The Mundane Computer: Non-Technical Design Challenges Facing Ubiquitous Computing and Ambient Intelligence

Interdisciplinary collaboration, to include those who are not natural scientists, engineers and computer scientists, is inherent in the idea of ubiquitous computing, as formulated by Mark Weiser in the late 1980s and early 1990s. However, ubiquitous computing has remained largely a computer science and engineering concept, and its non-technical side remains relatively underdeveloped. The aim of the article is, first, to clarify the kind of interdisciplinary collaboration envisaged by Weiser. Second, the difficulties of understanding the everyday and weaving ubiquitous technologies into the fabric of everyday life until they are indistinguishable from it, as conceived by Weiser, are explored. The contributions of Anne Galloway, Paul Dourish and Philip Agre to creating an understanding of everyday life relevant to the development of ubiquitous computing are discussed, focusing on the notions of performative practice, embodied interaction and contextualisation. Third, it is argued that with the shift to the notion of ambient intelligence, the larger scale socio-economic and socio-political dimensions of context become more explicit, in contrast to the focus on the smaller scale anthropological study of social (mainly workplace) practices inherent in the concept of ubiquitous computing. This can be seen in the adoption of the concept of ambient intelligence within the European Union and in the focus on rebalancing (personal) privacy protection and (state) security in the wake of 11 September 2001. Fourth, the importance of adopting a futures-oriented approach to discussing the issues arising from the notions of ubiquitous computing and ambient intelligence is stressed, while the difficulty of trying to achieve societal foresight is acknowledged

Smart labs and social practice: social tools for pervasive laboratory workspaces: a position paper

The emergence of pervasive and ubiquitous computing stimulates a view of future work environments where sharing of information, data and knowledge is easy and commonplace, particularly in highly interactive settings. Much of the work in this area focuses on tool development to support activities such as data collection, data recording and sharing, and so on. We are interested in this kind of technical development, which is both challenging and essential for science communities. But we are also interested in a broader interpretation of knowledge sharing and the human/social side of tools we develop to support this. We are keen to know more about how groups of different kinds of scientists can make their work understandable and shareable with each other in a multidisciplinary setting. This is a complex task because boundaries and barriers can emerge between disciplines engendered by differences in discourses and practices, which may not easily translate into other discipline areas. In the worst case, there may be some hostility between disciplines, or at least doubt and scepticism. Nevertheless, sharing approaches to research, research expertise, data and methods across disciplines can be a very fruitful exercise, and encouragement to engage in this activity is particularly pertinent in the digital era. Issues of privacy and security are also key aspects – knowing when and how to release data or information to other groups is crucial to providing a safe environment for people to work, and there are several sensitivities to be explored here. In this paper we describe an evolving situation that captures many of these issues, which we aim to track longitudinally

Role of Artificial Intelligence (AI) art in care of ageing society: focus on dementia

open access articleBackground: Art enhances both physical and mental health wellbeing. The health benefits include reduction in blood pressure, heart rate, pain perception and briefer inpatient stays, as well as improvement of communication skills and self-esteem. In addition to these, people living with dementia benefit from reduction of their noncognitive, behavioural changes, enhancement of their cognitive capacities and being socially active. Methods: The current study represents a narrative general literature review on available studies and knowledge about contribution of Artificial Intelligence (AI) in creative arts. Results: We review AI visual arts technologies, and their potential for use among people with dementia and care, drawing on similar experiences to date from traditional art in dementia care. Conclusion: The virtual reality, installations and the psychedelic properties of the AI created art provide a new venue for more detailed research about its therapeutic use in dementia

Location-based and contextual mobile learning. A STELLAR Small-Scale Study

This study starts from several inputs that the partners have collected from previous and current running research projects and a workshop organised at the STELLAR Alpine Rendevous 2010. In the study, several steps have been taken, firstly a literature review and analysis of existing systems; secondly, mobile learning experts have been involved in a concept mapping study to identify the main challenges that can be solved via mobile learning; and thirdly, an identification of educational patterns based on these examples has been done. Out of this study the partners aim to develop an educational framework for contextual learning as a unifying approach in the field. Therefore one of our central research questions is: how can we investigate, theorise, model and support contextual learning

Future bathroom: A study of user-centred design principles affecting usability, safety and satisfaction in bathrooms for people living with disabilities

Research and development work relating to assistive technology 2010-11 (Department of Health) Presented to Parliament pursuant to Section 22 of the Chronically Sick and Disabled Persons Act 197

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Big data analytics:Computational intelligence techniques and application areas

Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment

Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.

Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems