An embedded Simplified Fuzzy ARTMAP implemented on a microcontroller for food classification.
In the present study, a portable system based on a microcontroller has been developed to classify different kinds of honeys. In order to do this classification, a Simplified Fuzzy ARTMAP network (SFA) implemented in a microcontroller has been used. Due to memory limits when working with microcontrollers, it is necessary to optimize the use of both program and data memory. Thus, a Graphical User Interface (GUI) for MATLAB® has been developed in order to optimize the necessary parameters to programme the SFA in a microcontroller. The measures have been carried out by potentiometric techniques using a multielectrode made of seven different metals. Next, the neural network has been trained on a PC by means of the GUI in Matlab using the data obtained in the experimental phase. The microcontroller has been programmed with the obtained parameters and then, new samples have been analysed using the portable system in order to test the model. Results are very promising, as an 87.5% recognition rate has been achieved in the training phase, which suggests that this kind of procedures can be successfully used not only for honey classification, but also for many other kinds of food.
Centro de Reconocimiento Molecular y Desarrollo Tecnológico, Unidad Mixta UPV-UV, Universitat Politècnica de València, València, Spain. egarciab@eln.upv.es
Eduardo
E
Garcia-Breijo
Jose
J
Garrigues
Luis Gil
LG
Sanchez
Nicolas
N
Laguarda-Miro
D000465:Algorithms; D003196:Computer Graphics; D003217:Conductometry / Q000295:instrumentation*; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005504:Food Analysis / Q000295:instrumentation*; D017143:Fuzzy Logic; D006722:Honey / Q000032:analysis*; D008838:Microcomputers; D008904:Miniaturization; D010363:Pattern Recognition, Automated / Q000379:methods; D014584:User-Computer Interface