Módulo de realidade aumentada para uma aplicação LBS

As aplicações móveis de serviços baseados na localização, denominados LBS (Location-based services), disponibilizam serviços ao utilizador baseadas na sua localização geográfica. Este tipo de serviços começou a surgir ainda na década de 90 e, à medida que o número de dispositivos móveis cresceu de forma exponencial, a sua oferta disparou consideravelmente. Existem várias áreas com aplicabilidade prática, mas o foco desta tese é a pesquisa e localização de pontos de interesse (POI’s). Através dos sensores que os dispositivos móveis atualmente disponibilizam, torna-se possível localizar a posição do utilizador e apresentar-lhe os pontos de interesse que estão situados em seu redor. No entanto essa informação isolada revela-se por vezes insuficiente, uma vez que esses pontos de interesse são à partida desconhecidos para o utilizador. Através do serviço coolplaces, um projeto que pretende dedicar-se à pesquisa e partilha de POI’s, podemos criar a nossa rede de amigos e de locais, beneficiando assim da respetiva informação de contexto de um determinado POI. As inovações tecnológicas permitiram também o aparecimento de aplicações de Realidade Aumentada nos dispositivos móveis, isto é, aplicações capazes de sobrepor imagens virtuais a visualizações do mundo real. Considerando a visualização de POI’s num dado ambiente, se encararmos a Realidade Aumentada como um potenciador da interação do utilizador com o mundo real, rapidamente identificamos as potencialidades da junção destes conceitos numa só aplicação. Sendo assim, o trabalho desenvolvido nesta tese pretende constituir um estudo sobre a implementação e desenvolvimento de um módulo de Realidade Aumentada para a aplicação móvel do serviço coolplaces, fazendo uso da tecnologia disponível no mercado de forma a proporcionar uma experiência inovadora e acrescentar valor à referida aplicação.The mobile applications based upon the user’s localization, named LBS (Location-based services), present services to the user based on the geographical position of his device. This type of services first appeared in the nineties (1990s) and, by the time mobile devices offer was increasing rapidly, they also thrived. There are plenty of areas with practical applicability of these services, but the main focus of this thesis is the search and localization of Points of Interest. With the use of the sensors that are a part of the mobile devices nowadays, it has become possible to locate the user’s position and display to him the POI’s in their surroundings. However this sole information may reveal itself insufficient since these POI’s may be unknown to the user. With the use of the coolplaces service, a project that intends to be a reference of search and share of POI data, we can make our own network of friends and POI’s, taking advantage of the context information of certain POI. The technological developments also allowed the uprise of Augmented Reality applications for the mobile devices, in other words, applications capable of overlap virtual images on top of real world representations. If we take under consideration the visualization of a POI in its environment, thinking of Augmented Reality as an enhancer of the user interaction with the real world, we quickly realize the potential of mixing these two concepts in one application. With that being said, the work developed in this thesis seeks to provide a study of the implementation and development of a Augmented Reality resource to be included and to enhance the mobile application of the coolplaces project, with the help of the technology that the market has to offer, in a way that can add value to the application while providing an exhilarating experience to the users

Landmark-assisted location and tracking in outdoor mobile network

Modern mobile devices integrating sensors, like accelerometers and cameras, are paving the way to the definition of high-quality and accurate geolocation solutions based on the informations acquired by these sensors, and data collected and managed by GSM/3G networks. In this paper, we present a technique that provides geolocation and mobility prediction of mobile devices, mixing the location information acquired with the GSM/3G infrastructure and the results of a landmark matching achieved thanks to the camera integrated on the mobile devices. Our geolocation approach is based on an advanced Time-Forwarding algorithm and on database correlation technique over Received Signal Strength Indication (RSSI) data, and integrates information produced by a landmark recognition infrastructure, to enhance algorithm performances in those areas with poor signal and low accurate geolocation. Performances of the algorithm are evaluated on real data from a complex urban environment

Landmark assisted Location and Tracking in Outdoor Mobile Network

International audienceLandmark assisted Location and Tracking in Outdoor Mobile Networ