An array of thick film pH sensor electrodes has been fused using two separate fuser designs: the feedforward neural network and Nadaraya-Watson kernel estimator. In both cases the fuser is based on empirical data rather than analytical sensor models. Complementary sensor responses have been obtained by fabricating sensors using different metal oxides. This approach provides some immunity to interference caused by the ionic composition of the solution being sensed. The Nadaraya-Watson estimator is shown to provide a useful alternative to the feedforward neural network for multisensor fusion where sensor distributions are unknown. Indicative test results are provided for the measurement of pH in printing ink. The results confirm that the fused results are more accurate than those obtained using the single best sensor, or simple fusion schemes such as averaging or majority voting.