Comparison of 2.4 and 5 GHz WLAN network for purpose of indoor and outdoor location

This paper presents comparison of prototype location system built with standard components of 2.4 and 5 GHz WLAN network infrastructure. The system can be used for personal or other objects’ positioning, both for indoor and outdoor environments. The system is local, i.e. its operational area is limited to WLAN network operating range. The system is based on standard and widely available WLAN components (access points, network adapters). The goal is to avoid any hardware and software modifications. Also position calculation should not be power hungry operation. Method of location is based in Received Signal Strength Indication (RSSI) returned by most of RF ICs (including WLAN). The main focus is research of how much accuracy (and usefulness) can be expected from standard WLAN hardware. Both static and dynamic scenarios have been tested and compared

A Review of Hybrid Indoor Positioning Systems Employing WLAN Fingerprinting and Image Processing

Location-based services (LBS) are a significant permissive technology. One of the main components in indoor LBS is the indoor positioning system (IPS). IPS utilizes many existing technologies such as radio frequency, images, acoustic signals, as well as magnetic sensors, thermal sensors, optical sensors, and other sensors that are usually installed in a mobile device. The radio frequency technologies used in IPS are WLAN, Bluetooth, Zig Bee, RFID, frequency modulation, and ultra-wideband. This paper explores studies that have combined WLAN fingerprinting and image processing to build an IPS. The studies on combined WLAN fingerprinting and image processing techniques are divided based on the methods used. The first part explains the studies that have used WLAN fingerprinting to support image positioning. The second part examines works that have used image processing to support WLAN fingerprinting positioning. Then, image processing and WLAN fingerprinting are used in combination to build IPS in the third part. A new concept is proposed at the end for the future development of indoor positioning models based on WLAN fingerprinting and supported by image processing to solve the effect of people presence around users and the user orientation problem