Indoor positioning has finally testified a rise in interest, thanks to the big selection of services it is provided, and ubiquitous connectivity. There are currently many systems that can locate a person, be it wireless or by mobile phone and the most common systems in outdoor environments is the GPS, the most common in indoor environments is Wi-Fi positioning technique positioning. The improvement of positioning systems in indoor environments is desirable in many areas as it provides important facilities and services, such as airports, universities, factories, hospitals, and shopping malls. This paper provides an overview of the existing methods based on wireless indoor positioning technique. We focus in this survey on the strengths of these systems mentioned in the literature discordant with the present surveys; we also assess to additionally measure various systems from the scene of energy efficiency, price, and following accuracy instead of comparing the technologies, we also to additionally discuss residual challenges to correct indoor positioning.

The technology of indoor positioning has pulled in the consideration of researchers the expanding capability of smartphones and the advancement of sensor innovation, alongside the increase the time people spend working inside the building or being indoors. Sensor innovation, which is one of the most generally utilized information hotspots for indoor setting, has a favorable position that sensors can receive information from a cell phone without introducing any additional device. The idea of the proposed system is to use the Wi-Fi access points, inside the building, together with a Smartphone Wi-Fi sensor which lets the building administrator locate those carrying smartphones, wherever they exist inside the building. The proposed system consists of two-stage the testing stage (or preparation phase) and, the second stage is the training stage (or positioning phase). The data is collected and selected for accurate readings; a router is used, which is the Mikrotik access point type from which we can read the RSS value. The RSS value represents the Wi-Fi signal strength of the target device. The proposed IPS detection system is independent and can work in unconstrained environments. The database used to measure the performance of the proposed IPS detection system is collected from 14 locations (different in size). The number of readings obtained from the collected database is 1199 readings consist of received signal strength value from five access points. The proposed IPS accuracy is 96.8595% and the mean error is about 1.2 meters are achieved when using, K-Nearest Neighbor (K-NN), used the...