2015
DOI: 10.1109/jsen.2014.2347996
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Nitrate and Sulfate Estimations in Water Sources Using a Planar Electromagnetic Sensor Array and Artificial Neural Network Method

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Cited by 36 publications
(16 citation statements)
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“…Optical sensing is based on reflectance spectroscopy to measure the reflection and absorption by these macrosimulation [104,110,113]. To detect nitrate and sulfate concentration in natural water resources, a sensing method using planar electromagnetic sensors has been developed in [121]. This method is used to sense nitrate and sulfate levels by correlating the impedance of the sensor array with the concentration of these pollutants.…”
Section: Electrical Conductivity and Topography Surveysmentioning
confidence: 99%
See 1 more Smart Citation
“…Optical sensing is based on reflectance spectroscopy to measure the reflection and absorption by these macrosimulation [104,110,113]. To detect nitrate and sulfate concentration in natural water resources, a sensing method using planar electromagnetic sensors has been developed in [121]. This method is used to sense nitrate and sulfate levels by correlating the impedance of the sensor array with the concentration of these pollutants.…”
Section: Electrical Conductivity and Topography Surveysmentioning
confidence: 99%
“…This method is used to sense nitrate and sulfate levels by correlating the impedance of the sensor array with the concentration of these pollutants. It has been shown that sensor impedance decreases with increase in concentration of these chemicals [121]. Electrochemical, VIS-NIRS spectroscopy, and ATR spectroscopy are the major soil macro-nutrients sensing approaches.…”
Section: Electrical Conductivity and Topography Surveysmentioning
confidence: 99%
“…It is reported that PESA has the ability to detect and estimate nitrate in water samples [3,6,7,19,48,49,76].…”
Section: Optimum Valuementioning
confidence: 99%
“…Lastly, remote sensing systems can exploit satellite imagery for large-scale environmental monitoring of planetary phenomena, such as pollution [9], [43], weather forecasts [8], seismic activity [44]. In environmental applications, CI techniques are often used to detect the phenomenon of interest by fusing data obtained from heterogeneous environmental sensors (e.g, temperature, humidity, chemical concentration, vibrations) [19], [39], [41], [42], by classifying the distinctive features extracted from onedimensional or two-dimensional signals [8], [9], [35], [43], [44], and by performing forecasts based on time series analysis [7], [38].…”
Section: Monitoringmentioning
confidence: 99%