Finding ones way in unknown and unfamiliar environments is a common task. A number of tools ranging from paper maps to location-based services have been introduced to assist human navigation. Undoubtedly, car navigation systems can be considered the most successful example of location based services that widely gained user acceptance. However the concept of car navigation is not always (perhaps rarely) suitable for pedestrian navigation. Moreover, precise localization of moving objects indoors is not possible due to the absence of an absolute positioning method such as GPS. These make accurate indoor tracking and navigation an interesting problem to explore. Many of the methods of spatial analysis popular in outdoor applications can be used indoors. In particular, generation of the indoor navigation network can be an effective solution for a) improving the navigation experience inside complex indoor structures and b) enhancing the analysis of the indoor tracking data collected with existing positioning solutions. Such building models should be based on a graph representation and consist of the number of ‘nodes’ and ‘edges’, where ‘nodes’ correspond to the central position of the room and ‘edge’ represents the medial axis of the hallway polygons, which physically connects these rooms. Similar node-links should be applied stairs and elevators to connect building floors. To generate this model, I selected the campus of University of Saskatchewan as the study area and presented a method that creates an indoor navigation network using ESRI ArcGIS products. First, the proposed method automatically extracts geometry and topology of campus buildings and computes the distances among all entities to calculate the shortest path between them. The system navigates through the University campus and it helps locating classrooms, offices, or facilities. The calculation of the route is based on the Dijkstra algorithm, but could employ any network navigation algorithm. To show the advantage of the generated network, I present results of a study conducted in conjunction with the department of Computer Science. An experiment that included 37 participants was designed to collect the tracking data on a university campus to demonstrate how the incorporation of the indoor navigation model can improve the analysis of the indoor movement data. Based on the results of the study, it can be concluded that the generated indoor network can be applied to raw positioning data in order to improve accuracy, as well as be employed as a stand-alone tool for enhancing of the route guidance on a university campus, and by extension any large indoor space consisting of individual or multiple buildings.

Location tracking is of paramount importance to many applications such as healthcare, retail and navigation. Outdoor tracking can be easily implemented using the Global Positioning System (GPS). However, indoor tracking has been a difficult problem to tackle because GPS requires the line of sight to the satellites and therefore it does not work well in indoor environments. In this thesis, a high-precision indoor tracking system is proposed to identify, locate and track a person in an indoor room at a low cost. The proposed tracking system consists of three components: StepscanTM tiles, RFID and Kalman-filter based prediction. The StepscanTM tiles can generate precise location information. However, using StepscanTM tiles only in an indoor tracking system is too expensive because the manufacturing cost of each StepscanTM tile is very high. In the proposed system, StepscanTM tiles are deployed to cover a part of the indoor floor while RFID provides a full coverage. The location information from StepscanTM tiles and RFID is then used as inputs for our innovative prediction algorithm based on the Kalman filter, which consequently generates high-precision tracking results. The performance of the proposed system is investigated through extensive simulations. Our simulation results indicate that the proposed system increases the capability to track and locate a person by at least 24% (more than 50% in some cases), with errors ranging from 2.5% to 15%. Furthermore, the proposed system helps to reduce the cost of indoor tracking significantly. In terms of the number of StepscanTM tiles deployed in the system, a reduction of 7 to 25 tiles can be achieved in the scenarios under investigation. In terms of monetary cost, $21,000 to $75,000 can be saved for an indoor tracking system considered in our research.

The purpose of this thesis was to discover the Special Olympic floor hockey athletes' understanding of the coaches', teams' and players' goals, priorities and expectations. Traditionally, the viewpoint of the mentally retarded has been represented by professionals and parents on the "outside". The emphasis on the athletes' perspective focused on the "insider" point of view. The rationale was that the results might be beneficial in improving the leadership qualities of the B.C. Special Olympics floor hockey coach and in improving athlete/coach relationships, with the potential result of maximizing the personal growth, development and performance potential of athletes. The question posed was: do the coaches and athletes each have a theory of behaviour that is bound and defined by their respective cultures (the dominant culture and mental retardation subculture). The subjects consisted of approximately thirty members of a Special Olympic floor hockey team ranging in age from nineteen to forty six years. Four members were female and twenty six were male. They were studied ethnographically utilizing the techniques of participant observation and informal interview in varied settings. The study was conducted from early January through mid April, 1988, and consisted of three phases: orientation to establish rapport and to allow time to blend into the sport setting; observation/conversation and the more focused phase consisting of informal directed interviews. Data elicited revealed themes related to socialisation, stigma and sport culture. Socialisation and the dominant culture examined primary and secondary socialisation, social stock of knowledge and relevance structures. Impression management, front and back stage performances are strategies employed by the mentally retarded to manage tension. Sport culture is an avenue for the athletes to learn about the social stock of knowledge and the relevance structures of the dominant culture. Dealing with stigma is central in the daily lives of the mentally retarded and is a constant challenge because it is dependent on the interpretations of others...intersubjective reality. Passing and covering are two of the coping strategies utilized by the mentally retarded. Myths concerning the athletes emerged gradually, revealing that coaches and athletes each have a theory of behaviour that is bound and defined by their respective cultures. Of significance to Special Olympics is the value of uncovering and understanding dominant cultural assumptions and biases in the context of interacting with a subculture such as the Special Olympic athletes, potentially resulting in more effective athlete/coach interaction. / Education, Faculty of / Curriculum and Pedagogy (EDCP), Department of / Graduate

This item was digitized as part of the Million Books Project led by Carnegie Mellon University and supported by grants from the National Science Foundation (NSF). Cornell University coordinated the participation of land-grant and agricultural libraries in providing historical agricultural information for the digitization project; the University of Arizona Libraries, the College of Agriculture and Life Sciences, and the Office of Arid Lands Studies collaborated in the selection and provision of material for the digitization project.

In our day to day activity, imagine if you go to a museum, hospital or any kind of huge building. You need to find the best way to get into a specific depart- ment. It might be difficult to find the way even if you have the map of the building in your hand. Indoor positioning systems can be used to locate people or objects inside a building, using radio waves, signals, or other sensory information collected by a smartphone or tablet. Bluetooth Low Energy (BLE) beacons broadcast signals, and bluetooth devices, such as smartphones, can then receive these signals. BLE devices can take Received Signal Strength Indication (RSSI) information together with an algorithm to calculate the location of the user. This is a useful method for indoor environments when using Global Positioning System (GPS) is not an option [1]. In this project I tried to find a better solution for localization and navigation when GPS does not work. The focus of the project is to use communication be- tween smartphones and beacons, for guidance in inside environments, without using GPS. This thesis is about the applications I produced, which can be used for indoor localization and navigation. Using the applications, you can map any building such as university, hospital, museum, big mall etc. To map a building, you upload a map of the building and put waypoints where you placed beacons. Once mapping is done, you can log in to the web admin and put some informa- tion for each beacon. As a user, when outside a nearby mapped building, your phone can get notified (trough bluetooth), and you can download the user app, which includes the map of the building and shows your location. With the user app you can easily find your favorite places in the building and get information about place near you.

Yes / The advent of the Internet of Things has witnessed tremendous success in the application of wireless sensor networks and ubiquitous computing for diverse smart-based applications. The developed systems operate under different technologies using different methods to achieve their targeted goals. In this treatise, we carried out an inclusive survey on key indoor technologies and techniques, with to view to explore their various benefits, limitations, and areas for improvement. The mathematical formulation for simple localization problems is also presented. In addition, an empirical evaluation of the performance of these indoor technologies is carried out using a common generic metric of scalability, accuracy, complexity, robustness, energy-efficiency, cost and reliability. An empirical evaluation of performance of different RF-based technologies establishes the viability of Wi-Fi, RFID, UWB, Wi-Fi, Bluetooth, ZigBee, and Light over other indoor technologies for reliable IoT-based applications. Furthermore, the survey advocates hybridization of technologies as an effective approach to achieve reliable IoT-based indoor systems. The findings of the survey could be useful in the selection of appropriate indoor technologies for the development of reliable real-time indoor applications. The study could also be used as a reliable source for literature referencing on the subject of indoor location identification. / Supported in part by the Tertiary Education Trust Fund of the Federal Government of Nigeria, and in part by the European Union’s Horizon 2020 Research and Innovation Programme under Grant agreement H2020-MSCA-ITN-2016 SECRET-722424

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The Global Positioning System (GPS) is the most popular positioning system among some operational Global Navigation Satellite Systems (GNSS). However, GNSS suffer from accuracy deterioration and interruption of services in dense urban areas and are almost unavailable indoors. Although high-sensitivity receivers improve signal acquisition indoors, multipath is still be a challenging problem that affects accuracy especially indoors where a direct line of sight between transmitter and receiver almost never exist. Moreover, the wireless signal features are significantly jeopardized by obstacles and constructions indoors. To address these challenges, this research came in the context of proposing an alternative positioning system that is designed for GPS-denied environment and especially for indoors. Cramer-Rao Lower-Bound (CRLB) analysis was used to estimate the lower bound accuracy of different positioning methods indoors. Based on CRLB analysis, this research approached the wireless positioning problem indoors utilizing received signal strength (RSS) to achieve the following: 1) Developing new estimation methods to model the wireless RSS patterns in indoors. 2) Designing adaptive RSS-based wireless positioning methods for indoors. 3) Establishing a consistent framework for indoor wireless positioning systems. 4) Developing new methods to integrate inertial/odometer-based navigation systems with the developed wireless positioning methods for further improvements. The theoretical basis of the work was built on nonlinear stochastic estimation techniques including Particle Filtering, Gaussian Process Regression, Fast Orthogonal Search, Least-Squares, and Radial Basis Functions Neural Networks. All the proposed wireless positioning methods were developed and physically realized on Android-based smart-phones using the IEEE 802.11 WLANs (WiFi). In addition, successful integration with inertial/odometer sensors of mobile robots has been performed on embedded systems. Both theoretical analysis and experimental results showed significant improvements in modeling RSS indoors dynamically without offline training achieving a positioning accuracy of 1-3 meters. Sub-meter accuracy was achieved via integration with inertial/odometer sensors. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2013-03-25 16:11:59.518