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

Abstract

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.

HelpResponder—System for the Security of First Responder Interventions

“…Table 8 shows a sum-up comparison of the main contributions in the field of the research described in this paper. In the works [9][10][11][12][13][14], there is a lack of solution applied to indoor environments without visual information because of the smoke of fire and absence of GNSS signals. Our proposal's system predicts the origin of the flame, the fire focus, thanks to the models that have been integrated into the algorithm explained in Section 3.…”

“…In those spaces, the location of a point of interest related to the emergence could improve the results. Bluetooth Low Energy (BLE) is mentioned in the next surveys [12], sufficient to relay low-bandwidth data. Nevertheless, more complex communication scenarios with heterogeneous sensor nodes with varying bandwidth and distance requirements are revised; indeed, the network must provide quality-of-service for both higher-bandwidth data such as camera streams as well as low-bandwidth temperature readings.…”

“…Moreover, to improve the environmental acquisition, the inclusion of images from the environment could offer relevant information. Most solutions usually use RGB cameras to explore the indoor environment [12]. However, those solutions cannot be applied indoors with no visibility.…”

A Robust and Accurate Indoor Localization Using Learning-Based Fusion of Wi-Fi RTT and RSSI

“…The simplicity of RSSI techniques has motivated many researchers to work on mitigating these issues. The RSSI-fingerprinting technique is one of the successful techniques toward this goal [ 25 , 26 , 27 ]. Fingerprinting localization approaches are common examples of probabilistic localization techniques.…”

“…Fingerprinting and time-based techniques are the most researched ones in the field. Fingerprinting [ 25 , 26 , 27 ] is widely adopted due to its relatively good performance especially with deep learning. Fingerprinting technique builds a fingerprint database that involve signatures of Wi-Fi signals collected at different reference locations covering the area of interest.…”