Globally, national infrastructure is facing significant challenges: - Ageing assets: Much of the UK's existing infrastructure is old and no longer fit for purpose. In its State of the Nation Infrastructure 2014 report the Institution of Civil Engineers stated that none of the sectors analysed were "fit for the future" and only one sector was "adequate for now". The need to future-proof existing and new infrastructure is of paramount importance and has become a constant theme in industry documents, seminars, workshops and discussions. - Increased loading: Existing infrastructure is challenged by the need to increase load and usage - be that number of passengers carried, numbers of vehicles or volume of water used - and the requirement to maintain the existing infrastructure while operating at current capacity. - Changing climate: projections for increasing numbers and severity of extreme weather events mean that our infrastructure will need to be more resilient in the future. These challenges require innovation to address them. However, in the infrastructure and construction industries tight operating margins, industry segmentation and strong emphasis on safety and reliability create barriers to introducing innovation into industry practice. CSIC is an Innovation and Knowledge Centre funded by EPSRC and Innovate UK to help address this market failure, by translating world leading research into industry implementation, working with more than 40 industry partners to develop, trial, provide and deliver high-quality, low cost, accurate sensor technologies and predictive tools which enable new ways of monitoring how infrastructure behaves during construction and asset operation, providing a whole-life approach to achieving sustainability in an integrated way. It provides training and access for industry to source, develop and deliver these new approaches to stimulate business and encourage economic growth, improving the management of the nation's infrastructure and construction industry. Our collaborative approach, bringing together leaders from industry and academia, accelerates the commercial development of emerging technologies, and promotes knowledge transfer and industry implementation to shape the future of infrastructure. Phase 2 funding will enable CSIC to address specific challenges remaining to implementation of smart infrastructure solutions. Over the next five years, to overcome these barriers and create a self-sustaining market in smart infrastructure, CSIC along with an expanded group of industry and academic partners will: - Create the complete, innovative solutions that the sector needs by integrating the components of smart infrastructure into systems approaches, bringing together sensor data and asset management decisions to improve whole life management of assets and city scale infrastructure planning; spin-in technology where necessary, to allow demonstration of smart technology in an integrated manner. - Continue to build industry confidence by working closely with partners to demonstrate and deploy new smart infrastructure solutions on live infrastructure projects. Develop projects on behalf of industry using seed-funds to fund hardware and consumables, and demonstrate capability. - Generate a compelling business case for smart infrastructure solutions together with asset owners and government organisations based on combining smarter information with whole life value models for infrastructure assets. Focus on value-driven messaging around the whole system business case for why smart infrastructure is the future, and will strive to turn today's intangibles into business drivers for the future. - Facilitate the development and expansion of the supply chain through extending our network of partners in new areas, knowledge transfer, smart infrastructure standards and influencing policy.

Cloud computing promises to revolutionise how companies, research institutions and government organisations, including the National Health Service (NHS), offer applications and services to users in the digital economy. By consolidating many services as part of a shared ICT infrastructure operated by cloud providers, cloud computing can reduce management costs, shorten the deployment cycle of new services and improve energy efficiency. For example, the UK government's G-Cloud initiative aims to create a cloud ecosystem that will enable government organisations to deploy new applications rapidly, and to share and reuse existing services. Citizens will benefit from increased access to services, while public-sector ICT costs will be reduced. Security considerations, however, are a major issue holding back the widespread adoption of cloud computing: many organisations are concerned about the confidentiality and integrity of their users' data when hosted in third-party public clouds. Today's cloud providers struggle to give strong security guarantees that user data belonging to cloud tenants will be protected "end-to-end", i.e. across the entire workflow of a complex cloud-hosted distributed application. This is a challenging problem because data protection policies associated with applications usually require the strict isolation of certain data while permitting the sharing of other data. As an example, consider a local council with two applications on the G-Cloud: one for calculating unemployment benefits and one for receiving parking ticket fines, with both applications relying on a shared electoral roll database. How can the local council guarantee that data related to unemployment benefits will never be exposed to the parking fine application, even though both applications share a database and the cloud platform? The focus of the CloudSafetNet project is to rethink fundamentally how platform-as-a-service (PaaS) clouds should handle security requirements of applications. The overall goal is to provide the CloudSafetyNet middleware, a novel PaaS platform that acts as a "safety net", protecting against security violations caused by implementation flaws in applications ("intra-tenant security") or vulnerabilities in the cloud platform itself ("inter-tenant security"). CloudSafetyNet follows a "data-centric" security model: the integrity and confidentiality of application data is protected according to data flow policies -- agreements between cloud tenants and the provider specifying the permitted and prohibited exchanges of data between application components. It will enforce data flow policies through multiple levels of security mechanisms following a "defence-in-depth" strategy: based on policies, it creates "data compartments" that contain one or more components and isolate user data. A small privileged kernel, which is part of the middleware and constitutes a trusted computing base (TCB), tracks the flow of data between compartments and prevents flows that would violate policies. Previously such information flow control (IFC) models have been used successfully to enhance programming language, operating system and web application security. To make such a secure PaaS platform a reality, we plan to overcome a set of research challenges. We will explore how cloud application developers can express data-centric security policies that can be translated automatically into a set of data flow constraints in a distributed system. An open problem is how these constraints can be tied in with trusted enforcement mechanisms that exist in today's PaaS clouds. Addressing this will involve research into new lightweight isolation and sand-boxing techniques that allow the controlled execution of software components. In addition, we will advance software engineering methodology for secure cloud applications by developing new software architectures and design patterns that are compatible with compartmentalised data flow enforcement.

We propose to build the EPSRC Centre for Doctoral Training in Sensor Technologies for a Healthy and Sustainable Future (Sensor CDT) on the foundations we have established with our current CDT (EPSRC CDT for Sensor Technologies and Applications, see http://cdt.sensors.cam.ac.uk). The bid falls squarely into EPSRC's strategic priority theme of New Science and Technology for Sensing, Imaging and Analysis. The sensor market already contributes an annual £6bn in exports to the UK economy, underpinning 73000 jobs and markets estimated at £120bn (source: KTN UK). Major growth is expected in this sector but at the same time there is a growing problem in recruiting suitably qualified candidates with the necessary breadth of skills and leadership qualities to address identified needs from UK industry and to drive sustainable innovation. We have created an integrated programme for high quality research students that treats sensing as an academic discipline in its own right and provides comprehensive training in sensor technologies all the way from the fundamental science of sensing, the networking and interpretation of sensory data, to end user application. In the new, evolved CDT, we will provide training for our CDT students on themes that are of direct relevance to a sustainable and healthy future society, whilst retaining a focus that delivers value to the UK economy and academia. The 4-year programme is strongly cross disciplinary and focuses on sustainable development goals and emphasises training in Responsible Innovation. One example of the latter is our objective to 'democratise sensor technologies': Our students will learn how to engage with the public during research, how to play a valuable part in public debate, and how to innovate technology that benefits society. Technical aspects will be taught in a bespoke training programme for the course, that includes lectures, practicals, lab rotations, industry secondments, and skills training on key underpinning technologies. To support this effort, we have created dedicated, state-of-the-art infrastructure for the CDT that includes laboratory, office, teaching, and social spaces, and we connect to the world leading infrastructure available in the participating departments and partner industries. The programme is designed to create strong identities both within and across CDT cohorts (horizontal and vertical integration) to maximise opportunities for peer-to-peer learning and leadership training through activities such as our unique sensor team challenges and the monthly Sensor Cafés, attended by representatives from academia, industry, government agencies, and the public. We will create a diverse and inclusive atmosphere where students feel confident and empowered to offer different opinions and experiences and which maximises creativity and innovation. We have attracted substantial interest and support (>£2.5M) from established industrial partners, but our new programme emphasises engagement also with UK start-ups and SMEs, who are particularly vulnerable in the current economic climate and who have expressed a need for researchers with the breadth and depth of skills the CDT provides (see letters of support). We recruit outstanding, prizewinning students from a diverse range of disciplines and the training programme connects more than 90 PIs across 15 departments and 40 industrial partners working together to address future societal needs with novel sensor technologies. Technology developers will benefit through connection with experts in middleware (e.g. sensor distribution and networking, data processing) and applications experts (e.g. life scientists, atmospheric scientists, etc.) and vice versa. This integrative character of the CDT will inspire innovations that transform capability in many disciplines of science and industries.

The uneven ways that civil liberties, work, labour and health have all been impacted over the last 18 months as we have all turned to digital technologies to sustain previous ways of life, has not only shown us the extent of inequalities across all societies as they are cut through with gender, ethnicity, age, opportunities, class, geolocation; it has also led many organisations and businesses across all three sectors to question those values they previously supported. Capitalising on this moment of reflection across industry, the public and third sectors; we explore the possibility of imagining and building a future that takes different core values and practices as central, and works in very different ways. As the roles of organisations and businesses across all industry, the public and third sectors changes, what is now taken up as core values and ethos will be crucial in defining the future. INCLUDE+ will build a knowledge community around in/equalities in digital society that will comprise industry, academia, the public and third sectors. Responding to the Equitable Digital Society theme, we ask how we can design, co-create and realise digital services and infrastructures to support inclusion and equality in ways that enable all people to thrive. Focusing on the three connected strands of wellbeing, precarity, and civic culture; we address structural inequalities as they emerge through our research, investigating them through whole system approaches that includes the generation of outputs that comprise of new systems, services and practices to be taken up by organisations. More than this, our knowledge community will be underpinned by empirical, co-curation and participatory led research that will produce real interventions into those structural inequalities. These interventions will be taken up by organisations, responded to and considered, enabling the wider knowledge community to critically assess them in relation to the values they purport to promote. Fed by secondments and supported through smaller exploratory and escalator funds, our knowledge community will not only grow through traditional networking activities such as workshops, annual conferences, academic outputs and further funding; it will also grow through the development of interdisciplinary methods, knowledge exchange practices, and mentorship, which the secondment package will promote. In so doing, we structure our N+ around participatory research practices, people development and knowledge exchange, aiming to grow our network through the development and growth of people and good practice. INCLUDE+ is led by a highly experienced cross-disciplinary team incorporating Management and Business Studies, Computing, Social Sciences, Media and Communication and Legal Studies. Each Investigator brings vibrant international networks; active research projects feeding the Network+; and long experience of impact generation across policy and research. With support from organisations like the International Labour Organisation, Law Commission, Cabinet Office, and Equality and Human Rights Commission as well as the existing DE community, we will develop from and with existing research, extend this work and impact beyond it. Our partner organisations cut across industry, the public and third sectors and include (for example) Lego; NHS AI Lab; Space2; mHabitat; Leeds, Cambridgeshire and Swansea Councils; PeopleDotCom; Ditchley; 5Rights; EAMA; DataKind and IBM. We have designed the Network+ to enable a whole system approach that is genuinely exciting and innovative not just because of scalability, transference and scope, but also because of the commitment to people development, knowledge exchange and interdisciplinary practice that will also shape future research

Many aspects of a child or young person's life can affect their mental health. If someone has a serious mental health problem their general practitioner (GP) may refer them to mental health (psychiatry) services for assessment and treatment by professionals. Mental health services are stretched so often intervene late, leaving people to suffer unnecessarily with problems that therefore may last longer, be more severe, or be harder to treat. Early warning signs of mental health problems may be noticed by the person themselves or by others (e.g. school staff, social workers). Many things can suggest a mental health problem, such as difficult early experiences, bullying, changes in behaviour, poor school attendance or grades, or risk-taking. Not all who experience one or more of these will have a mental health problem, so we need to take them together to spot patterns that show who is developing problems and may need professional help. However, this information (data) is stored in different places, e.g. by schools, GPs and social workers and so it may be impossible to spot problems early. Some researchers have joined data from two or more sources to find patterns suggesting mental health problems. Their success indicates good potential in this approach, but they have not made a practical difference for two main reasons: 1) the models are not yet accurate enough, probably because they omit many factors that can lead to problems; 2) the results cannot be used directly to help young people as they are based on anonymous data. We will develop a system that can be used by health, education, or social workers to identify adolescents showing early signs of mental health problems, to offer them help sooner. At the same time we want to provide better anonymous data for research into predicting mental health problems. Data must be held securely (most likely in the NHS), and only people involved in a person's care should be able to see it, but we need to understand how best to do this. To use data for research while protecting privacy it will be anonymised, removing anything that directly identifies a person (e.g. name, address, date of birth, NHS number) and access will be restricted to approved researchers. But we do not yet know what technical problems there may be in linking the databases, or what data the system will need in order to detect people showing early signs of a problem. The final challenge is how to make this work within the NHS, schools, and social care settings to enable earlier identification of young sufferers of mental health problems. Over the next year, we want to tackle these challenges by creating a group including mental health researchers, psychologists, schools, the NHS, councils, computer scientists, security experts, mathematicians, people who provide services, and policy makers, many of whom are doing ground-breaking work in other areas. We want to turn their attention to jointly solving these problems. We must involve young people, their carers, and people with lived experience: it is their data and we need to understand their views. We would like their help thinking about which professionals can see their data, and what should happen when a young person is thought to be developing mental health problems. We will hold workshops about these questions. We also have permission to create an initial data set with data from health, social services, and education. We will anonymise these, and practise linking and analysing them. These will help us understand the challenges, so that our final plan will be more detailed and likely to succeed. In the future we want to test if a computer program makes it easier to identify mental health problems and offer young people treatments earlier, and if they get better quicker because of this. This might have a range of benefits including helping with school, relationships, home life, and getting jobs or into university, and we want to test this theory.