Una piattaforma per la localizzazione indoor tramite crowdsensing

Questo elaborato studia e analizza il comportamento di tre algoritmi di base per quanto riguarda la localizzazione indoor e in particolare la tecnica del fingerprint. L'elaborato include l'analisi di come l'eterogeneita dei dispositivi possa influenzare gli algoritmi e la loro accuratezza nel produrre il risultato. Si include inoltre l'analisi dello stato dell'arte la progettazione e lo sviluppo di un'applicazione Android e di un web service. L'illustrazione dei test effettuati e le considerazioni finali concludono la tesi.

WIFI indoor positioning for mobile devices, an application for the UJI Smart Campus

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Studio e valutazione sperimentale di tecniche di radio fingerprinting per navigazione indoor con dispositivi mobili Android

Lo studio effettuato raccoglie informazioni al fine di svolgere un’analisi globale delle tecniche attualmente in uso, o in fase di studio, nel campo della localizzazione di dispositivi all’interno di un ambiente chiuso, ovvero laddove non è possibile sfruttare la copertura del sistema GPS. La panoramica è frutto dell’analisi e dello studio di paper tecnici pubblicati dai collaboratori dell’IEEE, fruibili all’interno del portale IEEE Xplore. A corredo di questo studio è stata sviluppata una applicazione per dispositivi Android basata sulla tecnica del Wi-Fi fingerprint; l’applicazione, che rappresenta un primo approccio alle tecniche di localizzazione, è a tutti gli effetti un sistema standalone per la localizzazione, consente cioè di costruire sia la mappa per la localizzazione, partendo da un ambiente sconosciuto, sia di ottenere la posizione dell’utente all’interno di una mappa conosciuta. La tesi si conclude con una analisi dei risultati e delle performance ottenute dall’applicazione in un uso comune, al fine di poter valutare l’efficacia della tecnica presa in considerazione. I possibili sviluppi futuri sono analizzati in un capitolo a parte e trovano spazio in ambienti nei quali si vogliono offrire servizi "context-based", ovvero basati sulla posizione esatta dell’utente.

Performance of microstrip antennas in the presence of EBG in an indoor localization system

Indoor localization systems in nowadays is a huge area of interest not only at academic but also at industry and commercial level. The correct location in these systems is strongly influenced by antennas performance which can provide several gains, bandwidths, polarizations and radiation patterns, due to large variety of antennas types and formats. This paper presents the design, manufacture and measurement of a compact microstrip antenna, for a 2.4 GHZ frequency band, enhanced with the use of Electromagnetic Band-Gap (EBG) structures, which improve the electromagnetic behavior of the conventional antennas. The microstrip antenna with an EBG structure integrated allows an improvement of the location system performance in about 25% to 30% relatively to a conventional microstrip antenna.

A lightweight indoor localization model based on motley-keenan and COST

This paper presents a novel approach to WLAN propagation models for use in indoor localization. The major goal of this work is to eliminate the need for in situ data collection to generate the Fingerprinting map, instead, it is generated by using analytical propagation models such as: COST Multi-Wall, COST 231 average wall and Motley- Keenan. As Location Estimation Algorithms kNN (K-Nearest Neighbour) and WkNN (Weighted K-Nearest Neighbour) were used to determine the accuracy of the proposed technique. This work is based on analytical and measurement tools to determine which path loss propagation models are better for location estimation applications, based on Receive Signal Strength Indicator (RSSI).This study presents different proposals for choosing the most appropriate values for the models parameters, like obstacles attenuation and coefficients. Some adjustments to these models, particularly to Motley-Keenan, considering the thickness of walls, are proposed. The best found solution is based on the adjusted Motley-Keenan and COST models that allows to obtain the propagation loss estimation for several environments.Results obtained from two testing scenarios showed the reliability of the adjustments, providing smaller errors in the measured values values in comparison with the predicted values.

Step count algorithm adapted to indoor localization

This paper presents a step count algorithm designed to work in real-time using low computational power. This proposal is our first step for the development of an indoor navigation system, based on Pedestrian Dead Reckoning (PDR). We present two approaches to solve this problem and compare them based in their error on step counting, as well as, the capability of their use in a real time system.

Traveled Distance Estimation Algorithm for Indoor Localization

This paper presents an ankle mounted Inertial Navigation System (INS) used to estimate the distance traveled by a pedestrian. This distance is estimated by the number of steps given by the user. The proposed method is based on force sensors to enhance the results obtained from an INS. Experimental results have shown that, depending on the step frequency, the traveled distance error varies between 2.7% and 5.6%.

Indoor Localization Solutions for a Marine Industry Augmented Reality Tool

In this report are described means for indoor localization in special, challenging circum-stances in marine industry. The work has been carried out in MARIN project, where a tool based on mobile augmented reality technologies for marine industry is developed. The tool can be used for various inspection and documentation tasks and it is aimed for improving the efficiency in design and construction work by offering the possibility to visualize the newest 3D-CAD model in real environment. Indoor localization is needed to support the system in initialization of the accurate camera pose calculation and auto-matically finding the right location in the 3D-CAD model. The suitability of each indoor localization method to the specific environment and circumstances is evaluated.

The indoor localization system using vision for multiple mobile robots

This paper presents the development of an indoor localization system using camera vision. The localization system has a capability to determine 2D coordinate (x, y) for a team of mobile robots, Miabot. The experimental results show that the system outperforms our existing sonar localizer both in accuracy and a precision.

A low complexity system based on multiple weighted decision trees for indoor localization

[EN] Indoor position estimation has become an attractive research topic due to growing interest in location-aware services. Nevertheless, satisfying solutions have not been found with the considerations of both accuracy and system complexity. From the perspective of lightweight mobile devices, they are extremely important characteristics, because both the processor power and energy availability are limited. Hence, an indoor localization system with high computational complexity can cause complete battery drain within a few hours. In our research, we use a data mining technique named boosting to develop a localization system based on multiple weighted decision trees to predict the device location, since it has high accuracy and low computational complexity.

Progettazione ed implementazione di un prototipo per la geolocalizzazione indoor dei device wifi in ambito aeroportuale.

Nel documento vengono trattate le principali tecniche di geolocalizzazione basate sull'elaborazione dei segnali elettromagnetici ricevuti. E' altresì introdotto un sistema di remote positioning basato su test di prossimità rafforzato tramite machine learning tramite un approccio simulativo ed una implementazione reale.

SDR-based Passive Indoor Localization System for GSM

This study deals with indoor positioning using GSM radio, which has the distinct advantage of wide coverage over other wireless technologies. In particular, we focus on passive localization systems that are able to achieve high localization accuracy without any prior knowledge of the indoor environment or the tracking device radio settings. In order to overcome these challenges, newly proposed localization algorithms based on the exploitation of the received signal strength (RSS) are proposed. We explore the effects of non-line-of-sight communication links, opening and closing of doors, and human mobility on RSS measurements and localization accuracy. We have implemented the proposed algorithms on top of software defined radio systems and carried out detailed empirical indoor experiments. The performance results show that the proposed solutions are accurate with average localization errors between 2.4 and 3.2 meters.

Robust indoor localization of narrowband signals

Many location-based services target users in indoor environments. Similar to the case of dense urban areas where many obstacles exist, indoor localization techniques suffer from outlying measurements caused by severe multipath propaga??tion and non-line-of-sight (NLOS) reception. Obstructions in the signal path caused by static or mobile objects downgrade localization accuracy. We use robust multipath mitigation techniques to detect and filter out outlying measurements in indoor environments. We validate our approach using a power-based lo??calization system with GSM. We conducted experiments without any prior knowledge of the tracked device's radio settings or the indoor radio environment. We obtained localization errors in the range of 3m even if the sensors had NLOS links to the target device.