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A smart-phone based hand-held indoor positioning system is presented in this paper. The system collects data using the accelerometers, gyroscopes, barometers and gravity sensors embedded in the smart-phone. The accelerometer and gravity data are used for zero-velocity detection and calculating the vertical displacement of each walking step, and then the inverted pendulum model is applied to calculate...
As wireless local area network, WLAN, access point (AP) are becoming very common wireless communication infrastructures in indoor environments, Wi-Fi signal based Indoor Positioning Systems (IPS) have been widely developed in recent years and one of the most popular technologies is the received signal strength (RSS) fingerprinting technology. However, due to large amount of time-consuming work required...
This paper proposes a new semi-supervised machine learning for localization. It improves localization efficiency by reducing efforts needed to calibrate labeled training data by using unlabeled data, where training data come from received signal strengths of a wireless communication link. The main idea is to treat training data as spatio-temporal data. We compare the proposed algorithm with the state-of-art...
To avoid substantial manual calibration effort, some WiFi-based indoor localization methods attempt to achieve calibration-free feature. However, many of these methods have additional requirements which limit their practical applicabilities, e.g. lateration-based methods require the target locations to be covered by at least three APs, some methods require specific relationships between the training...
Most existing indoor localization algorithms based on Wi-Fi signals mainly rely on wireless access points (APs), i.e. hotspots, with fixed deployment, which are easily affected by the non-line of sight (NLOS) factors and the multipath effect. There also exist many other problems, such as positioning stability and blind spots, which can cause decline in positioning accuracy at certain positions, or...
Existing localization technologies face several challenges indoors because of their sensitivity to the environment. In this paper, we present an indoor localization system based on Low Frequency (LF) Radio-Frequency Identification (RFID) as a reliable and low-cost solution, which is less affected by challenging indoor conditions. The presented system makes use of LF (125 kHz) magnetic fields for reliable...
Post-processing indoor navigation is interesting, for example to develop crowdsourcing analysis. The post-processing framework allows to provide a better estimation than in a real-time framework. The main contribution of this paper is to present a piecewise parametrization using Inertial Measurement Unit (IMU) and Received Signal Strength (RSS) measurements only which lead to an optimization problem...
In this paper we present our developed and evaluated method for the dynamic mapping of the vertical characteristics inside a building. For achieving that, we extract data from smart-phone sensors and use those data for altitude estimation via the barometric formula. We introduce a novel approach for the extraction of reference pressure during the outdoor-to-indoor-transition of the user inside a building,...
How can the collected data from testing an indoor positioning deployment be transformed into information concerning the optimal tuning of a positioning system in this deployment? How can such kind of accumulated information from several deployments be transformed into more generic knowledge regarding the system's performance, with respect to several performance goals? In this work, we present a multiobjective...
There are an increasing number of smartphone applications using indoor positioning. Ideally, no additional infrastructure is needed and only sensors already present in smartphones are used to compute positions indoors. Therefore, approaches such as pedestrian dead reckoning and human motion monitoring are currently being reviewed. In fact, these approaches are not only being reviewed by research facilities,...
In this paper, the challenges of Ultra Wide Band localization for key fob applications in vehicular environments are discussed. Trilateration based Kalman and particle filter approaches are discussed regarding their applicability to this task. A particle filter method is proposed which combines the benefit of enabling non-Gaussian observation error distribution and direct mapping of a particle cloud...
In this contribution, an opto-acoustic system for distance measurement between a transmitter and a receiver is presented. This distance measurement is part of an indoor localization system which uses multilateration to obtain the position and orientation of rigid bodies. The novelty of the presented distance measurement is the efficiency in the sense that high accuracy is obtained with the use of...
Various indoor navigation methods have been developed recently, but digitalized data of indoor map is not always available. Therefore, an indoor navigation framework using an image of information board has been proposed. In this method, the process to extract map regions from the image of an information board is necessary to be done by hands beforehand, and the process to estimate passageway regions...
Acoustic ranging based indoor positioning solutions have the advantage of higher ranging accuracy and better compatibility with commercial-off-the-self consumer devices. However, similar to other time-domain based approaches using Time-of-Arrival and Time-Difference-of-Arrival, they suffer from performance degradation in presence of multi-path propagation and low received signal-to-noise ratio (SNR)...
Navigating in large hospitals is a challenging task. The consequences of difficulties faced by staff, patients and visitors in finding their way in the hospital can be multiple. The HUGApp project goals are to identify the navigational needs and requirements of people within the premises of Geneva University Hospitals (HUG) before proceeding with potential solutions, such as an indoor navigation mobile...
Vertical height estimation is critical to indoor localization technique. However, the common story height covers from 2.8m to 6.0m in multistory buildings, which make it meaningless to estimate height alone. An efficient indoor location system should provide accurate floor estimation with fuzzy story height information. This paper proposes a Bayesian Network inference method to identify pedestrian's...
Indoor localisation is a currently a key issue, from robotics to the Internet of Things. With hardware advancements making Ultra-Wideband devices more accurate and low powered (potentially even passive), this unlocks the potential of having such devices in common place around factories and homes, enabling an alternative method of navigation. Therefore, anchor calibration indoors becomes a key problem...
This paper presents a synchronization-free TDoA localization method (SF-TDOA) that can be used in wireless networks of hundreds and thousands of mobile nodes. The location of mobile node is determined based on the differences of the reception times of radio packets at node (packets transmitted by anchors), knowledge of anchors' location and anchors mode of operation. Since mobile nodes do not need...
Fingerprinting based WLAN indoor positioning system (FWIPS) provides a promising indoor positioning solution to meet the growing interests for indoor location-based services (e.g., indoor way finding or geo-fencing). FWIPS is preferred because it requires no additional infrastructure for deploying an FWIPS — achieving the position estimation by reusing the available WLAN and mobile devices, and is...
Ultra-wideband wireless positioning technologies based on IEEE 802.15.4a have gained attention for various use cases requiring highly precise localization. Multi-rotor unmanned aerial vehicle (UAV) systems provide several sensors for stabilization and navigation. However, absolute indoor positioning poses a problem for autonomous robotic systems. The specific challenge addressed in this paper is enabling...
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