Cost-effective smart irrigation controller using automatic weather stations

被引：3
作者：
Hema N. [1 ]
Kant K. [2 ]
机构：
[1] Department of Computer Science Engineering and Information Technology, Jaypee Institute of Information Technology, Sector-62, Noida
[2] Department of Computer Science Engineering and Information Technology, Jaypee Institute of Information Technology, Sector-128, Noida
来源：
International Journal of Hydrology Science and Technology | 2019年 / 9卷 / 01期
关键词：
automatic weather station; AWS; real-time climatic data; reconstruction; smart irrigation controllers; validation;
D O I：
10.1504/IJHST.2019.096795
中图分类号：
学科分类号：
摘要：
Water has become increasingly scarce and valuable resource due to the increasing population and misuse of the same. Agriculture is the largest sector using water with low-efficiency and low-cost. Traditional irrigation methodology uses a qualitative approach to schedule irrigation that does not measure actual environmental condition whereas the quantitative approach requires additional setup for climate measurement. Low cost innovative water-saving technology is the need of the hour. The presented work proposes the cost-effective smart irrigation controller using automatic weather stations(AWS). The proposed smart controller makes real-time irrigation decision by gathering climatic data from nearby AWS. AWS's data are available on an hourly basis from Indian meteorological department. The primary challenge in designing irrigation controller is to acquire real-time data, to validate and to reconstruct the missing data. These problems are addressed in the presented paper. Evapotranspiration computed from nearby AWS are comparable with evapotranspiration provided by Indian Agricultural Research Institute. © 2019 Inderscience Enterprises Ltd.
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页码：1 / 27
页数：26
相关论文
共 38 条
  • [31] Shiklomanov I.A., Rodda J.C., The Earth and Its Physical Features, World Water Resources at the Beginning of the Twenty-First Century, pp. 1-18, (2004)
  • [32] Thapar V., Agnihotri G., Sethi V.K., Estimation of hourly temperature at a site and its impact on energy yield of a PV module, International Journal of Green Energy, 9, 6, pp. 553-572, (2012)
  • [33] Tang Q., Wood A.W., Lettenmaier D.P., Real-time precipitation estimation based on index station percentiles, Journal of Hydrometeorology, 10, 1, pp. 266-277, (2009)
  • [34] Tobler W.R., A computer movie simulating urban growth in the Detroit region, Economic Geography, 46, pp. 234-240, (1970)
  • [35] Trajkovic S., Estimating hourly reference evapotranspiration from limited weather data by sequentially adaptive RBF network, Facta Universitatis-Series: Architecture and Civil Engineering, 9, 3, pp. 473-480, (2011)
  • [36] Wan J., Yang Y.C.E., Lin Y.F., Wang J., Groundwater resource planning to preserve streamflow: Where environmental amenity meets economic welfare loss, Journal of Water Resources Planning and Management, 139, 4, pp. 440-448, (2012)
  • [37] Waichler S.R., Wigmosta M.S., Development of hourly meteorological values from daily data and significance to hydrological modeling at HJ Andrews experimental forest, Journal of Hydrometeorology, 4, 2, pp. 251-263, (2003)
  • [38] Yeh H.C., Chen Y.C., Wei C., Chen R.H., Entropy and kriging approach to rainfall network design, Paddy and Water Environment, 9, 3, pp. 343-355, (2011)
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