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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10761/3928

Data: 25-gen-2016
Autori: La Delfa, Gaetano Carmelo
Titolo: Methodologies and Technologies for Indoor Localization: a Computer Vision Based Approach
Abstract: The massive diffusion of smartphones we are seeing in the last years, the growing interest for everything related to wearable devices and Internet of Things (IoT), the exponential rise of Location Based Services (LBS: services based on the position of the users and accessible through the device) has meant that technologies capable of determining the position of the user inside a specific context have taken a crucial role in the consumer sector. In outdoor environments, GPS (Global Positioning System) can be considered today as a standard de facto , while the localization and navigation in indoor environments still remains one of the technological challenges of the next years. Indoor Positioning Systems (IPS) have a remarkable importance in a lot of important market segments such as the retail sectors for con- textual advertising (commercial centers, supermarkets), touristic and transportation sectors (airports, museums), healthcare sectors (hospitals). Sometimes, in emergency situations they can make the difference between life and death. Even if actually doesn t exist a definitive solution as efficient and precise as GPS and with all its advantages, various approaches and methodologies has been proposed in the last years in scientific literature, and several technologies are appearing into the market. The researches have focused, rather than on realizing a general purpose IPS with high performances everywhere, on the development of a variety of solutions suitable for the specific place of deployment and which meet the specifics precision, security, invasiveness and cost requirements. In the first part of this doctoral dissertation, after an overview on the main methodologies used for locating a user in an indoor environment, we will analyze the state of the art and present some of the most interesting cases. We will focus particularly on approaches which utilize the smartphone s inertial sensors and 2D visual markers based computer vision techniques. In the second part of the dissertation we will propose our own solution to the indoor localization problem. Such solution consists in a visual markers system deployed onto the area of interest s floor and a step detection algorithm. We will compare the performances of three types of markers, taken from the scientific literature, from the point of view of the specifications required by the suggested solution, and choose the most better performing one. We will then propose a client - server architecture for managing the whole process of tracking the user inside a building, and present an implementation of the client, on the iOS platform. Finally in the last part of the dissertation, we will show the obtained results, and talk about the possible future works.
InArea 09 - Ingegneria industriale e dell'informazione

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