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Sensor Fusion (SF) combining accelerometer and gyroscope readings with position sensor (Wi-Fi, GPS) information is the way for increasing indoor positioning precision, mostly during intervals between subsequent callbacks from position sensor. Existing algorithms demonstrate the accuracy acceptable for the users. However customers often require the ALWAYS ON solution implemented on mobile platform...
These days, smart home applications such as a concierge service for residents, home appliance control and so on are attracting attention. In order to realize these applications, we strongly believe that we need an indoor positioning system which fulfills the following requirements: Req 1: high accuracy; Req 2: low installation cost; Req 3: small burden on the user; Req 4: low privacy invasion. There...
A common problem for indoor positioning methods is the fact that the differences in the reception characteristics among devices may significantly deteriorate the performance of a positioning system. Ranging algorithms for positioning rely on the accuracy of the parameters of the propagation model. This model is used to infer an estimate of the distance of a mobile device from each access point from...
Localization services available on today's mobile devices are proprietary and leverage a limited set of sources of location information. Integration of new location estimation methods is therefore cumbersome, requiring adaptation to the specific interfaces of the proprietary location service. In addition, location-based applications are tightly interwoven with the location service that is typically...
In this paper we present our work on the indoor positioning of users (shoppers), using a network of Bluetooth Low Energy (BLE) beacons deployed in a large wholesale shopping store. Our objective is to accurately determine which product sections a user is adjacent to while traversing the store, using RSSI readings from multiple beacons, measured asynchronously on a standard commercial mobile device...
The research presented in this paper is focused on In-home positioning systems. These indoor environments are characterized by a reduced number of AP, narrow spaces and very important radio signal attenuation. Existing indoor techniques seems to be not totally suitable for these scenarios; this paper proposes an add-on for helping these techniques by the use of wearable ultrasound sensors (distance...
The Global Navigation Satellite Systems (GNSS) suffer from accuracy deterioration and outages in dense urban canyons and are almost unavailable for indoor environments. Nowadays, developing indoor positioning systems has become an attractive research topic due to the increasing demands on ubiquitous positioning. WiFi technology has been studied for many years to provide indoor positioning services...
The paper presents a thorough evaluation of two representative visual place recognition algorithms that can be applied to the problem of indoor localization of a person equipped with a modern smartphone. The evaluation focuses on comparing two different state-of-the-art approaches: single image-based place recognition, represented by the FAB-MAP algorithm, and recognition based on a sequence of images,...
While indoor localization techniques based on Wi-Fi RSS measurements have been extensively studied, their application to eavesdropping Wi-Fi probe requests sent from mobile devices in large indoor environments, such as shopping malls, is scarce or absent in the literature. The idea behind this work is to observe Wi-Fi enabled smartphones, especially when they are not associated to a network. They...
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