Indoor Localization System Based on Bluetooth Low Energy With Inertial Sensor Assist for Resource Constrained Environments

Indoor localization refers to locating people or objects inside indoor areas where conventional localization approaches fail to perform. This paper presents a novel methodology for indoor localization with Bluetooth Low Energy and inertial sensors for resource constrained devices. Authors approach uses a Kalman filter-based localization method that is running on the cloud, compared to previous work that utilized the end node for processing. The performance of the proposed system depends on factors such as the accuracy of inertial sensors, data broadcast frequency, and the quality of indoor infrastructure. Results show that our approach for indoor localization is well suited for devices with limited processing power.