The emergence of a global ubiquitous computing environment in which each of us routinely interacts with many thousands of interconnected computers embedded into the everyday world around us will transform the ways in which we work, travel, learn, entertain ourselves and socialise. Ubiquitous computing will be the engine that drives our future digital economy, stimulating new forms of digital business and transforming existing ones.However, ubiquitous computing also carries considerable risks in terms of societal acceptance and a lack of established models of innovation and wealth creation, so that unlocking its potential is far from straightforward. In order to ensure that the UK reaps the benefits of ubiquitous computing while avoiding its risks, we must address three fundamental challenges. First, we need to pursue a new technical research agenda for the widespread adoption of ubiquitous computing. Second, we must understand and design for an increasingly diverse population of users. Third, we need to establish new paths to innovation in digital business. Meeting these challenges requires a new generation of researchers with interdisciplinary skills in the technical and human centred aspects of ubiquitous computing and transferable skills in research, innovation and societal impact.Our doctoral training centre for Ubiquitous Computing in the Digital Economy will develop a cohort of interdisciplinary researchers who have been exposed to new research methods and paradigms within a creative and adventurous culture so as to provide the future leadership in research and knowledge transfer that is necessary to secure the transformative potential of ubiquitous computing for the UK digital economy. To achieve this we will work across traditional research boundaries; encourage students to adopt an end-to-end perspective on innovation; promote creativity and adventure in research; and place engagement with society, industry and key stakeholders at the core of our programme.Our proposal brings together a unique pool of researchers with extensive expertise in the technologies of ubiquitous and location based computing, user-centred design, societal understanding, and research and training in innovation and leadership. It also involves a wide spectrum of industry partners from across the value chain for ubiquitous computing, spanning positioning, communications, devices, middleware, databases, design, and our two driving market sectors of the creative industries and transportation.Our training programme is based on the approach of personalised pathways that develop individual students' interdisciplinary and transferable skills, and that produce a personal portfolio to showcase the skills and experience gained alongside the more traditional PhD thesis. It includes a flexible taught programme that emphasises student-led seminars, short-fat modules, training projects and e-learning as delivery mechanisms that are suited to PhD training; an industrial internship scheme under which students spend three months working at an industrial partner; and a PhD research project that builds on a proposal developed during the first year of training and that is supported by multiple supervisors from different disciplines with industry involvement. Our DTC will foster a community of researchers through a dedicated shared space, a programme of community building events, training for supervisors and well as students, funding for a student society, and an alumni programme.

The success of Web 2.0 and CGM is based on tapping into the social nature of human interactions, by making it possible for people to voice their opinion, become part of a virtual community and collaborate remotely. If we take micro-blogging as an example, the growth in Twitter visits between 2008 and 2009 was over 1,000% and it is projected that by 2010 around 10% of all internet users will be on Twitter. This unprecedented rise in the volume and importance of online content has resulted in companies and individuals spending ever increasing amounts of time trying to keep up with relevant CGM. It is estimated that 700 person hours per year is the absolute minimum that companies and public services need to spend on CGM monitoring, online user engagement, and discovery of new information. This fellowship is about helping people to cope with the resulting information overload, through automatic methods that are capable of adapting to individual's information seeking goals and summarising briefly the relevant media and thus supporting information interpretation and decision making. Automatic text summarisation is key to our goal and consists of compressing the meaning of text documents while preserving the relevant information contained within them. While there has been a lot of research on well-authored texts such as news, summarisation of social media is still in its infancy, with research focused on product reviews. A key experimental finding has been that due to the characteristics of social media (product reviews in particular) it is better first to abstract the relevant information from the different documents and sites and then to use natural language generation to create a fluent text based on this information.In this fellowship I will investigate and evaluate new machine learning methods for personalised, abstractive multi-document summarisation across different social media. For example, diachronic summaries that combine Twitter posts, blog articles, and Facebook wall messages on a given topic. In contrast to previous work, we will pursue an inter-disciplinary approach, which will help us study the social dimension of CGM summarisation and establish actual user needs. The second research challenge is that the algorithms need to be robust in the face of this noisy, jargon-full and dynamic content, as well as needing models capable of representing the contradictory and strongly temporal nature of CGM. A key novel contribution of our work is personalising the summaries, based on a model of user interests, goals, and social context. Issues such as trustworthiness, privacy, and online communities (with their hubs and authorities) will also play an important role. The fourth research challenge is to generate personalised abstractive summaries that can help users with sensemaking and content interpretation. An exciting element of my research will be in studying the different kinds of summaries that are useful for a variety of real users (companies, journalists, and the general public) through multi-disciplinary collaborations with the Press Association, British Telecom, the Oxford Internet Institute, and Sheffield's Department of Journalism. A key project deliverable will be a publicly available browser plugin that provides easy access to the automatically generated summaries. This will allow me to evaluate the project results with real users, on a large scale. It will also provide a new evaluation challenge for the Natural Language Generation community, as researchers will be able to compare their summarisers against those delivered by our open-source algorithms. Last but not least, the fellowship covers not only foundational multi-disciplinary research but it also tests the results in several Digital Economy pilot experiments involving commercial partners (The Press Association, British Telecom, Fizzback).

The extraordinary increase of wireless data traffic by smartphones and laptops, virtual reality, billions of IoTs or Industry 4.0 infrastructure need 5G, small cell densification and reduction of digital divide. High throughput connectivity everywhere is a fundamental requirement to support the growing data demand and the evolution of future wireless communication market. Affordable wireless networks with fibre data rate are needed. Wireless links with multi-gigabit (Gb/s) distribution at millimetre waves have been demonstrated up to 400 GHz. However, the strong atmosphere attenuation at the increase of frequency and limitations of the present semiconductor-based millimetre wave technology limit their potentiality. E-band wireless links with 2 GHz bandwidth and theoretical few Gb/s are already in the market, but large antenna footprint and low transmission power are probably preventing wider adoption. The portion of the spectrum above 100 GHz includes numerous wide bands which are presently unused, and could support tens of Gb/s, if adequate millimetre wave technology were available. In particular, the D-band (141 - 174.8) has about 28 GHz split in three sub-bands. The DLINK project aims to bring the UK at the forefront of millimetre wave wireless technology through the realisation of the first high capacity link at D-band with unprecedented performance, to provide 45Gb/s, over 1 km range, and with 99.99% availability in ITU rain zone K (typical of UK and Europe). The DLINK system includes a high power vacuum traveling wave tube (TWT) of new generation driven by a novel resonant tunnelling diode (RTD) transmitter with an integrated vector modulator. The system will be demonstrated in Frequency Division Duplex (FDD), with two bands of 10 GHz each to provide about 45 Gb/s data rate. The high performance of DLINK is enabled by traveling wave tubes as amplifiers, with about 10W output power, which is more than one order of magnitude than solid state amplifiers at the same frequency. The TWT working mechanism is based on the transfer of energy from a high energy electron beam, flowing in a waveguide with high level of vacuum, to the electric field generated by the input signal. No D-band TWTs are available in the market. Substantial challenges must be solved for an affordable microfabrication of mm-wave waveguides, due to small dimensions and three dimensional shapes. The transmitter will be an RTD oscillator with very low phase noise to support QAM modulation generated by an on-chip PIN diode vector modulator. The DLINK system includes two transmitters, one for each FDD channel, integrating a RTD oscillator/transmitter, a TWT and an antenna. For the first time, the property of a transmission link with 20 GHz bandwidth above 100 GHz will be investigated by field tests at BT. The DLINK project has a strong industry focus. It is a collaboration between Lancaster and Glasgow Universities with the strategic support of the wireless communication industry full chain, from devices to end users: IQE (semiconductor wafers), Filtronic (mm-wave links), Teledyne e2v (mm-wave TWT), Nokia (system manufacturer), Intel (chip manufacturer), BT (UK main network operator and end user). The high impact of the project will enable new architectures of wireless high capacity networks by mesh of high data rate links at mm-waves. The DLINK project has the ambition to fully contribute to "Connected Nation", one of the four Prosperous Outcomes and to benefit other numerous ambitions of the Prosperous Nation outcomes. DLINK involves researchers and PhD students of two leading research groups and a number of industry partners that will work together for the success of the project, with a long term strategy for future industry exploitation. A particular attention is devoted to growth of talent, improving the gender balance in the millimetre wave technology sector highlighting role models in the Lancaster and Glasgow teams.

The impact of road traffic on local air quality is a major public policy concern and has stimulated a substantial body of research aimed at improving underlying vehicle and traffic management technologies and informing public policy action. Recent work has begun to exploit the capability of a variety of vehicle-based, person-based and infrastructure-based sensor systems to collect real time data on important aspects of driver and traffic behaviour, vehicle emissions, pollutant dispersion, concentration and human exposure. The variety, pervasiveness and scale of these sensor data will increase significantly in the future as a result of technological developments that will enable sensors to become cheaper, smaller and lower in power consumption. This will open up enormous opportunities to improve our understanding of urban air pollution and hence improve urban air quality. However, handing the vast quantities of real time data that will be generated by these sensors will be a formidable task and will require the application of advanced forms computing, communication and positioning technologies and the development of ways of combining and interpreting many different forms of data. Technologies developed in EPSRC's e-Science research programme offer many of the tools necessary to meet these challenges. The aim of the PMESG project is to take these tools and by extending them where necessary in appropriate ways develop and demonstrate practical applications of e-Science technologies to enable researchers and practitioners to coherently combine data from disparate environmental sensors and to develop models that could lead to improved urban air quality. The PMESG project is led by Imperial College London, and comprises a consortium of partners drawn from the Universities of Cambridge, Southampton, Newcastle and Leeds who will work closely with one another and with a number of major industrial partners and local authorities. Real applications will be carried out in London, Cambridge, Gateshead and Leicester which will build on the Universities' existing collaborative arrangements with the relevant local authorities in each site and will draw on substantial existing data resources, sensor networks and ongoing EPSRC and industrially funded research activities. These applications will address important problems that to date have been difficult or impossible for scientists and engineers working is this area of approach, due to a lack or relevant data. These problems are of three main types; (i) measuring human exposure to pollutants, (ii) the validation of various detailed models of traffic behaviour and pollutant emission and dispersion and (iii) the development of transport network management and control strategies that take account not just of traffic but also air quality impacts. The various case studies will look at different aspects of these questions and use a variety of different types of sensor systems to do so. In particular, the existing sensor networks in each city will be enhanced by the selective deployment of a number of new sensor types (both roadside and on-vehicle/person) to increase the diversity of sensor inputs. The e-Science technologies will be highly general in nature meaning that will have applications not only in transport and air quality management but also in many other fields that generate large volume of real time location-specific sensor data.Each institution participating in this project will be submitting their resource summary individually to Je-s. The resources listed within this Je-S Proposal are solely those of Imperial College with other institutions submitting their costs seperately, with one case for support.

The impact of road traffic on local air quality is a major public policy concern and has stimulated a substantial body of researchaimed at improving underlying vehicle and traffic management technologies and informing public policy action. Recent work hassought to use a variety of vehicle-based, person-based and infrastructure-based sensor systems to collect data on key aspects ofdriver and traffic behaviour, emissions, pollutant concentrations and exposure. The variety and pervasiveness of the sensor inputsavailable will increase significantly in the future as a result both of the increasingly widespread penetration of existingtechnologies (e.g., GPS based vehicle tracking, CANbus interfaces to on-board engine management system data) within thevehicle parc and the introduction of new technologies (such as e.g., UV sensing and nanotechnology based micro sensors). Aparticularly exciting direction for future development will be in the use of vehicles as platforms for outward facing environmentalsensor systems, allowing vehicles to operate as mobile environmental probes, providing radically improved capability for thedetection and monitoring of environmental pollutants and hazardous materials.However, these developments present new and formidable research challenges arising from the need to transmit,integrate, model and interpret vast quantities of highly diverse (spatially and temporally varying) sensor data. Our approach in thisproject is to address these challenges by novel combination and extension of state-of-the-art eScience, sensor, positioning andmodelling (data fusion, traffic, transport, emissions, dispersion) technologies. By so doing, we aim to develop the capability tomeasure, model and predict a wide range of environmental pollutants and hazards (both transport related and otherwise) using agrid of pervasive roadside and vehicle-mounted sensors. This work will be at the leading edge of eScience, stretching thecapabilities of the grid in a number of aspects of the processing of massive volumes of sensor data.