A macroscope in the redwoods

  • Authors:

  • Gilman Tolle;Joseph Polastre;Robert Szewczyk;David Culler;Neil Turner;Kevin Tu;Stephen Burgess;Todd Dawson;Phil Buonadonna;David Gay;Wei Hong

  • Affiliations:

  • University of California, Berkeley, Berkeley, CA;University of California, Berkeley, Berkeley, CA;University of California, Berkeley, Berkeley, CA;University of California, Berkeley, Berkeley, CA;University of California, Berkeley, Berkeley, CA;University of California, Berkeley, Berkeley, CA;University of California, Berkeley, Berkeley, CA;University of California, Berkeley, Berkeley, CA;Intel Research Berkeley, Berkeley, CA;Intel Research Berkeley, Berkeley, CA;Intel Research Berkeley, Berkeley, CA

  • Venue:
  • Proceedings of the 3rd international conference on Embedded networked sensor systems
  • Year:
  • 2005

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Abstract

The wireless sensor network "macroscope" offers the potential to advance science by enabling dense temporal and spatial monitoring of large physical volumes. This paper presents a case study of a wireless sensor network that recorded 44 days in the life of a 70-meter tall redwood tree, at a density of every 5 minutes in time and every 2 meters in space. Each node measured air temperature, relative humidity, and photosynthetically active solar radiation. The network captured a detailed picture of the complex spatial variation and temporal dynamics of the microclimate surrounding a coastal redwood tree. This paper describes the deployed network and then employs a multi-dimensional analysis methodology to reveal trends and gradients in this large and previously-unobtainable dataset. An analysis of system performance data is then performed, suggesting lessons for future deployments.