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Pourshamsaei, H
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Authors
Pourshamsaei, H
Nobakhti, A
Pourshamsaei, H
Nobakhti, A
Topics
Wireless Sensor Networks
Big Data, Data Mining and Deep Learning
Type
Oral
Year
2018
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1. A Comparative Study of Field-Wide Estimation of Soil Moisture Using Compressive Sensing

In precision agriculture, monitoring of soil moisture plays an essential role in correct decision making. In practice, regular mesh installation, or large random deployment of moisture sensors over a large field is not possible due to cost and maintenance prohibitions. Consequently, direct measurement of moisture is possible at only a few points in the field. A value for the moisture may then be estimated for the remaining areas using a variety of algorithms. It is shown that although... H. Pourshamsaei, A. Nobakhti

2. Optimal Sensor Placement for Field-Wide Estimation of Soil Moisture

Soil moisture is one of the most important parameters in precision agriculture. While techniques such as remote sensing seems appropriate for moisture monitoring over large areas, they generally do not offer sufficiently fine resolution for precision work, and there are time restrictions on when the data is available. Moreover, while it is possible to get high resolution-on demand data, but the costs are often prohibitive for most developing countries. Direct ground level measurement... H. Pourshamsaei, A. Nobakhti