Environmental Context Detection for Adaptive Navigation using GNSS Measurements from a Smartphone

The signals available for navigation depend on the environment. To operate reliably in a wide range of different environments, a navigation system is required to adopt different techniques based on the environmental contexts. In this paper, an environmental context detection framework is proposed, building the foundation of a context adaptive navigation system. Different land environments are categorized into indoor, urban, and open-sky environments based on how Global Navigation Satellite System (GNSS) positioning performs in these environments. Indoor and outdoor environments are first detected based on the availability and strength of GNSS signals using a hidden Markov model. Then the further classification of outdoor environments into urban and open-sky is investigated. Pseudorange residuals are extracted from raw GNSS measurements in a smartphone and used for classification in a fuzzy inference system alongside the signal strength data. Practical test results under different kinds of environments demonstrate an overall 88.2 percent detection accuracy

Expanding Navigation Systems by Integrating It with Advanced Technologies

Navigation systems provide the optimized route from one location to another. It is mainly assisted by external technologies such as Global Positioning System (GPS) and satellite-based radio navigation systems. GPS has many advantages such as high accuracy, available anywhere, reliable, and self-calibrated. However, GPS is limited to outdoor operations. The practice of combining different sources of data to improve the overall outcome is commonly used in various domains. GIS is already integrated with GPS to provide the visualization and realization aspects of a given location. Internet of things (IoT) is a growing domain, where embedded sensors are connected to the Internet and so IoT improves existing navigation systems and expands its capabilities. This chapter proposes a framework based on the integration of GPS, GIS, IoT, and mobile communications to provide a comprehensive and accurate navigation solution. In the next section, we outline the limitations of GPS, and then we describe the integration of GIS, smartphones, and GPS to enable its use in mobile applications. For the rest of this chapter, we introduce various navigation implementations using alternate technologies integrated with GPS or operated as standalone devices

Context-Aware System for Indoor Localization

User location is an important information to provide personalized service in any domain of interest. In this paper, we present a context-aware system to find location of a user at office domain. Hence, smartphone of the user transmits Wi-Fi signal and our system identifies the user by matching MAC address of the smartphone. Wi-Fi signal strength is used to calculate the distance of user from office room. Additionally, PIR sensor value and office time are used to increase localization accuracy as well as minimize the conflict of user location. Raspberry pi 3, a low-cost embedded platform, is used to collect and process sensed information, generate low-level context, and reason user location from available contexts. Demonstration result of our system shows an excellent performance within our domain of interest

Applications across Co-located Devices

We live surrounded by many computing devices. However, their presence has yet to be fully explored to create a richer ubiquitous computing environment. There is an opportunity to take better advantage of those devices by combining them into a unified user experience. To realize this vision, we studied and explored the use of a framework, which provides the tools and abstractions needed to develop applications that distribute UI components across co-located devices. The framework comprises the following components: authentication and authorization services; a broker to sync information across multiple application instances; background services that gather the capabilities of the devices; and a library to integrate web applications with the broker, determine which components to show based on UI requirements and device capabilities, and that provides custom elements to manage the distribution of the UI components and the multiple application states. Collaboration between users is supported by sharing application states. An indoor positioning solution had to be developed in order to determine when devices are close to each other to trigger the automatic redistribution of UI components. The research questions that we set out to respond are presented along with the contributions that have been produced. Those contributions include a framework for crossdevice applications, an indoor positioning solution for pervasive indoor environments, prototypes, end-user studies and developer focused evaluation. To contextualize our research, we studied previous research work about cross-device applications, proxemic interactions and indoor positioning systems. We presented four application prototypes. The first three were used to perform studies to evaluate the user experience. The last one was used to study the developer experience provided by the framework. The results were largely positive with users showing preference towards using multiple devices under some circumstances. Developers were also able to grasp the concepts provided by the framework relatively well.Vivemos rodeados de dispositivos computacionais. No entanto, ainda não tiramos partido da sua presença para criar ambientes de computação ubíqua mais ricos. Existe uma oportunidade de combiná-los para criar uma experiência de utilizador unificada. Para realizar esta visão, estudámos e explorámos a utilização de uma framework que forneça ferramentas e abstrações que permitam o desenvolvimento de aplicações que distribuem os componentes da interface do utilizador por dispositivos co-localizados. A framework é composta por: serviços de autenticação e autorização; broker que sincroniza informação entre várias instâncias da aplicação; serviços que reúnem as capacidades dos dispositivos; e uma biblioteca para integrar aplicações web com o broker, determinar as componentes a mostrar com base nos requisitos da interface e nas capacidades dos dispositivos, e que disponibiliza elementos para gerir a distribuição dos componentes da interface e dos estados de aplicação. A colaboração entre utilizadores é suportada através da partilha dos estados de aplicação. Foi necessário desenvolver um sistema de posicionamento em interiores para determinar quando é que os dispositivos estão perto uns dos outros para despoletar a redistribuição automática dos componentes da interface. As questões de investigação inicialmente colocadas são apresentadas juntamente com as contribuições que foram produzidas. Essas contribuições incluem uma framework para aplicações multi-dispositivo, uma solução de posicionamento em interiores para computação ubíqua, protótipos, estudos com utilizadores finais e avaliação com programadores. Para contextualizar a nossa investigação, estudámos trabalhos anteriores sobre aplicações multi-dispositivo, interação proxémica e sistemas de posicionamento em interiores. Apresentámos quatro aplicações protótipo. As primeiras três foram utilizadas para avaliar a experiência de utilização. A última foi utilizada para estudar a experiência de desenvolvimento com a framework. Os resultados foram geralmente positivos, com os utilizadores a preferirem utilizar múltiplos dispositivos em certas circunstâncias. Os programadores também foram capazes de compreender a framework relativamente bem

Intelligent evacuation management systems: A review

Crowd and evacuation management have been active areas of research and study in the recent past. Various developments continue to take place in the process of efficient evacuation of crowds in mass gatherings. This article is intended to provide a review of intelligent evacuation management systems covering the aspects of crowd monitoring, crowd disaster prediction, evacuation modelling, and evacuation path guidelines. Soft computing approaches play a vital role in the design and deployment of intelligent evacuation applications pertaining to crowd control management. While the review deals with video and nonvideo based aspects of crowd monitoring and crowd disaster prediction, evacuation techniques are reviewed via the theme of soft computing, along with a brief review on the evacuation navigation path. We believe that this review will assist researchers in developing reliable automated evacuation systems that will help in ensuring the safety of the evacuees especially during emergency evacuation scenarios

Smart hierarchical WiFi localization system for indoors

Premio Extraordinario de Doctorado de la UAH en el año académico 2013-2014En los últimos años, el número de aplicaciones para smartphones y tablets ha crecido rápidamente. Muchas de estas aplicaciones hacen uso de las capacidades de localización de estos dispositivos. Para poder proporcionar su localización, es necesario identificar la posición del usuario de forma robusta y en tiempo real. Tradicionalmente, esta localización se ha realizado mediante el uso del GPS que proporciona posicionamiento preciso en exteriores. Desafortunadamente, su baja precisión en interiores imposibilita su uso. Para proporcionar localización en interiores se utilizan diferentes tecnologías. Entre ellas, la tecnología WiFi es una de las más usadas debido a sus importantes ventajas tales como la disponibilidad de puntos de acceso WiFi en la mayoría de edificios y que medir la señal WiFi no tiene coste, incluso en redes privadas. Desafortunadamente, también tiene algunas desventajas, ya que en interiores la señal es altamente dependiente de la estructura del edificio por lo que aparecen otros efectos no deseados, como el efecto multicamino o las variaciones de pequeña escala. Además, las redes WiFi están instaladas para maximizar la conectividad sin tener en cuenta su posible uso para localización, por lo que los entornos suelen estar altamente poblados de puntos de acceso, aumentando las interferencias co-canal, que causan variaciones en el nivel de señal recibido. El objetivo de esta tesis es la localización de dispositivos móviles en interiores utilizando como única información el nivel de señal recibido de los puntos de acceso existentes en el entorno. La meta final es desarrollar un sistema de localización WiFi para dispositivos móviles, que pueda ser utilizado en cualquier entorno y por cualquier dispositivo, en tiempo real. Para alcanzar este objetivo, se propone un sistema de localización jerárquico basado en clasificadores borrosos que realizará la localización en entornos descritos topológicamente. Este sistema proporcionará una localización robusta en diferentes escenarios, prestando especial atención a los entornos grandes. Para ello, el sistema diseñado crea una partición jerárquica del entorno usando K-Means. Después, el sistema de localización se entrena utilizando diferentes algoritmos de clasificación supervisada para localizar las nuevas medidas WiFi. Finalmente, se ha diseñado un sistema probabilístico para seguir la posición del dispositivo en movimiento utilizando un filtro Bayesiano. Este sistema se ha probado en un entorno real, con varias plantas, obteniendo un error medio total por debajo de los 3 metros