Situational-Context for Virtually Modeling the Elderly

The generalized aging of the population is incrementing the pressure over, frequently overextended, healthcare systems. This situations is even worse in underdeveloped, sparsely populated regions like Extremadura in Spain or Alentejo in Portugal. In this paper we propose an initial approach to use the Situational-Context, a technique to seamlessly adapt Internet of Things systems to the needs and preferences of their users, for virtually modeling the elderly. These models could be used to enhance the elderly experience when using those kind of systems without raising the need for technical skills. The proposed virtual models will also be the basis for further eldercare innovations in sparsely populated regions

The influences of user generated ‘Big data’ on urban development

Cities are the nucleus for creativity and ideas, as it has all the potentials for people to work, explore and live. People always come to cities because they want to be part of something, this magnet in the cities created the problem of population (Ericsson: Thinking Cities in the Networked Society, 2012). Approximately 50% of world’s population lives in urban areas, a number which is expected to increase to nearly 60% by 2030. (Mutizwa-Mangiza ND, Arimah B C, Jensen I, Yemeru EA, Kinyanjui MK, 2011). According to the rapid change in cities’ population there exists a need to utilize intelligent prediction tools to deliver a better way of living. Smart cities provide an opportunity to connect people and places using innovative technologies that help in better city planning and management ( Khan, Anjum, Soomro, & Tahir, 2015). Data is never a new thing, but data sources are always in change. The internet made everything easier and more reachable. This wide range of technologies such as IOT (internet of things) and M2M (machine to machine) (Gartner, 2015), is believed to offer a new potential to deliver an analytical framework for urban optimization. The real value of such data is gained by new knowledge acquired by performing data analytics using various data mining, machine learning or statistical methods. According to this technologically mutated, data comes from weather channels, street security cameras, Facebook, Twitter, sensor networks, in-car devices, location-based smartphone apps, RFID tags, smart meters, among other sources (Hinssen, 2012). This massive amount of information that comes from real-time based tools, made the world in front of a new era of data called ‘Big Data’. However, turning an ocean of messy data into knowledge and wisdom is an extremely challenging task. The proposed paper will discuss the IOT developed frameworks which are used to improve cities infrastructure and their vital systems. Analyzing these frameworks will help developing a conceptual proposal of data visualizing software; with the aim of helping urban planners get a better and easier way to comprehend the usage of multi-data sources for city planning and management. The full control of data is an open challenge, however proposing the fundamental bases of framework with the ability to extend and having an application layer above would be very helpful for urban process shifting. The Egyptian case is our main scope to have a smarter city that provides an opportunity to connect people and places using innovative technologies

Estimation and Improvements of the Fundamental QoS in Networks with Random Topologies

The computer communication paradigm is moving towards the ubiquitous computing and Internet of Things (IoT). Small autonomous wirelessly networked devices are becoming more and more present in monitoring and automation of every human interaction with the environment, as well as in collecting various other information from the physical world. Applications, such as remote health monitoring, intelligent homes, early fire, volcano, and earthquake detection, traffic congestion prevention etc., are already present and all share the similar networking philosophy. An additional challenging for the scientific and engineering world is the appropriateness of the alike networks which are to be deployed in the inaccessible regions. These scenarios are typical in environmental and habitat monitoring and in military surveillance. Due to the environmental conditions, these networks can often only be deployed in some quasi-random way. This makes the application design challenging in the sense of coverage, connectivity, network lifetime and data dissemination. For the densely deployed networks, the random geometric graphs are often used to model the networking topology. This paper surveys some of the most important approaches and possibilities in modeling and improvement of coverage and connectivity in randomly deployed networks, with an accent on using the mobility in improving the network functionality

Estimation and Improvements of the Fundamental QoS in Networks with Random Topologies

The computer communication paradigm is moving towards the ubiquitous computing and Internet of Things (IoT). Small autonomous wirelessly networked devices are becoming more and more present in monitoring and automation of every human interaction with the environment, as well as in collecting various other information from the physical world. Applications, such as remote health monitoring, intelligent homes, early fire, volcano, and earthquake detection, traffic congestion prevention etc., are already present and all share the similar networking philosophy. An additional challenging for the scientific and engineering world is the appropriateness of the alike networks which are to be deployed in the inaccessible regions. These scenarios are typical in environmental and habitat monitoring and in military surveillance. Due to the environmental conditions, these networks can often only be deployed in some quasi-random way. This makes the application design challenging in the sense of coverage, connectivity, network lifetime and data dissemination. For the densely deployed networks, the random geometric graphs are often used to model the networking topology. This paper surveys some of the most important approaches and possibilities in modeling and improvement of co verage and connectivity in randomly deployed networks, with an accent on using the mobility in improving the network functionality

Internet of things: why we are not there yet

Twenty-one years past since Weiser’s vision of ubiquitous computing (UbiComp) has been written, and it is yet to be fully fulfilled despite of almost all the needed technologies already available. Still, the widespread interest in UbiComp and the results in some of its fields pose a question: why we are not there yet? It seems we miss the ‘octopus’ head. In this paper, we will try to depict the reasons why we are not there yet, from three different points of view: interaction media, device integration and applications

Modelagem Multiagentes de uma Infraestrutura Descentralizada para Aprendizagem Ubíqua

GLOBAL é uma infraestrutura descentralizada para ambientes de aprendizagem ubíqua, baseada em agentes de software. A partir da extensão dos seus agentes ou adição de novos, a infraestrutura pode ser especializada para a criação de ambientes de aprendizagem ubíqua. Este artigo contribui apresentando a modelagem da infraestrutura através de uma metodologia multiagentes. Nesse trabalho, GLOBAL foi completamente modelada usando a metodologia Prometheus. Além disso, o artigo discute como os agentes foram implementados e como foram integrados a um sistema dedicado à colaboração em ambientes de aprendizagem ubíqua

Mobile Sound Recognition for the Deaf and Hard of Hearing

Human perception of surrounding events is strongly dependent on audio cues. Thus, acoustic insulation can seriously impact situational awareness. We present an exploratory study in the domain of assistive computing, eliciting requirements and presenting solutions to problems found in the development of an environmental sound recognition system, which aims to assist deaf and hard of hearing people in the perception of sounds. To take advantage of smartphones computational ubiquity, we propose a system that executes all processing on the device itself, from audio features extraction to recognition and visual presentation of results. Our application also presents the confidence level of the classification to the user. A test of the system conducted with deaf users provided important and inspiring feedback from participants.Comment: 25 pages, 8 figure