Målet med det här arbetet har varit att ta fram en Androidapplikation som kan spåra användaren och ge information om hur användaren rört sig med tid, distans altitud och hastighet. Applikationen ska vara individuellt fungerande men det stora syftet är att den ska fungera som en av tre delar i en större applikation med fler funktioner för de som är ute i skogen och rör på sig. Då inte alla telefoner har en inbyggd stegräknare kommer en undersökning göras för att se vilken sensor som lämpar sig bäst för att räkna steg och sedan använda den i applikationen. Resultatet blev en fungerande applikation som spårar användaren med hjälp av GPS, räknar antalet steg med antingen den inbyggda stegräknaren eller med hjälp av gyroskopet som visade sig vara den mest lämpade sensorn att räkna steg med. Utöver det så presenteras information om tid, distans och vilken altitud användaren rört sig på. All information kan sparas och användaren kan scrolla i en lista med sparade rutter.

När ett mobilspel använder sig av GPS-koordinater för att positionera användaren kan det uppstå problem vid eventuella GPS-bortfall. En del spel hanterar det genom att frysa spelet till dess att GPS-kontakten kommer tillbaka. I detta arbete har möjligheten att istället positionera användaren med telefonens inbyggda sensorer undersökts. Detta då tanken är att en offline-positionering skall kunna ta över vid GPS-skuggor för att skapa jämnare gameplay för användaren. För att avgöra hur väl offline-positioneringen fungerade i jämförelse med GPS-positioneringen har en rutt tagits. Efter det räknades offline-positioneringens koordinater om till GPS-koordinater så att de kunde jämföras med de GPS-koordinater som kom från GPS:en. I slutändan blev skillnaden stor mellan de två olika positioneringarna. Så pass stor att resultatet i sig blev oanvändbart. Det intressanta ligger dock i att resultatet gav indikationer på att en offline-positionering likt den som detta arbete försöka skapa är möjligt.

Doctorat en sciences appliquées / info:eu-repo/semantics/nonPublished

In this paper, an asymmetric compact multiband slot antenna is proposed for global positioning system (GPS), worldwide interoperability for microwave access (WiMAX), and wireless area network (WLAN) applications. The top plane, a ground is composed of a rectangular slot with a trapezoidal-like stub, an inverted U-shaped slot at the right side of the rectangular slot, an inverted L-shaped slot at the left side of the rectangular slot, and three stubs. The proposed antenna is fed by an asymmetric cross-parasitic strip on the bottom plane. By properly designing the slots and stubs, four resonant frequency bands are achieved with -10 dB reflection coefficient bandwidths of 50 MHz, 400 MHz, 390 MHz, and 830 MHz in the 1.57 GHz GPS band, 2.4 GHz WLAN band, 3.5 GHz WiMAX band, and 5.5 GHz WLAN bands, respectively. The antenna has a total compact size of 13 mm x 32 mm x 0.8 mm. Simulated and measured results indicate that the proposed antenna has sufficient bandwidth and good radiation performance in each band.

Road traffic signs provide instructions, warning information, to regulate driver behavior. In addition, these signs provide a reliable guarantee for safe and convenient driving. The Traffic Sign Detection and Recognition (TSDR) system is one of the primary applications for Advanced Driver Assistance Systems (ADAS). TSDR has obtained a great deal of attention over the recent years. But, it is still a challenging field of image processing. In this thesis, we first created our own dataset for North American Traffic Signs, which is still being updated. We then decided to choose Histogram Orientation Gradients (HOG) and Support Vector Machines (SVMs) to build our system after comparing them with some other techniques. For better results, we tested different HOG parameters to find the best combination. After this, we developed a TSDR system using HOG, SVM and our new color information extraction algorithm. To reduce time-consumption, we used the Maximally Stable Extremal Region (MSER) to replace the HOG and SVM detection stage. In addition, we developed a new approach based on Global Positioning System (GPS) information other than image processing. At last, we tested these three systems; the results show that all of them can recognize traffic signs with a good accuracy rate. The MSER based system is faster than the one using only HOG and SVM; and, the GPS based system is even faster than the MSER based system.

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Ciência da Computação, Florianópolis, 2016. / Made available in DSpace on 2016-09-20T04:05:20Z (GMT). No. of bitstreams: 1 341079.pdf: 3720669 bytes, checksum: 5b6f1fa58f095d53e8e517f2a5b26b14 (MD5) Previous issue date: 2016 / Dispositivos como smartphones e navegadores GPS são muito populares. Estes equipamentos podem armazenar a localização de um objeto associada ao respectivo tempo, gerando um novo tipo de dado, chamado de trajetórias de objetos móveis. Com esses dados e possível descobrir vários padrões interessantes, entre eles o padrão encontro, permitindo inferir o grau de relacionamento entre os objetos que se encontram. Este trabalho propõe um método para inferir o grau de relacionamento entre objetos através dos encontros das suas trajetórias. Primeiramente,os encontros são detectados pelo algoritmo Being Together com base em uma nova definição, que considera todo o tempo em que os objetos estão próximos no tempo e no espaço, independentemente se estão parados ou em movimento. A partir de medidas baseadas na duração, frequência e área dos encontros são propostos os algoritmos MOREe MORE + +. Os algoritmos foram avaliados em experimentos com dados reais de trajetórias e mostram que os encontros e os respectivos relacionamentos são detectados corretamente.<br> / Abstract: Devices like smart phones and GPS navigators are very popular nowadays.These equipments can save the location of an object with an associated time, generating a new kind of data, called trajectories of moving objects. With these data it is possible to discover several interesting patterns, among which is the interaction between individuals, allowing to infer their relationship. This work proposes a method to infer the relationship degree between moving objects from their encounters. First,the encounters are detected by the algorithm Being Together based on a new denition that considers the entire time that objects are closein time and space, regardless of whether they are stopped or moving. The relationship degree is calculated using measures based on the duration, frequency and area of encounters, through the algorithms MORE and MORE + +. The algorithms were evaluated in experiments withreal datasets, and show that the meetings and their relationships are correctly detected.

The intent of this master’s thesis is to look for the best solution of finding lost items of everyday use. Described solution is based on GPS for outdoor and Bluetooth Low Energy for indoor localization. User of this system will be able to find his/her lost items using smartphone application.

This thesis deals with design and implementation of collecting data from GPS device. The proposed solution provides storage of the current GPS information in NMEA standard, where each sentence of this standard are stored in XML le. Record performs GPS device based on Windows Mobile 6.1 system, which communicates with built-in module and the data are stored in XML format. Thus, stored data is interpreted using Interpret GPS data, which uses Google Maps to display information about the track.

This master’s thesis is focused on problems of monitoring GSM network using a mobile phone. Problems are analyzed on a theoretic basis with a description of available network parameters. Then the thesis offers a description of existing application environments providing a user with given data about the network. The main part of this work describes a development of application compiling queue data from mobile network and GPS, and creates output data illustrating signal strength in selected areas. The work also includes extensive measuring in select areas together with an evaluation of the processed data.

The thesis deals with adding new parts to program for measuring data rates in mobile communications. New program parts are used for analyzing web pages and HTTP protocol, recieving position data from GPS reciever and for creating automated measuring sequences.