Abstract Received Signal Strength (RSS) based location systems are potential candidates to enable indoor location aware services due to pervasively available wireless local area networks and hand held devices. Intrinsically RSS based positioning is a multi-class pattern recognition problem. Previous researches have shown that Visibility Matrix based approach of modular classi ers improves location accuracy but costs longer periods of training and testing in development life cycle. We present a Context-aware Fuzzy ArtMap neural network that provides competitive location accuracy in comparison with modular approach while leveraging online and incremental learning capabilities to location system development life cycle.