Butler, Randy; Servilla, Mark; Gage, Stuart H.; Basney, Jim; Welch, Von; Baker, Bill; Fleury, Terry; Duda, Patrick; Gehrig, David; Bletzinger, Michael; Jiang, Tao; Freemon, D. Michael

doi:10.1109/clade.2006.1652051

Cited by 8 publications

(5 citation statements)

References 10 publications

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“…Multiple sampling points might be set up semipermanently with wireless transmission of signals or alerts (Butler et al 2006) to reduce the labor involved in inserting nails and attaching acoustic sensors. The acoustic instruments could be made more portable and robust to accommodate the high temperatures and humidities and the high densities of plants in sugarcane Þeld environments.…”

Section: Discussionmentioning

confidence: 99%

Acoustic Detection of Melolonthine Larvae in Australian Sugarcane

Mankin¹,

Samson²,

Chandler³

2009

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Decision support systems have been developed for risk analysis and management of root-feeding white grubs (Coleoptera: Scarabaeidae: Melolonthinae) in Queensland, Australia, sugarcane (Saccharum spp.), based partly on manual inspection of soil samples. Acoustic technology was considered as a potential alternative to this laborious procedure. Field surveys were conducted to detect the major pests Dermolepida albohirtum (Waterhouse) near Mackay, and Antitrogus parvulus Britton near Bundaberg. Computer analyses were developed to identify distinctive scrapes and other sounds produced by D. albohirtum and Antitrogus species and to distinguish them from sounds of nondamaging white grubs (Rutelinae, Dynastinae), as well as from extraneous, wind-induced tapping signals. Procedures were considered for incorporating acoustic methods into surveys and sequential sampling plans. Digging up and inspecting sugarcane root systems requires 10-12 min per sample, but acoustic assessments can be obtained in 3-5 min, so labor and time could be reduced by beginning the surveys with acoustic sampling. In a typical survey conducted in a field with low population densities, sampling might terminate quickly after five negative acoustic samples, establishing a desired precision level of 0.25 but avoiding the effort of excavating and inspecting empty samples. With a high population density, sampling might terminate also if signals were detected in five samples, in which case it would be beneficial to excavate the samples and count the white grubs. In intermediate populations, it might be necessary to collect up to 20 samples to achieve desired precision, and acoustic methods could help determine which samples would be best to excavate.

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Section: Discussionmentioning

confidence: 99%

Acoustic Detection of Melolonthine Larvae in Australian Sugarcane

Mankin¹,

Samson²,

Chandler³

2009

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“…It is the job of the back-end, when data are finally uploaded, to do any needed analysis such as counting bird populations, inferring social communication patterns, or recognizing that two files, refer to the same vocalization. A description of such a back-end appears in Butler et al [2007]. This article is concerned with the design of the acoustic sensing system that feeds such a back-end and tolerates long periods of disconnected operation.…”

Section: System Designmentioning

confidence: 99%

“…A significant literature has addressed this problem adequately. Software toolkits (e.g., Butler et al [2007]) exist that implement acoustic recognition algorithms. Not to replicate the existing effort but leverage it, we focused on the acoustic collection front-end.…”

Section: Data Retrieval and Analysismentioning

confidence: 99%

Design, implementation, and evaluation of EnviroMic

Luo

Cao

Huang

et al. 2009

ACM Trans. Sen. Netw.

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This article presents the design, implementation, and evaluation of EnviroMic, a low-cost experimental prototype of a novel distributed acoustic monitoring, storage, and trace retrieval system designed for disconnected operation. Our intended use of acoustic monitoring is to study animal populations in the wild. Since a permanent connection to the outside world is not assumed and due to the relatively large size of audio traces, the system must optimally exploit available resources such as energy and network storage capacity. Towards that end, we design, prototype, and evaluate distributed algorithms for coordinating acoustic recording tasks, reducing redundancy of data stored by nearby sensors, filtering out silence, and balancing storage utilization in the network. For experimentation purposes, we implement EnviroMic on a TinyOS-based platform and systematically evaluate its performance through both indoor testbed experiments and an outdoor deployment. Results demonstrate up to a four-fold improvement in effective storage capacity of the network compared to uncoordinated recording.

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“…Zones of air temperature could be displayed on top of a view of a natural mountain-side landscape to see how ecozones lined up with field temperature data. Another example is the Biophony Grid Portal that manages acoustic data from numerous field-deployed microphones (Butler et al 2006). Combining recorded bird songs from these microphones, a database of known bird acoustic signatures, and distributed GIS coverages allows researchers to identify a probability of presence for bird species.…”

Section: Ecoinformaticsmentioning

confidence: 99%

Beyond data management: how ecoinformatics can benefit environmental monitoring programs

Hale

Hollister

2008

Environ Monit Assess

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We review ways in which the new discipline of ecoinformatics is changing how environmental monitoring data are managed, synthesized, and analyzed. Rapid improvements in information technology and strong interest in biodiversity and sustainable ecosystems are driving a vigorous phase of development in ecological databases. Emerging data standards and protocols enable these data to be shared in ways that have previously been difficult. We use the U.S. Environmental Protection Agency's National Coastal Assessment (NCA) as an example. The NCA has collected biological, chemical, and physical data from thousands of stations around the U.S. coasts since 1990. NCA data that were collected primarily to assess the ecological condition of the U.S. coasts can be used in innovative ways, such as biogeographical studies to analyze species invasions. NCA application of ecoinformatics tools leads to new possibilities for integrating the hundreds of thousands of NCA species records with other databases to address broad-scale and long-term questions such as environmental impacts, global climate change, and species invasions.

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CyberInfrastructure for the Analysis of Ecological Acoustic Sensor Data: A Use Case Study in Grid Deployment

Cited by 8 publications

References 10 publications

Acoustic Detection of Melolonthine Larvae in Australian Sugarcane

Acoustic Detection of Melolonthine Larvae in Australian Sugarcane

Design, implementation, and evaluation of EnviroMic

Beyond data management: how ecoinformatics can benefit environmental monitoring programs

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