Indoor Localization with a Crowdsourcing based Fingerprints Collecting (Joint with Prof. Hui Yu)
Each wireless router broadcasts a signal that is received by devices in the area. These devices have the capability to measure the strength of the signal. This strength is converted to a number, known as received signal strength indicator (RSSI). Wi-Fi devices, such as smartphones, typically perform this conversion automatically in order to provide signal strength information to applications running on it.
WITH the wide deployment of wireless local area networks (WLAN) and mobile wireless devices, indoor location-based services (LBSs) can be made possible without additional cost for infrastructure. Using RSSI to record the environments and developing locate algorithms to make the basic system work. The following is our diagram for the basic system.
(2) Using Inertial Measurement Unit(IMU)
The pedestrian localization and tracking system developed nowadays mainly based on a micro-machined electromechanical systems (MEMS) inertial measurement unit (IMU). For most smart terminals (especially smart phones), accelerometer, gyroscope, magnetometer and some more sensors are included as default. We use them to improve performance of our basic system.
In particular the movement of a pedestrian is naturally constrained by walls, floors and ceilings that are present in nearly all indoor environments. By using such constraints it may be possible to track a pedestrian indefinitely in an indoor environment, with no degradation in accuracy and without the need to install any fixed infrastructure.
Using Crowdsourcing and Cloud Computing
Crowdsourcing and Cloud Computing also make it possible to deploy our location systems with high performance and low costs. With system deployed on cloud, many algorithms can be tested and integrated with each other to make the system work better. The future location algorithms and applications, services are meant to be on clouds.