Smart cities try to use technology and data to improve the efficiency of city services, to address societal challenges and to improve collaboration between citizens and government. Driving such social change requires a deep socio-ecological transition with both organisations and individual's lifestyles needing to change. This has led to an increasing recognition of the need for education to empower people to play a more active role within smart city initiatives. This paper examines our use of a MOOC as a tool to facilitate attitudinal learning around the topic of smart cities and to explore whether the learners engage in local smart city activities. A mixed methods research design was employed, collecting data via an online survey that was completed by 202 learners and through in-depth interviews with 8 of those learners. The results show that learners’ perceived high levels of attitudinal learning on the topic of smart cities across four categories of learning outcomes (general, cognitive, affective and behavioural). Our findings also contribute to an understanding of the types of post-course activities learners participate in and their experiences of trying to apply what they learnt if they participated in local smart city activities. We conclude by providing new insights into how to design for learning to support social change in the context of a MOOC.@en

Many Smart City projects are beginning to consider the role of citizens. However, current methods for engaging urban populations in participatory design (PD) activities are somewhat limited. In this article, we describe an approach taken to empower socially disadvantaged citizens, using a variety of both social and technological tools, in a Smart City project. Through analysing the nature of citizens' concerns and proposed solutions, we explore the benefits of our approach, arguing that engaging citizens can uncover hyper-local concerns that provide a foundation for finding solutions to address citizen concerns. By reflecting on our approach, we identify four key challenges to utilising PD at an urban scale; balancing scale with the personal, who has control of the process, who is participating and integrating citizen-led work with local authorities. By addressing these challenges, we will be able to truly engage citizens as collaborators in co-designing their city.@en

The technological focus of many Smart City projects relies on top-down innovations, ignoring the role that citizens can play in improving their local communities. In this paper we outline our approach to supporting citizens in playing an active role in urban innovation, from the crowdsourcing of initial ideas through to facilitating citizen involvement in the realization of community projects. This extends previous work in the field by exploring how to go beyond identifying issues and ideas to securing a commitment from citizens to assisting a project intended to address an identified issue.@en

Choosing the right technologies to build an urban-scale IoT system can be challenging. There is often a focus on low-level architectural details such as the scalability of message handling. In our experience building an IoT information system requires a high-level holistic approach that mixes traditional data collection from vendor-specific cloud backends, together with data collected directly from embedded hardware and mobile devices. Supporting this heterogeneous environment can prove challenging and lead to complex systems that are difficult to develop and deploy in a timely fashion. In this paper we describe how we address these challenges by proposing a three-tiered DevOps model which we used to build an information system that is capable of providing real-time analytics of Electric Vehicle (EV) mobility usage and management within a smart city project.@en

Choosing the right technologies to build an urban-scale IoT system can be challenging. There is often a focus on low-level architectural details such as the scalability of message handling. In our experience building an IoT information system requires a high-level holistic approach that mixes traditional data collection from vendor-specific cloud backends, together with data collected directly from embedded hardware and mobile devices. Supporting this heterogeneous environment can prove challenging and lead to complex systems that are difficult to develop and deploy in a timely fashion. In this paper we describe how we address these challenges by proposing a three-tiered DevOps model which we used to build an information system that is capable of providing real-time analytics of Electric Vehicle (EV) mobility usage and management within a smart city project.@en

The potential of open data as a resource for driving citizen-led urban innovation relies not only on a suitable technical infrastructure but also on the skills and knowledge of the citizens themselves. In this chapter, we describe how a smart city project in Milton Keynes, UK, is supporting multiple stages of citizen innovation, from ideation to citizen-led smart city projects. The Our MK initiative provides support and funding to help citizens develop their ideas about making their communities more sustainable into reality. This approach encounters challenges when engaging with citizens in identifying and implementing data-driven solutions to urban problems. The majority of citizens have little practical experience with the types of data sets that might be available or possess the appropriate skills for their analysis and utilisation for addressing urban issues or finding novel ways to hack their city. We go on to describe the Urban Data School, which aims to offer a long-term solution to this problem by providing teaching resources around urban data sets aimed at raising the standard of data literacy amongst future generations. Lesson resources that form part of the Urban Data School have been piloted in one primary and three secondary schools in Milton Keynes. This work has demonstrated that with the appropriate support, even young children can begin to develop the skills necessary to work with large complex data sets. Through our two approaches, we illustrate some of the barriers to citizen participation in urban innovation and detail our solutions to overcoming those barriers.@en