Publication

Abstract : Many of the indoor applications like navigation, indoor localization, object tracking require an indoor map. Indoor environments are dynamic in nature because of the objects present in it. To capture the essence of the indoor environment, it is essential to perform an object level mapping of an indoor space. This is because an object has the potential to alter the map of an indoor environment. Mapping a huge indoor environment could prove to be costly in terms of time with high infrastructure dependency. This compels us to find a simple solution in terms of cost, time and reliability to build an indoor map. The proposed solution should have minimal infrastructure dependence, so that it can be used in situations like disaster and rapid response scenarios, where the available infrastructure is minimal and time is of essence. We propose a Radio Frequency Identification(RFID) based approach which performs an object level mapping of the indoor environment using a portable RFID reader, RFID Ultra High Frequency(UHF) passive tags and inertial navigation sensors(INS). This approach identifies each object in the indoor environment using one or more passive tags. A novel algorithm has been developed which accurately maps the objects present in the indoor space. It is easily scalable to map huge indoor environments and can be applied without any intensive manual labor or expensive equipments. Our experiments show that this approach generates object level indoor maps with high accuracy.