Review of computer vision in intelligent environment design

This paper discusses and compares the use of vision based and non-vision based technologies in developing intelligent environments. By reviewing the related projects that use vision based techniques in intelligent environment design, the achieved functions, technical issues and drawbacks of those projects are discussed and summarized, and the potential solutions for future improvement are proposed, which leads to the prospective direction of my PhD research

Overcoming barriers and increasing independence: service robots for elderly and disabled people

This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

ANGELAH: A Framework for Assisting Elders At Home

The ever growing percentage of elderly people within modern societies poses welfare systems under relevant stress. In fact, partial and progressive loss of motor, sensorial, and/or cognitive skills renders elders unable to live autonomously, eventually leading to their hospitalization. This results in both relevant emotional and economic costs. Ubiquitous computing technologies can offer interesting opportunities for in-house safety and autonomy. However, existing systems partially address in-house safety requirements and typically focus on only elder monitoring and emergency detection. The paper presents ANGELAH, a middleware-level solution integrating both ”elder monitoring and emergency detection” solutions and networking solutions. ANGELAH has two main features: i) it enables efficient integration between a variety of sensors and actuators deployed at home for emergency detection and ii) provides a solid framework for creating and managing rescue teams composed of individuals willing to promptly assist elders in case of emergency situations. A prototype of ANGELAH, designed for a case study for helping elders with vision impairments, is developed and interesting results are obtained from both computer simulations and a real-network testbed

Image recognition-based architecture to enhance inclusive mobility of visually impaired people in smart and urban environments

The demographic growth that we have witnessed in recent years, which is expected to increase in the years to come, raises emerging challenges worldwide regarding urban mobility, both in transport and pedestrian movement. The sustainable development of cities is also intrinsically linked to urban planning and mobility strategies. The tasks of navigation and orientation in cities are something that we resort to today with great frequency, especially in unknown cities and places. Current navigation solutions refer to the precision aspect as a big challenge, especially between buildings in city centers. In this paper, we focus on the segment of visually impaired people and how they can obtain information about where they are when, for some reason, they have lost their orientation. Of course, the challenges are different and much more challenging in this situation and with this population segment. GPS, a technique widely used for navigation in outdoor environments, does not have the precision we need or the most beneficial type of content because the information that a visually impaired person needs when lost is not the name of the street or the coordinates but a reference point. Therefore, this paper includes the proposal of a conceptual architecture for outdoor positioning of visually impaired people using the Landmark Positioning approach.5311-8814-F0ED | Sara Maria da Cruz Maia de Oliveira PaivaN/

Novel development of distributed manufacturing monitoring systems to support high cost and complexity manufacturing

In the current manufacturing environment, characterized by diverse change sources (e.g. economical, technological, political, social) and integrated supply chains, success demands close cooperation and coordination between stakeholders and agility. Tools and systems based on software agents, intelligent products and virtual enterprises have been developed to achieve such demands but either because of: (i) focus on a single application; (ii) focus on a single product; (iii) separation between the product and its information; or (iv) focus on a single system characteristic (e.g. hardware, software, architecture, requirements) their use has been limited to trial or academic scenarios. In this thesis a reusable distributed manufacturing monitoring system for harsh environments, capable of addressing traceability and controllability requirements within stakeholders and across high cost and complexity supply chains is presented. [Continues.

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

Ambient intelligence: applications and privacy policies

Proceedings of: 12th International Conference on Practical Applications of Agents and Multi-Agent Systems, University of Salamanca (Spain), 4th-6th June, 2014. Workshop on Intelligent Systems for Context-based Information Fusion (ISCIF 2014)In this paper, we present a complete overview of Ambient Intelligence (AmI) focused in its applications, considering the involved domain and technologies. The applications include AmI at home, care of elderly and people with disabilities, healthcare, education, business, public services, leisure and entertainment. The aim of this survey of AmI’s applications is to show its socials and ethical implications and specially privacy issues. Intelligent Environments (IE) collect and process a massive amount of person-related and sensitive data. These data must ensure privacy of the users. An important concern in AmI's applications is privacy. Addressing design by privacy, an important challenge to consider is the development of an architecture that includes the different privacy policies and how can we fusion them in a specific application domain. Ensuring privacy in Intelligent Environments is a difficult problem to solve, as there are different perceptions of privacy and its role in computing for each user. In the so called ‘design by privacy’ we have to identify the relevant design issues that should be addressed for its developing. Here we present an approach to the dimensions to consider, in order to provide privacy in the design of Ambient Intelligence’s applications.This work has been supported in part by the projects: CAM “Contexts” (S2009/TIC-1485), MINECO “Falcon” (TEC2011-28626-C02-02), MINECO “Tease” (TEC2012-37832-C02-01)