6,300 research outputs found
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
Smart Computing and Sensing Technologies for Animal Welfare: A Systematic Review
Animals play a profoundly important and intricate role in our lives today.
Dogs have been human companions for thousands of years, but they now work
closely with us to assist the disabled, and in combat and search and rescue
situations. Farm animals are a critical part of the global food supply chain,
and there is increasing consumer interest in organically fed and humanely
raised livestock, and how it impacts our health and environmental footprint.
Wild animals are threatened with extinction by human induced factors, and
shrinking and compromised habitat. This review sets the goal to systematically
survey the existing literature in smart computing and sensing technologies for
domestic, farm and wild animal welfare. We use the notion of \emph{animal
welfare} in broad terms, to review the technologies for assessing whether
animals are healthy, free of pain and suffering, and also positively stimulated
in their environment. Also the notion of \emph{smart computing and sensing} is
used in broad terms, to refer to computing and sensing systems that are not
isolated but interconnected with communication networks, and capable of remote
data collection, processing, exchange and analysis. We review smart
technologies for domestic animals, indoor and outdoor animal farming, as well
as animals in the wild and zoos. The findings of this review are expected to
motivate future research and contribute to data, information and communication
management as well as policy for animal welfare
Multi-camera cooperative scene interpretation
In our society, video processing has become a convenient and widely used tool to assist, protect and simplify the daily life of people in areas such as surveillance and video conferencing. The growing number of cameras, the handling and analysis of these vast amounts of video data enable the development of multi-camera applications that cooperatively use multiple sensors. In many applications, bandwidth constraints, privacy issues, and difficulties in storing and analyzing large amounts of video data make applications costly and technically challenging. In this thesis, we deploy techniques ranging from low-level to high-level approaches, specifically designed for multi-camera networks. As a low-level approach, we designed a novel low-level foreground detection algorithm for real-time tracking applications, concentrating on difficult and changing illumination conditions. The main part of this dissertation focuses on a detailed analysis of two novel state-of-the-art real-time tracking approaches: a multi-camera tracking approach based on occupancy maps and a distributed multi-camera tracking approach with a feedback loop. As a high-level application we propose an approach to understand the dynamics in meetings - so called, smart meetings - using a multi-camera setup, consisting of fixed ambient and portable close-up cameras. For all method, we provided qualitative and quantitative results on several experiments, compared to state-of-the-art methods
Advances in Stereo Vision
Stereopsis is a vision process whose geometrical foundation has been known for a long time, ever since the experiments by Wheatstone, in the 19th century. Nevertheless, its inner workings in biological organisms, as well as its emulation by computer systems, have proven elusive, and stereo vision remains a very active and challenging area of research nowadays. In this volume we have attempted to present a limited but relevant sample of the work being carried out in stereo vision, covering significant aspects both from the applied and from the theoretical standpoints
The Challenge of Protecting Transit and Passenger Rail: Understanding How Security Works Against Terrorism
Terrorists see transit and passenger rail as an attractive target. Designed for public convenience, trains and stations offer terrorists easy access to crowds of people in confined environments where there are minimal security risks and attacks can cause high casualties. This report examines the unique attributes of the terrorist threat, how security measures against terrorism have evolved over the years, and their overall effectiveness.
Does security work? Empirical evidence is hard to come by. Terrorist incidents are statistically rare and random, making it difficult to discern effects. The fact that terrorists focus most of their attacks on targets with little or no security suggests that security influences their choice of targets. Increased security does not reduce terrorism overall, but appears to push terrorists toward softer targets. These indirect effects are visible only over long periods of time.
Public surface transportation poses unique challenges. It is not easy to increase security without causing inconvenience, unreasonably slowing travel times, adding significant costs, and creating vulnerable queues of people waiting to pass through security checkpoints. This has compelled rail operators to explore other options: enlisting passengers and staff in alerting authorities to suspicious objects or behavior, random passenger screening, designing new stations to facilitate surveillance and reduce potential casualties from explosions or fire, and ensuring rapid intervention
An information theoretical approach to crowd simulation
Crowd constitutes a critical component in many virtual environment and entertainment applications. In this thesis, we propose methods to solve two distinct problems in crowd simulation domain; automatic camera control and adaptive behavioral modeling. As the basis of our methods, we develop a framework which uses information theoretical concepts to automatically construct analytical maps of crowd's locomotion, which are called behavior maps. The developed framework contains a probabilistic model of the scene to build behavior maps. In the first part of this thesis, we propose a novel automatic camera control technique which utilizes behavior maps to find interest points which represent either characteristic behaviors of the crowd or novel events occurring in the scene. The camera is updated accordingly to display selected interest points. In the second part of this thesis, we propose a novel behavioral model which uses behavior maps to control agents' behavior adaptively with agent-crowd interaction formulations. Our model can be integrated into crowd simulators and enhance their behavioral complexity. We made comparative analyses of the presented behavior model with measured crowd data and two agent-based crowd simulators
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