Design, implementation, and evaluation of EnviroMic: A storage-centric audio sensor network

  • Authors:

  • Liqian Luo;Qing Cao;Chengdu Huang;Lili Wang;Tarek F. Abdelzaher;John A. Stankovic;Michael Ward

  • Affiliations:

  • Microsoft Research, Redmond, WA;University of Illinois at Urbana-Champaign;University of Illinois at Urbana-Champaign;University of Illinois at Urbana-Champaign;University of Illinois at Urbana-Champaign;University of Virginia;University of Illinois at Urbana-Champaign

  • Venue:
  • ACM Transactions on Sensor Networks (TOSN)
  • Year:
  • 2009

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Abstract

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.