Title of article :
Artificial neural network onto eight bit microcontroller for Secchi depth calculation
Author/Authors :
Ibلٌez Civera، نويسنده , , Javier and Garcia Breijo، نويسنده , , Eduardo and Laguarda Mirَ، نويسنده , , Nicolلs and Gil Sلnchez، نويسنده , , Luis and Garrigues Baixauli، نويسنده , , José and Romero Gil، نويسنده , , Inmaculada and Masot Peris، نويسنده , , Rafael and Alcaٌiz Fillol، نويسنده , , Miguel، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2011
Abstract :
In this paper we present a model to predict Secchi depth in water bodies by means of an artificial neural network application onto eight bit microcontroller. Water turbidity data were collected by both a Secchi disk and a new patented device (named LUZEX) that uses commercial photodiodes with not monochromatic sensitive band as a basis to perform “in situ” measurements for sunlight extinction coefficients. In order to have a wide range of turbidity data three different water bodies were selected to do the measurements. The developed neural network model is able to relate well the data obtained by these methods and the obtained value for regression coefficient (R) is 0.998.
depth measure is a reference method to determine turbidity in continental and coastal water bodies, especially in the Mediterranean Sea region, but sometimes there are particular cases that makes difficult the use of the Secchi disk (e.g. shallow water bodies), the authors propose LUZEX as a substitute for Secchi disk when it is difficult or impossible to use.
Keywords :
Artificial neural network , Secchi disk , Secchi depth , Water quality , turbidity , Sunlight extinction coefficient
Journal title :
Sensors and Actuators B: Chemical
Journal title :
Sensors and Actuators B: Chemical