A Subarea Mapping Approach for Indoor Localization

Location information can be useful to construct a profile of a person’s activities of daily living. This paper proposes an approach with the aim of improving the accuracy and robustness of a location recognition approach based on RFID technology. A method was introduced for the optimal deployment of an RFID reader network, which aims to minimize the hardware cost whilst achieving high localization accuracy. A functional subarea mapping approach was proposed based on both a coarse-grained and a fine-grained method. Experimental results indicated that the coarse-grained mapping provided a higher overall accuracy of location detection. The average subarea location accuracy achieved based on coarse-grained and fine-grained data was 85.4% and 68.7%, respectively. Nevertheless it was found that the fine-grained mapping approach was capable of providing more information in relation to the details of the functional subareas. This implies that we need to balance the requirements between the size of the subareas and the location accuracy.