Desenvolvimento de aplicação para posicionamento indoor por meio das redes wifi em ambientes internos

Orientadora: Dra. Luciene Stamato DelazariDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências da Terra, Programa de Pós-Graduação em Ciências Geodésicas. Defesa : Curitiba, 08/02/2019Inclui referências: p.122-131Área de concentração: CartografiaResumo: No ambiente interno a navegação de um usuário é baseada em seu conhecimento do local ou com base em pontos de referências que encontramse no ambiente, isto pode ser assistido por sistemas que forneçam a posição do usuário. Neste tipo de ambiente, deve-se usar um Sistema de Posicionamento Interno (IPS), sendo que os IPS mais usados são os que utilizam a tecnologia WIFI, já que encontra-se implantada na maioria dos prédios e dispositivos móveis atuais, tem um padrão de transmissão e infraestrutura estabelecida. Nesta pesquisa foi desenvolvida uma solução de código aberto para um IPS com a tecnologia WIFI em um dispositivo móvel com sistema operacional android, no contexto de aplicação UFPR CampusMap, que corresponde a um sistema desenvolvido pelo grupo de pesquisa de Cartografia e SIG da Universidade Federal do Paraná (UFPR), que tem por objetivo mapear os ambientes externos e internos dos diferentes campus da UFPR, o sistema atual corresponde a uma aplicação web e não tem disponível a funcionalidade do posicionamento. Para gerar a solução, foram feitos estudos com respeito ao Received Signal Strength Indicator (RSSI), e como este varia com respeito à distância, concluindo que este diminui com o aumento da distância, e devido aos fatores que o interferem deve ser modelado, para melhorar a qualidade do posicionamento obtido com base no RSSI. Além disso, foi avaliado o posicionamento no modo estático e cinemático para as técnicas do centróide, centróide ponderado e da trilateração, obtendo como acurácias médias 10,43; 7,39 e 8,38 metros respectivamente, com isso foi escolhida a técnica do centróide ponderado como a técnica para ser empregada na solução. Finalmente, foi avaliada a solução enquanto a detecção do prédio, andar e sala, concluindo que o aplicativo poderia ser utilizado para auxiliar ao usuário na sua localização, já que tem uma certeza de 100% na detecção do prédio e 79% do andar. Os resultados apontam à viabilidade de desenvolvimento e a possibilidade de gerar interfaces gráficas para dados geográficos em dispositivos móveis, que permitam uma melhor representação e interação entre o usuário e o ambiente interno. Palavras-chave: Posicionamento interno. Redes WIFI. Código aberto. Android.Abstract: In the indoor environment, a user's navigation is based on knowledge of the place or based on reference points found in the environment, this can be assisted by systems that provide the user's position. In this type of environment, one should use an Indoor Positioning System (IPS), the most used IPS are those that use WIFI technology, since it is implanted in most of the buildings and current mobile devices, it has a transmission pattern and established infrastructure. In this research was developed an open source solution for an IPS with this technology in a smartphone with android operating system, in the context of the UFPR Campus Map application, which corresponds to a system developed by the Cartography and GIS research group of the Federal University of Paraná (UFPR), which aims to map the indoor and outdoor environments of the different UFPR campus, the system corresponds to a web application and has no positioning functionality available. In order to generate the solution, studies were conducted regarding the Received Signal Strength Indicator (RSSI), how it varies with respect to distance, concluding that it decreases with increasing distance, and because of the factors that interfere in it must be modeled, to improve the quality of the positioning obtained from RSSI. In addition, the positioning in the static and kinematic mode was evaluated for the centroid, weighted centroid and trilateration techniques, obtaining as accuracy 10.43; 7.39 and 8.38 meters respectively, with this chose the weighted centroid technique as the technique to be employed in the solution. Finally, the solution was evaluated in detecting the building, floor and room, concluding that the application could be used to assist the user in its location, since it has a certainty of 100% in the detection of the building and 79% of the floor. The results point to the feasibility of development and the possibility of generating graphical interfaces for geographic data in mobile devices, allowing a better representation and interaction between the user and the indoor environment. Key-words: Indoor positioning. WIFI networks. Open source code. Android

Signal modelling based scalable hybrid Wi-Fi indoor positioning system

Location based services (LBS) such as advertising, navigation and social media require a mobile device to be aware of its location anywhere. Global Positioning System (GPS) is accurate outdoors. However, in case of indoor environments, GPS fails to provide a location due to non-line of sight. Even in cases where GPS does manage to get a position fix indoors, it is largely inaccurate due to interference of indoor environment. Wi-Fi based indoor positioning offers best solution indoors, due to wide usage of Wi-Fi for internet access. Wi-Fi based indoor positioning systems are widely based on two techniques, first Lateration which uses distances estimated based on signal properties such as RSS (Received Signal Strength) and second, Fingerprint matching of data collected in offline phase. The accuracy of estimated position using Lateration techniques is lower compared to fingerprinting techniques. However, Fingerprinting techniques require storing a large amount of data and are also computationally intensive. Another drawback of systems based on fingerprinting techniques is that they are not scalable. As the system is scaled up, the database required to be maintained for fingerprinting techniques increases significantly. Lateration techniques also have challenges with coordinate system used in a scaled-up system. This thesis proposes a new scalable positioning system which combines the two techniques and reduces the amount of data to be stored, but also provides accuracy close to fingerprinting techniques. Data collected during the offline/calibration phase is processed by dividing the test area into blocks and then stored for use during online/positioning phase. During positioning phase, processed data is used to identify the block first and then lateration techniques are used to refine the estimated location. The current system reduces the data to be stored by a factor of 20. And the 50th percentile accuracy with this novel system is 4.8m, while fingerprint system accuracy was 2.8m using same data. The significant reduction in database size and lower computational intensity benefits some of the applications like location-based search engines even with slightly lower performance in terms of accuracy