A fuzzy technique for food- and water quality assessment with an electronic tongue

Authors:
Boyko Iliev;Malin Lindquist;Linn Robertsson;Peter Wide
Affiliations:
Örebro University, Center for Applied Autonomous Sensor Systems, AASS, SE-701 82 Örebro, Sweden;Örebro University, Center for Applied Autonomous Sensor Systems, AASS, SE-701 82 Örebro, Sweden;Örebro University, Center for Applied Autonomous Sensor Systems, AASS, SE-701 82 Örebro, Sweden;Örebro University, Center for Applied Autonomous Sensor Systems, AASS, SE-701 82 Örebro, Sweden
Venue:
Fuzzy Sets and Systems
Year:
2006

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Abstract

The problem of food- and water quality assessment is important for many practical applications, such as food industry and environmental monitoring. In this article we present a method for fast online quality assessment based on electronic tongue measurements. The idea is implemented in two steps. First we apply a fuzzy clustering technique to obtain prototypes corresponding to good and bad quality from a set of training data. During the second, online step we evaluate the membership of the current measurement to each cluster and make a decision about its quality. The result is presented to the user in a simple and understandable way, similar to the concept of traffic light signals. Namely, good quality is indicated with by a green light, bad quality with a red one, and a yellow light is a warning signal. The approach is demonstrated in two case studies: quality assessment of drinking water and baby food.