ILPS: Indoor localization using physical maps and smartphone sensors

Abstract

Indoor positioning and tracking services are garnering more attention. Recently, several state-of-the-art localization techniques have been proposed that use radio maps or the sensors readily available on smartphones. This paper presents a localization system called Indoor Localization using Physical maps and smartphone Sensors (ILPS), which is based on a building blueprint database and smartphone sensors. The blueprint database and access points (APs) provide a number of reference points that can be used to acquire the initial position and adjust the user position each time a reference point is detected. The proposed method is implemented on a smartphone and tested in real indoor environments. The experiments with ILPS demonstrate that using a static blueprint will avoid the costly database updates that are usually required in other approaches due to signal attenuation. Furthermore, ILPS performs better than existing work in term of accuracy and effectiveness for indoor localization.

Step detection algorithm for accurate distance estimation using dynamic step length

“…• Peak detection: the algorithm works as follows: the time is divided into dynamic time windows in which each time window contains the magnitude values which are computed by (2). The algorithm keeps track of three consecutive values in a vector called Start Vector, if the three values getting increased, then a peak might be a head.…”

“…However, due to the noise in the accelerometer output, any error in the signal will accumulate rapidly with time. To avoid this error, the distance is estimated by multiplying the number of steps by a constant step length [2,4].…”

“…Several methods have been proposed for the detection of the steps, such as, detection of the peaks [5], flat zone detection [6] and zero-crossings method [4,7]. Many previous works, e.g., [8,9] proposed different methods to estimate the step length; some of them used static length of each step, while others used dynamic step length [2].…”

Smartphones-Based Crowdsourcing Approach for Installing Indoor Wi-Fi Access Points

“…Positioning system can be divided into two categories [3]: indoor positioning and outdoor positioning. The indoor positioning precision requirements are higher than that for outdoors.…”

“…In addition, indoor location-based services (ILBSs) have become an essential part of people's activities in living, working, studying and shopping [5]. Indoor localization depends on infrastructures, such as ultra-wideband radio, Bluetooth and wireless access point [3] [6].…”