A Dynamic Indoor Location Model for Smartphones Based on Magnetic Field: A Preliminary Approach

Due to an increase interest for providing services based on user location, several indoor location approaches based on mobile devices have been proposed recently. This paper focuses on the use of a novel crowdsourcing approach for indoor location of a mobile device that uses social collaboration to improve the accuracy and magnetic field signal as information source using feature extraction and a deterministic method that allows us to include information from new users that improves the fitness of the model. Four phases were included in the methodology: Raw data collection, Data pre-process, Feature extraction and Social collaboration. An experiment was succesfully carried out to test the proposed methodology. On the whole, good results were obtained on computational cost, recalculation time and accuracy improvement.