An Expert System for Full pH Range Prediction Using a Disposable Optical Sensor Array

The design of optical sensor arrays encompasses tasks such as the acquisition of sensor optical parameters, as for example color features, and the calibration of a multivariate method to model the array global behavior. Different techniques have been used to model the sensor array responses, such as multivariate regression or neural networks, although they show certain limitations. The former methods require either high amount of computer memory or speed so therefore they are not suitable for implementation in portable electronic devices with low resources, while the later is a black box whose operation cannot be easily modeled and explained for industrial development validation. This work addresses these problems and proposes an expert system to overcome the previous drawbacks. The approach makes an accurate pH prediction, and it comprises a balance between memory and microprocessor speed for its integration within embedded systems with low memory and chip resources. In addition, it is also able to provide a high expressive explanation of why such prediction was made, so that the industrial validation is easier than using other proposals such as neural networks.