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 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.

This project is part of a collaborative eScience pilot project.Please see the corresponding application from Imperial College for the summary of the project

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.