Multi-Sensor Based IoT Indoor Localization

A typical indoor localization system relies on the availability of infrastructure such as Wi-Fi Access Points, blue-tooth beacons or antenna arrays. This increases the overall system cost and it may not be feasible for deployment in real environments such as shopping malls. A practical indoor localization system should be one that can function with mini-mum existing infrastructure. The proposed system in this paper leverages on the embedded sensors in off-the-shelf Internet of Things (IoT) devices such as smartphone in conjunction with Quick Response (QR) codes which are widely deployed under the authorities requirement due to COVID-19 pandemic. Our proposed stationary inertial measurement unit (IMU) feature is implemented through a first order finite impulse response (FIR) filter that works along with the QR codes. It has successfully reduced the drift errors suffered by IMU. The performance was evaluated in the testing environment at an university campus. From the evaluation results, the proposed method outperformed the conventional method (IMU only) and hybrid model (IMU + QR code) by 94.9% and 57.7% respectively, making the proposed method a promising technique that can be readily applied to other indoor environments.