Context Aware Handover Algorithms for Mobile Positioning Systems

Abstract: This work proposes context aware handover algorithms for mobile positioning systems. The algorithms perform handover among positioning systems based on important contextual factors related to position determination with efficient use of battery. The proposed solution which consists of the algorithms is implemented in the form of an Android application named Locate@nav6. The performance of the proposed solution was tested in selected experimental areas. The handover performance was compared with other existing location applications. The proposed solution performed correct handover among positioning systems in 95% of cases studied while two other applications performed correct handover in only 50% of cases studied. Battery usage of the proposed solution is less than one third of the battery usage of two other applications. The analysis of the positioning error of the applications demonstrated that, the proposed solution is able to reduce positioning error indirectly by handing over the task of positioning to an appropriate positioning system. This kept the average error of positioning below 42.1 meters for Locate@nav6 while the average error for two other applications namely Google Latitude and Malaysia maps was between 92.7 and 171.13 meters

Context Aware Handover Algorithms For Mobile Positioning Systems

This work proposes context aware handover algorithms for mobile positioning systems. The algorithms perform handover among positioning systems based on important contextual factors related to position determination with efficient use of battery. The proposed solution is implemented in the form of an Android application named Locate@nav6. The performance of the proposed solution was tested in selected experimental areas. The handover performance was compared with other existing location applications. The proposed solution performed correct handover among positioning systems in 95 percent of cases studied while two other applications performed correct handover in only 50 percent of cases studied. Battery usage of the proposed solution is less than one third of the battery usage of two other applications. The analysis of the positioning error of the applications demonstrated that, the proposed solution is able to reduce positioning error indirectly by handing over the task of positioning to an appropriate positioning system. This kept the average error of positioning below 42.1 meters for Locate@nav6 while the average error for two other applications namely Google Latitude and Malaysia maps was between 92.7 and 171.13 meters

Performance Evaluation of Mobile U-Navigation based on GPS/WLAN Hybridization

This paper present our mobile u-navigation system. This approach utilizes hybridization of wireless local area network and Global Positioning System internal sensor which to receive signal strength from access point and the same time retrieve Global Navigation System Satellite signal. This positioning information will be switched based on type of environment in order to ensure the ubiquity of positioning system. Finally we present our results to illustrate the performance of the localization system for an indoor/ outdoor environment set-up.Comment: Journal of Convergence Information Technology(JCIT

Context Aware Handover Algorithms for Mobile Positioning Systems

Abstract: This work proposes context aware handover algorithms for mobile positioning systems. The algorithms perform handover among positioning systems based on important contextual factors related to position determination with efficient use of battery. The proposed solution which consists of the algorithms is implemented in the form of an Android application named Locate@nav6. The performance of the proposed solution was tested in selected experimental areas. The handover performance was compared with other existing location applications. The proposed solution performed correct handover among positioning systems in 95% of cases studied while two other applications performed correct handover in only 50% of cases studied. Battery usage of the proposed solution is less than one third of the battery usage of two other applications. The analysis of the positioning error of the applications demonstrated that, the proposed solution is able to reduce positioning error indirectly by handing over the task of positioning to an appropriate positioning system. This kept the average error of positioning below 42.1 meters for Locate@nav6 while the average error for two other applications namely Google Latitude and Malaysia maps was between 92.7 and 171.13 meters

Cooperative environment recognition utilizing UWB waveforms and CNNs

Cooperative navigation enhances localization performance and situational awareness in challenging conditions, such as in tactical and first responder operations. In this work we demonstrate how the waveform of the Ultra Wideband (UWB) signal used for ranging in cooperative navigation can also be used to detect the environment surrounding the user of the navigation system. Different environments affect the wave-form in different ways, and thus the received waveform contains features characteristic to the environment around the receiver. We show how the received UWB signal waveform can be used in a Convolutional Neural Network (CNN) in order to determine whether the user is outdoors, indoors or in a forest. The environment is recognized correctly more than 90% of the time. © 2020 German Institute of Navigation - DGON.Peer reviewe

Indoor localisation based on fusing WLAN and image data

In this paper we address the automatic identification of indoor locations using a combination of WLAN and image sensing. We demonstrate the effectiveness of combining the strengths of these two complementary modalities for very chal- lenging data. We describe a fusion approach that allows localising to a specific office within a building to a high degree of precision or to a location within that office with reasonable precision. As it can be orientated towards the needs and capabilities of a user based on context the method becomes useful for ambient assisted living applications

A mobile sensing solution for indoor and outdoor state detection

Abstract. One important research challenge in ubiquitous computing is determining a device’s indoor/outdoor environmental state. Particularly with modern smartphones, environmental information is important for enabling of new types of services and optimizing already existing functionalities. This thesis presents a tool for Android-powered smartphones called ContextIO for detecting the device’s indoor/outdoor state by combining different onboard sensors of the device itself. To develop ContextIO, we developed a plugin to AWARE mobile sensing framework. Together the plugin and its separate controller component collect rich environmental sensor data. The data analysis and ContextIO’s design considers collected data particularly about magnetometer, ambient light and GSM cellular signal strength. We manually derive thresholds in the data that can be used in combination to infer whether a device is indoor or outdoor. ContextIO uses the same thresholds to infer the state in real time. This thesis contributes an Android tool for inferring the device’s indoor/outdoor status, an open dataset that other researchers can use in their work and an analysis of the collected sensor data for environmental indoor/outdoor state detection.Tiivistelmä. Yksi jokapaikan tietotekniikan tutkimuskysymyksistä keskittyy selvittämään onko laitteen sijainti sisä- vai ulkotilassa. Etenkin uudet älypuhelimet pystyvät hyödyntämään tätä tietoa uudenlaisten palveluiden ja sovellusten kehittämisessä sekä vanhojen toiminnallisuuksien optimoinnissa. Tämä diplomityö esittelee Android-käyttöjärjestelmällä toimiville puhelimille suunnatun työkalun nimeltään ContextIO. Työkalu yhdistelee älypuhelimen sensorien tuottamaa tietoa ja havaitsee laitteen siirtymisen eri sijaintiin sisä- ja ulkotilojen suhteen. ContextIO:n suunnittelu ja kehitystyö perustuvat data-analyysiin, jonka data kerättiin AWARE-sensorialustan liitännäisellä sekä erillisellä nimeämistyökalulla. Data-analyysi keskittyy magnetometrin, valosensorin sekä GSM-kentän voimakkuuden hyödyntämiseen paikantamisessa. Kerätystä datasta määriteltiin raja-arvot, joita yhdistelemällä voidaan varsin luotettavasti todeta laitteen sijainti sisä- ja ulkotilojen suhteen. Nämä raja-arvot luovat perustan ContextIO:n reaaliaikaiselle laitteen sijainnin määrittämiselle. Tämän diplomityön pääasialliset tulokset ovat työkalu Android-pohjaisten älypuhelinten sijainnin määrittämiseen sisä- ja ulkotilojen suhteen, avoin datasetti, jota muut tutkijat voivat käyttää sekä sijainnin määrittämiseen keskittyvä data-analyysi

INDOOR LOCALIZATION AND TRACKING: METHODS, TECHNOLOGIES AND RESEARCH CHALLENGES

The paper presents a comprehensive survey of contemporary methods, technologies and systems for localization and tracking of moving objects in indoor environment and gives their comparison according to various criteria, such as accuracy, privacy, scalability and type of location data. Some representative examples of indoor LBS applications available on the market are presented that are based on reviewed localization technologies. The prominent research directions in this domain are categorized and discussed

Representaciones enriquecidas para la navegación indoor-outdoor en aplicaciones móviles

En este trabajo se presenta un modelo orientado a objetos que permite representar espacios enriquecidos. Un espacio enriquecido se define en nuestro modelo como una representación espacial, el cual posee al menos un punto de acceso (por ejemplo, una puerta), puede tener definido una red de circulación (sobre la que se calculan caminos) y puntos de interés. Eventualmente a un espacio enriquecido se le pueden definir sub-espacios enriquecidos. Se mostrará mediante un ejemplo como el modelo propuesto permite realizar cálculo de caminos a puntos de interés, brindando además el soporte necesario para asistir al usuario en la navegación indoor-outdoor.Presentado en el VIII Workshop Ingeniería de Software (WIS)Red de Universidades con Carreras en Informática (RedUNCI