Citation
David Jun, Long Le, Douglas L. Jones. "Cheap Noisy Sensors Can Improve Activity Monitoring Under Stringent Energy Constraints". IEEE Global Conference on Signal and Information Processing (GlobalSIP), December, 2013.

Abstract
This paper proposes a low-power acoustic sensor built using off-the-shelf components. To reduce energy consumption, the ADC and the microphone's signal-conditioning circuit are replaced by a low-power analog comparator with adjustable thresholds. Although the SNR of the proposed sensor is reduced, we demonstrate how recent advancements in adaptive sensor scheduling can utilize this sensing modality at the right times to deliver high estimation performance in the presence of extremely stringent device-energy constraints. In a long-term acoustic wildlife monitoring application, energy consumption is reduced by a factor of up to 15x over the scheduling policy that does not utilize the proposed sensor. Furthermore, when device energy is extremely scarce, optimal sensor management can reduce error rate from nearly 40% to 8%.

Electronic downloads

• http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6736983

• HTML

  David Jun, Long Le, Douglas L. Jones. <a
  href="http://www.terraswarm.org/pubs/150.html"
  >Cheap Noisy Sensors Can Improve Activity Monitoring
  Under Stringent Energy Constraints</a>, IEEE Global
  Conference on Signal and Information Processing (GlobalSIP),
  December, 2013.

• Plain text

  David Jun, Long Le, Douglas L. Jones. "Cheap Noisy
  Sensors Can Improve Activity Monitoring Under Stringent
  Energy Constraints". IEEE Global Conference on Signal
  and Information Processing (GlobalSIP), December, 2013.

• BibTeX

  @inproceedings{JunLeJones13_CheapNoisySensorsCanImproveActivityMonitoringUnderStringent,
      author = {David Jun and Long Le and Douglas L. Jones},
      title = {Cheap Noisy Sensors Can Improve Activity
                Monitoring Under Stringent Energy Constraints},
      booktitle = {IEEE Global Conference on Signal and Information
                Processing (GlobalSIP)},
      month = {December},
      year = {2013},
      abstract = {This paper proposes a low-power acoustic sensor
                built using off-the-shelf components. To reduce
                energy consumption, the ADC and the microphone's
                signal-conditioning circuit are replaced by a
                low-power analog comparator with adjustable
                thresholds. Although the SNR of the proposed
                sensor is reduced, we demonstrate how recent
                advancements in adaptive sensor scheduling can
                utilize this sensing modality at the right times
                to deliver high estimation performance in the
                presence of extremely stringent device-energy
                constraints. In a long-term acoustic wildlife
                monitoring application, energy consumption is
                reduced by a factor of up to 15x over the
                scheduling policy that does not utilize the
                proposed sensor. Furthermore, when device energy
                is extremely scarce, optimal sensor management can
                reduce error rate from nearly 40% to 8%. },
      URL = {http://terraswarm.org/pubs/150.html}
  }
  

Posted by Mila MacBain on 18 Oct 2013.