INDOOR LOCALIZATION USING WI-FI BASED FINGERPRINTING AND TRILATERATION TECHIQUES FOR LBS APPLICATIONS (original) (raw)

Wireless Indoor Localization Using Fingerprinting Technique

Journal of Advanced Research in Dynamical and Control Systems, 2020

Indoor positioning has gained more interest as one of the upcoming applications due to its use in a variety of services. Multiple technologies such as Bluetooth, Wi-Fi, RFID. However, Wi-Fi based localization in indoor environment offers significant advantages utilizing installed wireless infrastructures and good performances with low cost. With this study, we aim to provide a compromise between accurate positioning and feasibility of the system for practical applications. For this purpose, we minimize the fluctuations of Wi-Fi received signal strength (RSS) by filtering and we combine two approaches to locate a mobile user. At first, we implemeted the traditional fingerprinting technique that uses a real time matching of pre-recorded received signal strength (RSS) from the location data of the user transmitted to nearby access points (AP). Secondly, we used distance-based trilateration technique which determines positions using three known access points. The combination of the two methods provides enhancement of accuracy and wide indoor locating coverage. Regardless the locating data number, experiment confirmed a significant and a consistent performance in term of execution time and accuracy.

Indoor Position Detection Using WiFi and Trilateration

2012

Various techniques that employ GPS signals such as A-GPS and GPS transmitters [4, 7] have been introduced with the hope to provide a solution for indoor positioning detection. We proposed the implementation of trilateration technique to determine the position of users in indoor areas based on Wi-Fi signal strengths from access points (AP) within the indoor vicinity. In this paper, percentage of signal strengths obtained from Wi-Fi analyzer in a smartphone were converted into distance between users and each AP. A user’s indoor position could then be determined using a formula proposed based on trilateration technique.

Indoor Location Estimation Utilizing Wi-Fi Signals

International Journal of Emerging Trends in Engineering Research, 2020

Global Positioning System is commonly been used for locating a position of a specific structure in finding geographical coordinates of a target area. Though, this application is still having a restricted in term of the signals, might not well operated and ineffective for indoor usage. The study aim is to develop positioning and localization systems by using Wi-Fi signal. Estimation was made based on the measurement of wireless distance for estimation the user's coordinates. Analysis of views called the fingerprint algorithm is used in this study. The algorithm involved two phases over an offline and the online phases of the survey. Unidentified user's coordinates will be in the online phase by comparative databases collected in the survey phase. MATLAB Graphical User Interface and Android has been used to develop a user interface for simulation purposes. Several analyses were performed to define the precision and efficiency of occurred error as the number of access points and the traffic environment. Finally, the user required to provide several inputs e.g. the exact location and the RSS from AP's number at the present location. The simulation-based software will evaluate the estimation location and positioning of the user and will match to user's precise location.

INDOOR POSITION DETECTION USING WIFI AND TRILATERATION TECHNIQUE

Various techniques that employ GPS signals such as have been introduced with the hope to provide a solution for indoor positioning detection. We proposed the implementation of trilateration technique to determine the position of users in indoor areas based on Wi-Fi signal strengths from access points (AP) within the indoor vicinity. In this paper, percentage of signal strengths obtained from Wi-Fi analyzer in a smartphone were converted into distance between users and each AP. A user's indoor position could then be determined using a formula proposed based on trilateration technique.

Wi-Fi RSS Fingerprinting for Indoor Localization Using Augmented Reality

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020

Indoor localization has attracted the attention of researchers for wide applications in areas like construction, facility management, industries, logistics, and health. The Received Signal Strength (RSS) based fingerprinting method is widely adopted because it has a lower cost over other methods. RSS is a measurement of the power present in the received radio signal. While this fingerprinting method is very popular, there is a significant amount of effort required for collecting fingerprints for indoor space. In this paper, we propose an RSS fingerprinting method using Augmented Reality (AR) that does not rely on an external sensor resulting in ease of use and maintenance. This method uses spatial mapping techniques to help align the floor plan of existing buildings; then, after the alignment, we map local device coordinates to global coordinates. After this process, we partition the space in equally distanced reference points for RSS fingerprint collection. We developed an application for Microsoft HoloLens to align the floor plan and collect fingerprints on reference points. Then we tested collected fingerprints with existing RSS based indoor localization methods for its accuracy and performance.

Finding indoor position of person using wi-fi & smartphone:A survey

Positioning system can be used for different purposes and for different services, so a lot of research is going on to find a more accurate position with low error techniques with good results. The Positioning techniques have been actively studied recently due to service as well as safety and security matters. Global Positioning System (GPS) is more widely used for outdoor but GPS is not suitable for indoor . There are many localization systems with different architectures, configurations, accuracies and reliabilities Wi-Fi Positioning system (WPS) solves this problem. Here we find out position with the help of Wi-Fi signal strength. We also discuss location fingerprinting in detail since it is used in most current system or solutions. A small program installed on to calculate the position. This will help in many applications for mobile users and network administrators. It will make use of existing Wi-Fi infrastructure, although Wi-Fi system was never designed to find out the location. The smart device regularly scans the signal strengths for surrounding Wi-Fi access points and send information to a central server. This paper try to survey the recent work related to indoor positioning system.

On the efficacy of WiFi indoor positioning in a practical setting

2013 IEEE Symposium on Computers and Communications (ISCC), 2013

We implement two popular WiFi, fingerprinting based indoor tracking mechanisms, namely the k-nearest neighbours and probabilistic positioning methods. Both mechanisms are evaluated in the context of an indoor position-tracking tablet application, following an investigation to determine optimal working parameters. Our results indicate that even after significant optimisation, both fingerprinting algorithms are highly sensitive to the location of the access points and do not produce finely grained location results. Although in this case the results are accurate enough for our purposes, factors such as the effect of natural body obstruction of the user as well as the location of the access points used in fingerprinting must be considered carefully if more accuracy is required.

Indoor Localization Method Based on Wi-Fi Trilateration Technique

—This paper describes a Wi-Fi trilateration method for indoor localization using Android-based mobile device. Approaches based on signal propagation model and received signal strength measurement collection are considered. The indoor signal propagation problem is resolved by received signal strength measurement collection that improves localization accuracy. Indoor positioning technique opens possibilities for development various intelligent systems that provide the user location-based information inside buildings. These systems include positioning functionality based on such technologies as Wi-Fi, Bluetooth, and GSM.

A new method for improving Wi-Fi-based indoor positioning accuracy

Wi-Fi and smartphone based positioning technologies are play-ing a more and more important role in Location Based Service (LBS) industries due to the rapid development of the smartphone market. However, the low positioning accuracy of these technologies is still an issue for indoor positioning. To ad-dress this problem, a new method for improving the indoor posi-tioning accuracy was developed. The new method initially used the Nearest Neighbor (NN) algorithm of the fingerprinting meth-od to identify the initial position estimate of the smartphone us-er. Then two distance correction values in two roughly perpen-dicular directions were calculated by the path loss model based on the two signal strength indicator (RSSI) values observed. The errors from the path loss model were eliminated by differencing two model-derived distances from the same access point. The new method was tested and the results compared and assessed against that of the commercial Ekahau RTLS system and the NN algorithm. The preliminary results showed that the positioning accuracy has been improved consistently after the new method was applied and the root mean square accuracy improved to 3.3 m from 3.8 m compared with the NN algorithm.