Journal of Korean Society of Water and Wastewater (상하수도학회지)

The Korean Society of Water and Wastewater (대한상하수도학회)
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Evaluation of Field Applicability for All-In-One Smart Water Meter to Measure both Water Quantity and Quality in Office Building Water Usage

사무실 사용용수의 수량/수질 동시 측정이 가능한 일체형 스마트 워터 미터의 현장 적용성 평가

  • Lee, Saeromi (Environmental and Plant Engineering Research Institute, Korea Institute of Civil Engineering and Building Technology) ;
  • Oh, Hyun Je (Environmental and Plant Engineering Research Institute, Korea Institute of Civil Engineering and Building Technology) ;
  • Joo, Jin Chul (Department of Civil & Environmental Engineering, Hanbat National University) ;
  • Ahn, Chang Hyuk (Environmental and Plant Engineering Research Institute, Korea Institute of Civil Engineering and Building Technology) ;
  • Park, Jae Roh (Environmental and Plant Engineering Research Institute, Korea Institute of Civil Engineering and Building Technology)
  • 이새로미 (한국건설기술연구원 환경.플랜트연구소) ;
  • 오현제 (한국건설기술연구원 환경.플랜트연구소) ;
  • 주진철 (한밭대학교 건설환경공학과) ;
  • 안창혁 (한국건설기술연구원 환경.플랜트연구소) ;
  • 박재로 (한국건설기술연구원 환경.플랜트연구소)
  • Received : 2016.08.30
  • Accepted : 2016.10.14
  • Published : 2016.12.23
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Abstract

Recently, advanced metering infrastructure (AMI) has been recognized as a core technology of smart water grid, and the relevant market is growing constantly. In this study, we developed all-in-one smart water meter of the AMI system, which was installed on the test-bed to verify both effectiveness and field applicability in office building water usage. Developed 15 mm-diameter smart water meter is a magneto-resistive digital meter, and measures flow rate and water quality parameters (temperature, conductivity) simultaneously. As a result of the water usage analysis by installing six smart water meters on various purposes in office building water usage, the water usage in shower room showed the highest values as the 1,870 L/day and 26.6 liter per capita day (LPCD). But, the water usage in laboratory was irregular, depending on the many variables. From the analysis of the water usage based on day of the week, the water usage on Monday showed the highest value, and tended to decrease toward the weekend. According to the PCA results and multivariate statistical approaches, the shower room (Group 3) and 2 floor man's restroom sink (Group 1-3) have been classified as a separate group, and the others did not show a significant difference in both water use and water quality aspects. From the analysis of water usage measured in this study, the leak or water quality accident did not occur. Consequently, all-in-one smart water meter developed in this study can measure flow rate and water quality parameters (temperature, conductivity) simultaneously with effective field applicability in office building water usage.

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References

  1. Brogueira, M. J., and Cabecadas, G. (2006). Identification of similar environmental areas in Tagus estuary by using multivariate analysis. Ecological Indicators, 6(3), 508-515. https://doi.org/10.1016/j.ecolind.2005.07.001
  2. Charef, A., Ghauch, A., Baussand, P., and Martin-Bouyer, M. (2000). Water quality monitoring using a smart sensing system, Measurement, 28(3), 219-224. https://doi.org/10.1016/S0263-2241(00)00015-4
  3. Gungor, V. C., Sahin, D., Kocak, T., Ergut, S., Buccella, C., Cecati, C., and Hancke, G. P. (2012). Smart grid and smart homes: key players and pilot projects, IEEE Industrial Electronics Magazine, 6(4), 18-34. https://doi.org/10.1109/MIE.2012.2207489
  4. IBM (2011). Smart Water Pilot Study Report(City of Dubuque, Iowa).
  5. ITU (2010). ICT as an Enabler for Smart Water Management.
  6. Jankovic-Nisic, B., Maksimovic, C., Butler, D., and Graham, N. J. (2004). Use of flow meters for managing water supply networks, Journal of water resources planning and management, 130(2), 171-179. https://doi.org/10.1061/(ASCE)0733-9496(2004)130:2(171)
  7. Joo, J. C., Ahn, H., Ahn, C. H., Ko, K. R., and Oh, H. J. (2012a). Field Application of Waterworks Automatic Meter Reading and Analysis of Household Water Use, Journal of Korean Society of Environmental Engineers, 34(10), 656-663. https://doi.org/10.4491/KSEE.2012.34.10.656
  8. Joo, J. C., Ahn, H., Ahn, C. H., Ko, K. R., and Oh, H. J. (2012b). Recent Developments and Field Application of Foreign Waterworks Automatic Meter Reading, Journal of Korean Society of Environmental Engineers, 34(12), 863-870. https://doi.org/10.4491/KSEE.2012.34.12.863
  9. Joo, J. C., Oh, H. J., Ahn, H., Ahn, C. H., Lee, S., and Ko, K. R. (2015). Field application of waterworks automated meter reading systems and analysis of household water consumption, Desalination and Water Treatment, 54(4-5), 1401-1409. https://doi.org/10.1080/19443994.2014.889609
  10. Kim, H., and Ayurzana, O. (2009). Improvement of data receive ratio in remote water meter system by upgrading sensor, International Journal of Control, Automation and Systems, 7(1), 145-150. https://doi.org/10.1007/s12555-009-0118-7
  11. Kim, J. H., Kim, H. S., Lee, D. J., and Kim, G. H. (2007). Analysis of water use characteristics by household demand monitoring. Journal of Korean Society of Environmental Engineers, 29(8), 864-869.
  12. Kim, H. S., Lee, D. J., Park, N. S., and Jung, K. S. (2008). Analysis on statistical characteristics of household water end-uses, Journal of the Korean Society of Civil Engineers, 28(5B), 603-614.
  13. Loeff, B. and Fox, J. (2010). Advanced metering infrastructure for water utilities: Market drivers, technology issues, deployment case, Pike Research LLC, Boulder, CO, USA.
  14. McCleskey, R. B., Nordstrom, D. K., and Ryan, J. N. (2012). Comparison of electrical conductivity calculation methods for natural waters, Limnol. Oceanogr.: Methods, 10, 952-967. https://doi.org/10.4319/lom.2012.10.952
  15. Park, S.Y. (2005). Standardization of waterworks AMR systems, MS Thesis, University of Seoul, Korea.
  16. Ramchurn, S. D., Vytelingum, P., Rogers, A., and Jennings, N. R. (2012). Putting the'smarts' into the smart grid: a grand challenge for artificial intelligence. Communications of the ACM, 55(4), 86-97. https://doi.org/10.1145/2133806.2133825
  17. Zpryme (2012). Smart Grid Insights.