Location has become an essential part of the next-generation Internet of Things systems.This paper proposes a multi-sensor-based 3D indoor localization approach.Compared with the existing 3D localization methods, this paper presents a wireless Rinse Nozzle received signal strength (RSS)-profile-based floor-detection approach to enhance RSS-based floor detection.The profile-based floor detection is further integrated with the barometer data to gain more reliable estimations of the height and the barometer bias.Furthermore, the data from inertial sensors, magnetometers, and a barometer are integrated with the RSS data through an extend Kalman filter.
The proposed multi-sensor integration algorithm provided more robust and smoother Wheelchair floor detection and 3D localization solutions than the existing methods.