Mobility and safety are primary concerns for blind and visually impaired (BVI) users when navigating in unfamiliar environments. Typically, a sighted person can locate a place of interest if they are provided guidance while approaching within a few meters of the location. However, this resolution of guidance is often insufficient for blind travelers. In this thesis, we propose a crowdsourcing based micro navigation system for BVI users in both indoor and outdoor environments. To achieve this goal, our system includes three parts: crowdsourcing reports generated by volunteers using the volunteer application, landmarks validation performed by the system administrator using the admin application, and the BVI user navigation obtained through the BVI user application. In addition, we provide accessible audio navigation for indoor and outdoor environments required to deliver real time step by step landmark information to BVI users. Crowdsourcing is enabled by the contribution of many volunteers which use the proposed volunteer application to report specific landmarks in the environment including their location, description and surrounding landmarks. These reports which are uploaded to the server database, are validated by the admin application which updates the server database and deploy BLE tags for indoor environment. The BVI user application localizes users by GPS outdoors and BLE proximity technology indoors. Using the real-time location of users and the landmark node graph we built from updated server database, this application provides the shortest route to the destination and real time “micro-navigation” information describing how to get to the next landmark’s location with corresponding distance & orientation. This information is used ix to make users well aware of where they are, and guide users to their chosen destination within a cane’s distance. This application will improve the confidence and safety of BVI users by enabling them to explore and get navigation in both indoor and outdoor environments.

Positioning systems enable location-awareness for mobile devices, computers, and even tactical radios. From the collected location information, location-based services can be realized. One type of positioning system is based on location fingerprints. Unlike the conventional positioning techniques of time of or time delay of arrival (TOA/TDOA) or even angle of arrival (AOA), fingerprinting associates unique characteristics such as received signal strength (RSS) that differentiates a location from another location. The location-dependent characteristics then can be used to infer a user's location. Furthermore, fingerprinting requires no specialized hardware because of its reliance on an existing communications infrastructure. In estimating a user's position, fingerprint-based positioning systems are centrally calculated on a mobile computer using either a Euclidean distance algorithm, Bayesian statistics, or neural networks. With large service areas and, subsequently, large radio maps, one mobile computer may not have the adequate resources to locally compute a user's position. Wireless distributed computing provides a means for the mobile computer to meet the location-based service requirements and increase its network lifetime. This thesis develops distributed localization algorithms to be used in an indoor fingerprint-based positioning system. Fingerprint calculations are not computed on a single device, but rather on a wireless distributed computing network on Virginia Tech's Cognitive Radio Network Testbed (CORNET). / Master of Science

Recently, indoor localization becomes a hot topic no matter in industry or academic field. Smart phones are good candidates for localization since they are carrying various sensors such as GPS, Wi-Fi, accelerometer, barometer and etc, which can be used to estimate the current location. But there are still many challenges for 3D indoor geolocation using smart phones, among which the map selection and 3D performance evaluation problems are the most common and crucial. In the indoor environment, the popular outdoor Google maps cannot be utilized since we need maps showing the layout of every individual floor. Also, layout of different floors differ from one another. Therefore, algorithms are required to detect whether we are inside or outside a building and determine on which floor we are located so that an appropriate map can be selected accordingly. For Wi-Fi based indoor localization, the performance of location estimation is closely related to the algorithms and deployment that we are using. It is difficult to find out a general approach that can be used to evaluate any localization system. On one hand, since the RF signal will suffer extra loss when traveling through the ceilings between floors, its propagation property will be different from the empirical ones and consequently we should design a new propagation model for 3D scenarios. On the other hand, properties of sensors are unique so that corresponding models are required before we analyze the localization scheme. In-depth investigation on the possible hybrid are also needed in case more than one sensor is operated in the localization system. In this thesis, we firstly designed two algorithms to use GPS signal for detecting whether the smart device is operating inside or outside a building, which is called outdoor-indoor transition detection. We also design another algorithm to use barometer data for determining on which floor are we located, which is considered as a multi-floor transition detection. With three scenarios designed inside the Akwater Kent Laboratory building (AK building) at Worcester Polytechnic Institute (WPI), we collected raw data from an Android phone with a version of 4.3 and conducted experimental analysis based on that. An efficient way to quantitatively evaluate the 3D localization systems is using Cramer-Rao Lower Bound (CRLB), which is considered as the lower bound of the estimated error for any localization system. The characteristics of Wi-Fi and barometer signals are explored and proper models are introduced as a foundation. Then we extended the 2D CRLB into a 3D format so that it can fit the our 3D scenarios. A barometer-assisted CRLB is introduced as an improvement for the existing Wi-Fi Receive Signal Strength (RSS)-only scheme and both of the two schemes are compared with the contours in every scenario and the statistical analysis.

no / A comparison is presented between two indoor localization algorithms using received signal strength, namely the vector algorithm and the Comparative Received Signal Strength (CRSS) algorithm. Signal values were obtained using ray tracing software and processed with MATLAB to ascertain the effects on localization accuracy of radio map resolution, number of access points and operating frequency. The vector algorithm outperforms the CRSS algorithm, which suffers from ambiguity, although that can be reduced by using more access points and a higher operating frequency. Ambiguity is worsened by the addition of more reference points. The vector algorithm performance is enhanced by adding more access points and reference points while it degrades with increasing frequency provided that the statistical mean of error increased to about 60 cm for most studied cases. / Unable to contact publisher. Contact webform only works for members - no email addresses. Raed said he would try and get contact details - email 14th March 2016 / The full text is unavailable. The publisher is unable to be contacted.

Indoor localization systems have a variety of applications such as tracking of assets, indoor robot navigation, and monitoring of people (e.g. patients) in hospitals or at home. Global positioning system (GPS) offers location accuracy of several meters and is mainly used for outdoor location-based applications as its accuracy degrades significantly in indoor scenarios. Wireless local area networks (WLAN) have also been used for indoor localization, but the accuracy is too low and power consumption of WLAN terminals is too high for most applications. Ultra-wideband (UWB) localization is superior in terms of accuracy and power consumption compared with GPS and WLAN localization, and is thus more suitable for most indoor location-based applications [1-4]. The accuracy and precision requirements of localization systems depend on the specific characteristics of the applications. For example, centimeter or even millimeter localization accuracy is required for dynamic part tracking, while decimeter accuracy might be sufficient for tracking patients in hospitals or at home. Note that accuracy is not the only aspect of the overall performance of the system. Factors such as cost, range, and complexity should also be considered in system design. In the first part of this dissertation, a centimeter-accurate UWB localization system is developed. The technical challenges to achieve centimeter localization accuracy are investigated. Since all the receivers are synchronized through wire connection in this system, a wireless localization system with centimeter accuracy is introduced in order to make the system easier for deployment. A two-step synchronization algorithm with picosecond accuracy is presented, and the system is tested in a laboratory environment. The second part of this dissertation focuses on reducing the complexity of UWB localization systems when the localization accuracy requirement is relaxed. An UWB three-dimensional localization scheme with a single cluster of receivers is proposed. This scheme employs the time-of-arrival (TOA) technique and requires no wireless synchronization among the receivers. A hardware and software prototype that works in the 3.1-5.1 GHz range is constructed and tested in a laboratory environment. An average position estimation error of less than 3 decimeter is achieved by the experimental system. This TOA scheme with receivers in a single unit requires synchronization between the transmitter and the receiver unit. In order to further reduce system complexity, a new time-difference-of-arrival localization scheme is proposed. This scheme requires multiple units, each operating on its own clock. It avoids synchronization between the transmitter and receivers, and thus makes the development of the transmitter extremely simple. The performance of this system is simulated and analyzed analytically, and turns out to be satisfactory for most indoor localization applications. / Graduation date: 2013

The vision of ubiquitous computing is to seamlessly integrate information processing into everyday objects and activities. Part of this integration is an awareness on the part of a system of its user's context. Context can be composed of several variables --- such as a user's current activity, goals, or state of mind --- but location (both past and present) is almost always a key component. Determining location outdoors has become quite simple and pervasive with today's low-cost handheld Global Positioning System (GPS) receivers. Technologies enabling the location of people and objects to be determined while indoors, however, have lagged due to their extensive infrastructure requirements and associated cost. Just as GPS receivers utilize radio signals from satellites to triangulate their position, an indoor real-time locating system (RTLS) must also make use of some feature of the environment to determine the location of mobile units. Since the signal from GPS satellites is not sufficiently strong to penetrate the structure of a building, indoor RTLS systems must either use some existing feature of the environment or generate a new one. This typically requires a large amount of infrastructure (e.g. specialized RF receivers, additional 802.11 access points, RFID readers, etc.) to be deployed, making indoor RTLSs impractical for the home. While numerous techniques have been proposed for locating people and objects within a building, none of these has yet proven to be a viable option in terms of cost, complexity of installation, and accuracy for home users. This dissertation builds on work by Patel et al. in which the home power lines are used to radiate a low-frequency wireless RF signal that mobile tags use for location fingerprinting. Leveraging the existing power line permits this system to operate on far less additional infrastructure than existing solutions such as cellular (GSM and CDMA), 802.11b/g, and FM radio based systems. The contributions of this research to indoor power line-based RTLS are threefold. First, I examine the temporal stability of a power line based RTLS system's output. Fingerprinting-based RTLS relies upon some feature of the environment, such as the amplitude of an RF signal, to be stable over time at a particular location (temporal stability), but to change in space (spatial differentiability). I show that a power line-based RTLS can be made much more resistant to temporal instability in individual fingerprint components by utilizing a wide-band RF fingerprint. Next, I directly compare the temporal stability of the raw features used by various fingerprinting based indoor RTLSs, such as cellular, 802.11b/g, and FM radio. In doing so, I show that a power line based indoor RTLS has an inherent advantage in temporal stability over these other methods. Finally, I characterize the power line as a receiving antenna for low-powered wireless devices within the home, thus allowing the power line to not only transmit the RF signals used for fingerprinting, but also to receive the sensed features reported by location tags. Here, I show that the powerline is a viable receiver for these devices and that the globally available 27.12 MHz ISM band is a good choice of frequency for communications.

L'environnement \textit{indoor} permet un grand nombre de services issus des technologies de l'information et de la communication. La localisation de l'utilisateur, via celle de son smartphone, est donc un élément-clé de cette réussite. Cette thèse s'intéresse au suivi des déplacements de l'utilisateur grâce aux capteurs de mouvement embarqués dans son smartphone. Elle repose sur la détermination du type de locomotion. Nous proposons une solution de navigation \textit{indoor} complète, permettant de proposer à l'utilisateur un chemin jusqu'à sa destination dans n'importe quel bâtiment tout en connaissant sa position à chaque instant, avec une précision de l'ordre du mètre. De façon analogue, nous avons également montré que nous pouvons déterminer le mode de transport d'un utilisateur pour une application de détection de places de parking libres. / Indoor environments present opportunities for a rich set of location-aware services in the information and communications technology (ICT) area. Therefore, accurately localizing a user indoors has become a key enabling technology. This thesis addresses the issue of tracking a user equipped with an off-the-shelf smartphone by exploiting its embedded motion sensors. Leveraging key characteristics of human locomotion, we propose a complete, infrastructure-free indoor navigation solution, allowing a user to navigate any unknown building with meter-level accuracy. Finally, extending our understanding of locomotion to outdoors areas where users are inside vehicles, we design and implement a smartphone application for smart on-street parking.

The use of smartphones for positioning and navigation is mostly limited to outdoor settings. Indoors, where GPS signals are too inaccurate for positioning, an alternative must be used. This project aimed at producing an indoor positioning system which could be both configured and used by an end user organization without equipping its buildings with proprietary hardware. The prerequisites were that a complete digital representation of the building floors is available, and that the floors have a sufficient amount of WiFi access points. Our system measures radio signal strength from existing WiFi infrastructure using a smartphone. This data is sent to a backend and is used to position a device using two different methods: trilateration and fingerprinting. The finished system can position a user with an accuracy of approximately four meters using fingerprinting instead of trilateration as it yielded the best results. The building used for testing was scanned using a smartphone equipped with our application, something that we would expect an end user to be able to do. / Användandet av smartphones för positionering och navigering är mestadels inriktat på utomhusanvändning. Inomhus är GPS signaler inte tillräckligt noggranna för positionering, och ett alternativ måste användas. Det här projektets mål var att producera ett inomhuspositioneringssystem som kan konfigureras och användas av slutanvändarorganisationen utan att behöva utrusta sina byggnader med proprietär hårdvara. Förutsättningarna är att en komplett digital representation av byggnaden finns tillgänglig, och att våningsplanen har tillräckligt många WiFi basstationer. Vårt system mäter radiosignalstyrka från den existerande WiFi infrastrukturen. Denna data skickas till en backend och används i två olika metoder: trilateration och fingerprinting. Det slutgiltiga systemet kan positionera en användare med en träffsäkerhet på ungefär fyra meter när fingerprintingmetoden används då den producerade det bästa resultatet. Byggnaden som systemet testades i skannades av en smartphone med vår applikation, en sak som vi förväntar oss att en slutanvändare skulle kunna göra själv.

This diploma thesis describes implementation of an indoor positioning system for tracking the location and movement of material and products through the manufacturing plant. The system is designed with regards to simple installation and low overall implementation costs. It utilizes method of Wi-Fi and magnetic field fingerprinting. The system employs a client hardware (active tag with Wi-Fi module and sensors designed for this project) communicating with a server software which does the mapping and fingerprinting processing. Finall positioning system is prepared to collect locations data for further analysis aiming to improve efficiency of manufacturing processes.

Táto práca je prípadovou štúdiou postupného vývoja a nasadzovania lokačného softwaru v reálnom čase. Cieľom tejto práce je zrýchliť tento proces. Zvolený problém bol vyriešený s konvenčnými testovacími nastrojmi, vlastným nástrojom pre generovanie sieťovej prevádzky lokalizačnej platformy a nástrojmi CI/CD Gitlab. Prínosom tejto práce je zrýchlenie vývoja, zaručenie kvality vyvijaného softwaru a predstavenie spôsobu ako platformu pre lokalizáciu v reálnom čase testovať.