Manchester: Future City is an exciting project that will develop practical solutions to the challenges facing post-industrial cities as they seek to meet the energy, waste, water and transport needs of the future. This will focus on integrating systems and creating a knowledge platform for further intergation that will also stimulate innovation, support strategic decision making and respond to and shape consumer choice. the builds on existing projects to integrate systems and evaluate their impact on a wider area. The feasibility study will build on existing partnership across the City, including between the Universities, hospital, science park, public and private sector to develop a full Demonstrator proposal that shows the benefits and priorities for integration. These will be radical and transformative supporting Manchester's ambitions as a world class city.

CityVerve is based around the large-scale deployment of technologies, where everyday objects can be connected to a network in order to share data. This approach will demonstrate and evidence the benefits to citizens’ through environmental improvements, economic opportunities, and the more efficient and effective delivery of services such as transport, healthcare and energy. It will provide the ability to create new services and operating models through the interoperability between transport, healthcare and energy systems. The geographical focus of CityVerve will be Greater Manchester; a city region which has been at the forefront of the city devolution agenda, in particular health and social care provision, leading the way in designing new ways of delivering services and providing the blueprint for other cities in the UK and beyond. CityVerve will build on these opportunities to provide a once-in-a-generation opportunity to transform healthcare and other city services around the needs of people, not only is this is an urgent priority for Greater Manchester, but a challenge faced by many global cities.

Greater Manchester (GM), far from being a historically unified whole, is made up of ten boroughs, each with its own unique character. The Manchester Voices project investigates the ways in which people in the city-region position themselves locally, regionally and nationally, and the role of language in enacting social and regional identities. The project is structurally organised around three core strands: language use, language attitudes, and regional and social identities. It addresses a number of issues relating to the academic and non-academic treatment of regional and social varieties of language in the UK, and the role of such language varieties in the construction of identity: 1. Lack of detailed linguistic descriptions of regional variation across GM. Previous research has tended to view 'Manchester English' as a monolithic entity or has focused on specific areas within GM, thus not acknowledging the wide linguistic variation that exists. This project provides a rich and full description of language use across the region's ten boroughs, thus ensuring an accurate contemporary record of developing and changing regional varieties of language. 2. Societal and institutional disregard for regional accents and dialects. 'Regional' language varieties are often perceived in a negative way, with speakers being stigmatised. This project explores and challenges those perceptions by promoting and celebrating the linguistic and cultural heritage of GM, thereby advancing our understanding of the social, cultural, and historical factors that continue to shape the language, places, and people of the region. 3. Lack of attention to attitudes as factors mediating the relationship between language and identity. By exploring people's feelings towards their own speech and towards that of others, the project seeks to uncover deeply embedded and widely held beliefs regarding the status and value of regional accents and dialects. This attitudinal data will serve to challenge perceptions of regional accents and dialects and to promote linguistic equality and diversity as a means of nurturing a sense of social and regional pride. 4. Lack of sociolinguistic insight into existing cultural, historical, and literary resources relating to regional identity. GM, like many regions across the UK, has a wealth of resources relating to past and present society, much of which is collected by Manchester Libraries. However, the extent to which this material has been explored from a sociolinguistic perspective is minimal, despite language being at the heart of the available resources. By partnering with librarians, poets, literary specialists and cultural historians, the project will reach a fuller understanding of the linguistic context, contributing to a fuller understanding of the historical and literary landscape of GM. 5. Lack of community access and engagement in sociolinguistic research. Sociolinguistic data tends to be collected during pre-arranged meetings in neutral locations and formal contexts. To counter this, we will take our research into the community in the form of a mobile interview booth, allowing us to access groups who might otherwise be unaware of, or unwilling to be involved in, the project. In addition to majority populations, we will seek the voices of specific groups, such as young people and GM's multilingual/multicultural communities. The primary spoken data will be collected in the Accent Van, which will travel the ten boroughs of GM gathering speech and insights from people across the region. In addition, creative poetry and history workshops will gather further data and explore themes around regional identities. Dialect maps will be collected online, and attitude tests will take place online and at the University. Finally, existing audio recordings being digitised as part of the Save Our Sounds project will be housed with our data in a Voices resource area at Manchester Central Library.

Human observers move their eyes in order to direct their attention to important aspects of a visual scene. There are models called salience maps; they predict where the eyes will move to when looking at a scene. At present, these models do not deal with video input, nor do they predict how an observer's task will affect where they look. In other words, there are no models for real-life viewing situations, where an observer has a specific task.We are proposing a new approach to this problem. We have access to video information from cameras used in urban surveillance, and to the operators whose job it is to spot abnormal behaviour in such video inputs. We shall obtain (previously unseen) video recordings of events in UK urban streets, and display them in a simulated control room to operators familiar with the town in question. We shall monitor where they look on the bank of video screens, and also when they decide that an event is abnormal and/or requires some form of intervention, e.g. calling the police. We shall use the record of eye fixations to teach a computer system to distinguish between normal and abnormal events. In this way, we shall be able to learn what is important for humans to do such surveillance by observing their eye fixation behaviour, for a realistic (and difficult) task and set of real-life video sequences. The project is important for four reasons. First, this will be the first attempt to develop a model of human attention/eye movements which will be firmly based on realistic video input and a real task. Second, this will be the first time that a computer system is able to learn from human behaviour in this way. Third, we will learn much about the ability of trained observers to cope with a demanding task as the number of TV monitors increases. Finally, we will develop an automated system which will be able to analyse the input from any urban CCTV camera in order to alert operators to look at that video stream - at present, most CCTV video streams are not observed by anyone since there are too many cameras for the number of human observers. Therefore, an automated alerting system is greatly neeeded and this project constitutes the best attempt to date to produce one.