Micro-Futures

One of humankinds oldest quests has been to find the ‘elixir of life’, a mythical potion that, would grant the drinker immortality (and preferably, eternal youth!). One of the most famous tales of a search for this fabled tonic was that of the first emperor of a unified China, Qin Shi Huang (246 BC. to 210 BC), who, in the latter part of his life, is said to have become preoccupied with finding this illusive concoction. This article is presented at a workshop that is taking place in the heartland of what was Qin Shi Huang's empire (China), and touches on a modern day search for an elixir of life, this time a high-tech approach based on computers and artificial intelligence technology, that goes by the name of ‘The Technological Singularity’. However, as fascinating as a search for an elixir of life may be, the real motivation of this paper is to introduce micro-fiction as a methodology for capturing and communicating visions for scientific, business and societal innovations. To those end, The Technological Singularity is described and used as a means to illustrate the workings of micro SciFi-Prototyping (micro-SFPs)

Understanding and Personalising Smart City Services Using Machine Learning, the Internet-of-Things and Big Data

This paper explores the potential of Machine Learning (ML) and Artificial Intelligence (AI) to lever Internet of Things (IoT) and Big Data in the development of personalised services in Smart Cities. We do this by studying the performance of four well-known ML classification algorithms (Bayes Network (BN), Naïve Bayesian (NB), J48, and Nearest Neighbour (NN)) in correlating the effects of weather data (especially rainfall and temperature) on short journeys made by cyclists in London. The performance of the algorithms was assessed in terms of accuracy, trustworthy and speed. The data sets were provided by Transport for London (TfL) and the UK MetOffice. We employed a random sample of some 1,800,000 instances, comprising six individual datasets, which we analysed on the WEKA platform. The results revealed that there were a high degree of correlations between weather-based attributes and the Big Data being analysed. Notable observations were that, on average, the decision tree J48 algorithm performed best in terms of accuracy while the kNN IBK algorithm was the fastest to build models. Finally we suggest IoT Smart City applications that may benefit from our work

Using mixed-reality to develop smart environments

Smart homes, smart cars, smart classrooms are now a reality as the world becomes increasingly interconnected by ubiquitous computing technology. The next step is to interconnect such environments, however there are a number of significant barriers to advancing research in this area, most notably the lack of available environments, standards and tools etc. A possible solution is the use of simulated spaces, nevertheless as realistic as strive to make them, they are, at best, only approximations to the real spaces, with important differences such as utilising idealised rather than noisy sensor data. In this respect, an improvement to simulation is emulation, which uses specially adapted physical components to imitate real systems and environments. In this paper we present our work-in-progress towards the creation of a development tool for intelligent environments based on the interconnection of simulated, emulated and real intelligent spaces using a distributed model of mixed reality. To do so, we propose the use of physical/virtual components (xReality objects) able to be combined through a 3D graphical user interface, sharing real-time information. We present three scenarios of interconnected real and emulated spaces, used for education, achieving integration between real and virtual worlds

Interactions within distributed mixed reality collaborative environments

Traditionally virtual worlds have been regarded as standalone entities. However, the world moves fast towards a mixed reality collective environment, joining virtual and real world by incorporating accessible ubiquitous computing for people. Mobile and wearable computers act as a door to connect people to virtuality, e.g. The use of fitness/activity trackers, which collect real world information helping users to complement reality with virtuality improving their health and fitness. A different example is the use of mobile devices to connect people that do not share the same physical location in a virtual way, thought phone calls, videoconferences, chat and social media applications. These examples show that currently we live in two realities, processing information of both worlds in real time. Our video submission presents a work-in-progress research prototype towards the creation of a Blended Reality Distributed System, complementing the paper [1] submitted to the main track of the conference. The test bed scenario proposed is a mixed reality collaborative laboratory activity, performed by learners within geographically dispersed locations. The goal of the activity is to construct a small robot emphasising computing fundamentals. The video is available at: http://youtu.be/akKPHnDY9bw

Remote Mixed Reality Collaborative Laboratory Activities: Learning Activities within the InterReality Portal

Technology is changing our way to experience education from one-dimensional (physical) to multi-dimensional (physical and virtual) education using a diversity of resources such as web-based platforms (eLearning), videoconferences, eBooks and innovative technologies (e.g. mixed reality, virtual worlds, immersive technology, etc.). This represents bigger opportunities for universities and educational institutions to collaborate with partners from around the world and to be part of today's knowledge economy. This also enables greater opportunities to experience distance learning, modifying our experience of both space and time, changing specific spatial locations to ubiquitous locations and time as asynchronous/synchronous according to our necessities. The use of virtual and remote laboratory activities is an example of the application of some of these concepts. In this work-in-progress paper we propose a different approach to the integration of the physical and virtual world by creating remote mixed reality collaborative laboratory activities within an Inter Reality Portal learning environment, thereby extending our previous progress towards these goals. The learning goal of our mixed reality lab activity is to produce Internet-of-Things-based computer projects using combinations of Cross-Reality (xReality) and Virtual objects based on co-creative and collaborative interaction between geographically dispersed students. © 2012 IEEE

An Efficient Feature Selection Method for Activity Classification

Abstract-Feature selection is a key step for activity classification applications. Feature selection selects the most relevant features and considers how to use each of the selected features in the most suitable format. This paper proposes an efficient feature selection method that organizes multiple subsets of features in a multilayer, rather than utilizing all selected features together as one large feature set. The proposed method was evaluated by 13 subjects (aged from 23 to 50) in a lab environment. The experimental results illustrate that the large number of features (3 vs. 7 features) are not associated with high classification accuracy using a single Support Vector Machine (SVM) model (61.3% vs. 44.7%). However, the accuracy was improved significantly (83.1% vs. 44.7%), when the selected 7 features were organized as 3 subsets and used to classify 10 postures (9 motionless with 1 motion) in 3 layers via a hierarchical algorithm, which combined a rule-based algorithm with 3 independent SVM models