3,452 research outputs found
Smartphone-based user positioning in a multiple-user context with Wi-Fi and Bluetooth
In a multiuser context, the Bluetooth data from the smartphone could give an
approximation of the distance between users. Meanwhile, the Wi-Fi data can be
used to calculate the user's position directly. However, both the Wi-Fi-based
position outputs and Bluetooth-based distances are affected by some degree of
noise. In our work, we propose several approaches to combine the two types of
outputs for improving the tracking accuracy in the context of collaborative
positioning. The two proposed approaches attempt to build a model for measuring
the errors of the Bluetooth output and Wi-Fi output. In a non-temporal
approach, the model establishes the relationship in a specific interval of the
Bluetooth output and Wi-Fi output. In a temporal approach, the error
measurement model is expanded to include the time component between users'
movement. To evaluate the performance of the two approaches, we collected the
data from several multiuser scenarios in indoor environment. The results show
that the proposed approaches could reach a distance error around 3.0m for 75
percent of time, which outperforms the positioning results of the standard
Wi-Fi fingerprinting model.Comment: International Conference on Indoor Positioning and Indoor Navigation
(IPIN), Sep 2018, Nantes, Franc
Toward a unified PNT, Part 1: Complexity and context: Key challenges of multisensor positioning
The next generation of navigation and positioning systems must provide greater accuracy and reliability in a range of challenging environments to meet the needs of a variety of mission-critical applications. No single navigation technology is robust enough to meet these requirements on its own, so a multisensor solution is required. Known environmental features, such as signs, buildings, terrain height variation, and magnetic anomalies, may or may not be available for positioning. The system could be stationary, carried by a pedestrian, or on any type of land, sea, or air vehicle. Furthermore, for many applications, the environment and host behavior are subject to change. A multi-sensor solution is thus required. The expert knowledge problem is compounded by the fact that different modules in an integrated navigation system are often supplied by different organizations, who may be reluctant to share necessary design information if this is considered to be intellectual property that must be protected
Combining IoT and users’ profiles to provide contextualized information and services
Technological evolution has led to the emergence of a set of solutions suitable to support mobility and ubiquity scenarios. Wireless computing and mobile devices together with the miniaturization of sensors and actuators, which are now embedded in physical spaces, are today’s reality. This phenomenon opened the door to a set of opportunities for reengineering how we perceive a given fact or situation and how we act on it. With regard to the delivery of information to users of a given physical space, there is now the possibility of radically transforming the mechanisms of interaction between the space and the user, redesigning the entire experience of interaction. This change allows the user to see the physical space around him adapt to himself and provide him with contextualized and personalized information according to his profile of interest. This approach can improve the way we manage customer relationships in a given business context. This article presents an overview of the state of the art of intelligent spaces and analyzes the potential of indoor positioning systems and techniques, and proposes a conceptual model for the detection of users in physical spaces and the consequent adaptation of an intelligent physical space to provide information aligned with the user's interest profile and in accordance with their privacy rules.UNIAG, R&D unit funded by the FCT – Portuguese Foundation for the Development of Science and Technology,
Ministry of Science, Technology and Higher Education. UID/GES/4752/2019.info:eu-repo/semantics/publishedVersio
Survey and Systematization of Secure Device Pairing
Secure Device Pairing (SDP) schemes have been developed to facilitate secure
communications among smart devices, both personal mobile devices and Internet
of Things (IoT) devices. Comparison and assessment of SDP schemes is
troublesome, because each scheme makes different assumptions about out-of-band
channels and adversary models, and are driven by their particular use-cases. A
conceptual model that facilitates meaningful comparison among SDP schemes is
missing. We provide such a model. In this article, we survey and analyze a wide
range of SDP schemes that are described in the literature, including a number
that have been adopted as standards. A system model and consistent terminology
for SDP schemes are built on the foundation of this survey, which are then used
to classify existing SDP schemes into a taxonomy that, for the first time,
enables their meaningful comparison and analysis.The existing SDP schemes are
analyzed using this model, revealing common systemic security weaknesses among
the surveyed SDP schemes that should become priority areas for future SDP
research, such as improving the integration of privacy requirements into the
design of SDP schemes. Our results allow SDP scheme designers to create schemes
that are more easily comparable with one another, and to assist the prevention
of persisting the weaknesses common to the current generation of SDP schemes.Comment: 34 pages, 5 figures, 3 tables, accepted at IEEE Communications
Surveys & Tutorials 2017 (Volume: PP, Issue: 99
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
Indoor navigation for the visually impaired : enhancements through utilisation of the Internet of Things and deep learning
Wayfinding and navigation are essential aspects of independent living that heavily rely on the sense of vision. Walking in a complex building requires knowing exact location to find a suitable path to the desired destination, avoiding obstacles and monitoring orientation and movement along the route. People who do not have access to sight-dependent information, such as that provided by signage, maps and environmental cues, can encounter challenges in achieving these tasks independently. They can rely on assistance from others or maintain their independence by using assistive technologies and the resources provided by smart environments. Several solutions have adapted technological innovations to combat navigation in an indoor environment over the last few years. However, there remains a significant lack of a complete solution to aid the navigation requirements of visually impaired (VI) people. The use of a single technology cannot provide a solution to fulfil all the navigation difficulties faced. A hybrid solution using Internet of Things (IoT) devices and deep learning techniques to discern the patterns of an indoor environment may help VI people gain confidence to travel independently. This thesis aims to improve the independence and enhance the journey of VI people in an indoor setting with the proposed framework, using a smartphone. The thesis proposes a novel framework, Indoor-Nav, to provide a VI-friendly path to avoid obstacles and predict the user s position. The components include Ortho-PATH, Blue Dot for VI People (BVIP), and a deep learning-based indoor positioning model. The work establishes a novel collision-free pathfinding algorithm, Orth-PATH, to generate a VI-friendly path via sensing a grid-based indoor space. Further, to ensure correct movement, with the use of beacons and a smartphone, BVIP monitors the movements and relative position of the moving user. In dark areas without external devices, the research tests the feasibility of using sensory information from a smartphone with a pre-trained regression-based deep learning model to predict the user s absolute position. The work accomplishes a diverse range of simulations and experiments to confirm the performance and effectiveness of the proposed framework and its components. The results show that Indoor-Nav is the first type of pathfinding algorithm to provide a novel path to reflect the needs of VI people. The approach designs a path alongside walls, avoiding obstacles, and this research benchmarks the approach with other popular pathfinding algorithms. Further, this research develops a smartphone-based application to test the trajectories of a moving user in an indoor environment
- …