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Remotely Accessible Instrumented Monitoring of Global Development Programs: Technology Development and Validation

Author

Listed:
  • Evan A. Thomas

    (Portland State University, Mechanical and Materials Engineering Department, 1930 SW 4th Ave, Suite 400, Portland, OR 97201, USA)

  • Zdenek Zumr

    (Portland State University, Mechanical and Materials Engineering Department, 1930 SW 4th Ave, Suite 400, Portland, OR 97201, USA)

  • Jodi Graf

    (Portland State University, Mechanical and Materials Engineering Department, 1930 SW 4th Ave, Suite 400, Portland, OR 97201, USA)

  • Carson A. Wick

    (Georgia Institute of Technology, School of Electrical and Computer Engineering, 777 Atlantic Drive Northwest, Atlanta, GA 30332, USA)

  • James H. McCellan

    (Georgia Institute of Technology, School of Electrical and Computer Engineering, 777 Atlantic Drive Northwest, Atlanta, GA 30332, USA)

  • Zachary Imam

    (Georgia Institute of Technology, School of Electrical and Computer Engineering, 777 Atlantic Drive Northwest, Atlanta, GA 30332, USA)

  • Christina Barstow

    (University of Colorado at Boulder, Civil and Environmental Engineering Department, UCB 401, Boulder, CO 80301, USA)

  • Kelly Spiller

    (Stevens Water Monitoring Inc., 12067 NE Glenn Widing Dr. #106, Portland, OR 97220, USA)

  • Michael Fleming

    (Stevens Water Monitoring Inc., 12067 NE Glenn Widing Dr. #106, Portland, OR 97220, USA)

Abstract

Many global development agencies self-report their project outcomes, often relying on subjective data that is collected sporadically and communicated months later. These reports often highlight successes and downplay challenges. Instrumented monitoring via distributed data collection platforms may provide crucial evidence to help inform the sector and public on the effectiveness of aid, and the on-going challenges. This paper presents the process of designing and validating an integrated sensor platform with cellular-to-internet reporting purposely targeted at global development programs. The integrated hardware platform has been applied to water, sanitation, energy and infrastructure interventions and validated through laboratory calibration and field observations. Presented here are two examples: a water pump and a household water filter, wherein field observations agreed with the data algorithm with a linear fit slope of between 0.91 and 1, and an r-squared of between 0.36 and 0.39, indicating a wide confidence interval but with low overall error ( i.e. , less than 0.5% in the case of structured field observations of water volume added to a household water filter) and few false negatives or false positives.

Suggested Citation

  • Evan A. Thomas & Zdenek Zumr & Jodi Graf & Carson A. Wick & James H. McCellan & Zachary Imam & Christina Barstow & Kelly Spiller & Michael Fleming, 2013. "Remotely Accessible Instrumented Monitoring of Global Development Programs: Technology Development and Validation," Sustainability, MDPI, vol. 5(8), pages 1-14, August.
  • Handle: RePEc:gam:jsusta:v:5:y:2013:i:8:p:3288-3301:d:27714
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    References listed on IDEAS

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    1. Kremer, Michael R. & Karlan, D. S. & Hornbeck, Richard A. & Gine, X. & Duflo, E. & Pariente, W. & Null, C. & Miguel, E. & Devoto, F. & Crepon, B. & Banerjee, A. & Zwane, A. P. & Zinman, J. & Van Dusen, 2011. "Being Surveyed Can Change Later Behavior and Related Parameter Estimates," Scholarly Articles 11339433, Harvard University Department of Economics.
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    1. Nick Turman-Bryant & Corey Nagel & Lauren Stover & Christian Muragijimana & Evan A. Thomas, 2019. "Improved Drought Resilience Through Continuous Water Service Monitoring and Specialized Institutions—A Longitudinal Analysis of Water Service Delivery Across Motorized Boreholes in Northern Kenya," Sustainability, MDPI, vol. 11(11), pages 1-16, May.

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