Normalizing RSS Values of Wi-Fi Access Points to Improve an Integrated Indoors Smartphone Positioning Solutions

The demand for advanced location-based services (LBS), which use smartphones, has increased significantly in the last few years, essentially in Global-Navigation-Satellite-System (GNSS) contradict situations. Smartphones are accompanying us ubiquitously and gives us the ability to access numerous purposes. Since many applications based on indoor positioning, hearten further progress for LBS, since the GNSS cannot provide accurate indoor positioning due to weak GNSS signals. Alternatively, several wireless and sensors technologies are embedded on smartphones including Wi-Fi, Bluetooth, Cellular and inertial sensors. Further, the smartphones provide powerful processing capability to meet these LBS application requirements. Therefore, locating using smartphones has been a significant subject since it is needed to determine indoor people position. The obtained indoor position can be used for many services such as customer location detection, real-time monitoring, security alarms, media services and entertaining applications. However, such services suffer from the positioning accuracy and cost issue of deploying the positioning solutions. To tackle these issues, this article proposes an improvement solution to provide a continuous positioning approach on the go by integrating smartphone positioning sensors (Accelerometer and Gyroscope) with the improved received signal strength (RSS) of the Wi-Fi Access points (WAP). The positioning accuracy, based on a set of real experiments, less than 2 meters positioning accuracy is achieved at lower cost in comparison with the current developed techniques.