A method of assessing concentration of at least one analyte ion in a liquid, the method including: Contacting the liquid with a plurality of electrodes, each of which is configured to generate a signal in response to sensing a selected ion in the liquid; and Receiving the signal from each of the electrodes, characterized in that the method includes: processing the signal from each of the electrodes using a neural network algorithm residing on a processor that has been trained to calculate ion interference between the selected ion and other ions in the liquid sensed at one of the electrodes and electrode interference between ones of the electrodes sensing a same selected ion based on a result of a comparison of training data indicative of a known ionic concentration applied to the neural network algorithm and the known ionic concentration; processing the signal from one or more of the electrodes with a genetic Independent Component Analysis ( geneticICA) and providing the processed signal as input data for the neural network algorithm; compensating for said ion interference and said electrode interference; and assessing the concentration of the at least one analyte ion in the liquid on the basis of a compensated output from the neural network algorithm. Contacting the liquid with a plurality of electrodes, each of which is configured to generate a signal in response to sensing a selected ion in the liquid; and Receiving the signal from each of the electrodes, characterized in that the method includes: processing the signal from each of the electrodes using a neural network algorithm residing on a processor that has been trained to calculate ion interference between the selected ion and other ions in the liquid sensed at one of the electrodes and electrode interference between ones of the electrodes sensing a same selected ion based on a result of a comparison of training data indicative of a known ionic concentration applied to the neural network algorithm and the known ionic concentration; processing the signal from one or more of the electrodes with a genetic Independent Component Analysis ( geneticICA) and providing the processed signal as input data for the neural network algorithm; compensating for said ion interference and said electrode interference; and assessing the concentration of the at least one analyte ion in the liquid on the basis of a compensated output from the neural network algorithm. processing the signal from each of the electrodes using a neural network algorithm residing on a processor that has been trained to calculate ion interference between the selected ion and other ions in the liquid sensed at one of the electrodes and electrode interference between ones of the electrodes sensing a same selected ion based on a result of a comparison of training data indicative of a known ionic concentration applied to the neural network algorithm and the known ionic concentration; processing the signal from one or more of the electrodes with a genetic Independent Component Analysis ( geneticICA) and providing the processed signal as input data for the neural network algorithm; compensating for said ion interference and said electrode interference; and assessing the concentration of the at least one analyte ion in the liquid on the basis of a compensated output from the neural network algorithm.