TCitySmartF: A comprehensive systematic framework for transforming cities into smart cities

A shared agreed-upon definition of "smart city" (SC) is not available and there is no "best formula" to follow in transforming each and every city into SC. In a broader inclusive definition, it can be described as an opportunistic concept that enhances harmony between the lives and the environment around those lives perpetually in a city by harnessing the smart technology enabling a comfortable and convenient living ecosystem paving the way towards smarter countries and the smarter planet. SCs are being implemented to combine governors, organisations, institutions, citizens, environment, and emerging technologies in a highly synergistic synchronised ecosystem in order to increase the quality of life (QoL) and enable a more sustainable future for urban life with increasing natural resource constraints. In this study, we analyse how to develop citizen- and resource-centric smarter cities based on the recent SC development initiatives with the successful use cases, future SC development plans, and many other particular SC development solutions. The main features of SC are presented in a framework fuelled by recent technological advancement, particular city requirements and dynamics. This framework - TCitySmartF 1) aims to aspire a platform that seamlessly forges engineering and technology solutions with social dynamics in a new philosophical city automation concept - socio-technical transitions, 2) incorporates many smart evolving components, best practices, and contemporary solutions into a coherent synergistic SC topology, 3) unfolds current and future opportunities in order to adopt smarter, safer and more sustainable urban environments, and 4) demonstrates a variety of insights and orchestrational directions for local governors and private sector about how to transform cities into smarter cities from the technological, social, economic and environmental point of view, particularly by both putting residents and urban dynamics at the forefront of the development with participatory planning and interaction for the robust community- and citizen-tailored services. The framework developed in this paper is aimed to be incorporated into the real-world SC development projects in Lancashire, UK

Making sense framework and assessment of participatory strategies

This report is a combined effort of Dundee University and the Joint Research Centre, based on the integration of D5.2 (Report and evaluation of the pilot approaches to ‘Making Sense campaigns’) and D4.3 (Report on assessment of participatory methods in the pilots and final recommendations). The document is structured as follows: Section 1 articulates the Making Sense approach to pilots and covers our campaign rationale, stakeholders and summarises the Making Sense pilots; Section 2 describes the design and iteration of the Making Sense Framework; Section 3 shows how the Making Sense Framework has been exemplified through the pilots and describes and illustrates each phase of the Framework with an example from a pilot; Section 4 focuses on ten key topics where we observed how citizen engagement and community building were addressed inside Making Sense and how the project participatory strategies developed from there on; Section 5 puts forward a new augmented version of previously devised recommendations for participatory or community driven sensing projects, with lessons learned from and for Making Sense.JRC.I.2-Foresight, Behavioural Insights and Design for Polic

Participatory GIS as a Tool for Stakeholder Engagement in Building Resilience to Sea Level Rise: A Demonstration Project

This article describes a participatory geographical information system (PGIS) demonstration project used as part of the stakeholder engagement efforts undertaken by the Citizen Engagement Working Group of the Hampton Roads Sea Level Rise Preparedness and Resilience Intergovernmental Planning Pilot Project. The PGIS demonstration project was conducted in the Little Creek/Pretty Lake case study area in the Hampton Roads region of southeastern coastal Virginia. PGIS served as a deliberative and participatory mechanism to obtain local knowledge from residents about the location of valued assets within the community and locations challenged by increased flooding and sea level rise. The PGIS application, using the weTable tool, was found to be useful for soliciting and documenting local knowledge, such as by highlighting community assets and identifying community challenges. It was also found to be useful for facilitating community-wide discussion, visualizing the problem, and understanding the severity of sea level rise and flooding. The PGIS demonstration project showed how participatory mapping can directly engage residents in creating sociospatial data, build knowledge, and foster learning and deliberation in a complex issue such as resilience to flooding and sea level rise

Exploring 'smart citizenship' as a socio-technical ecology: the case of Oxfordshire, UK

Critical social science scholarship on ‘smart citizenship’ has thus far emphasised ‘bottom-up’ participation as a democratising antidote to ‘top-down’ corporate or state-led smart cities. It is implied that contesting these powerful smart actors involves increasing the degree of citizen participation in smart programmes or projects and by enabling greater political agency in grassroots or citizen-centric alternatives. In this thesis, I emphasise the multiple and heterogenous ways ‘smart citizenship’ is enacted through a diverse set of discourses, practices, and materialities. Approaching these collectives as ‘socio-technical ecologies’, I seek to move beyond existing dichotomies that frame smart citizenship as either a condition of technologically-mediated authoritarian control (top-down) or of increased democratic participatory processes (bottom-up). My approach, I argue, helps to account for a wider set of interrelated ways in which citizenship is negotiated in actually-existing contexts of the smart city. The thesis draws on empirical materials generated through a study of how the UK county of Oxfordshire is being made ‘smart’. In doing so, I identify four overlapping, interconnected ways in which smart citizenship is constituted through ecologies of discourses, practices and materialities. The first is a type of ‘informational’ smart citizenship, which is centred on establishing and mobilising a fairly familiar mix of participatory deliberative engagement practices, procedures, and technologies. The second is the primarily discursive framing of citizens as living lab ‘beneficiaries’ who accrue relative advantages from experiments with technological products or services. Beneficiary citizens are enrolled in political-economic discourses of innovation to legitimise imaginaries of anticipated smart futures. The third raises the importance of 'expert' citizenship, which is deployed by partners to constitute local tech workers as experts engaged in making Oxford smart. I finally consider the ‘sim’ citizenships produced from machine learning methods of data analysis generative of road actor behaviour models for digital twin modelling. Sim citizens, calibrated by smart city data, populate the digital twin for iterative validation and verification testing of automated driving systems. The thesis altogether contributes to scholarly understandings of smart city citizenship by identifying emerging sets of relations between humans and technologies in digitally-mediated cities

Making climate public: energy monitoring and smart grids as political participation

This article presents the findings of ethnographic research in the UK with a network of engineers, activists, and citizens involved in developing smart energy monitoring systems and community smart grids. The paper explores how everyday uses of data, material evidence, and sensory information on material and thermodynamic processes that appear in such projects, are opening up new spaces for public participation in climate change politics. Here, familiar discursive and deliberative forms of democratic participation are supplemented by what I term material diagnostics—a practice of public participation that revolves around a collective effort to unpack and rethink infrastructures as sites of climate action. Building on these findings, the paper suggests that everyday digitally informed experiments with urban infrastructures have the potential to extend the kinds of political subjectivities and participatory politics that are possible, as governments seek to transition to a net-zero future

Citizen Sensing : A Toolkit

We produced this book as a part of the Making Sense project, which draws on nine citizen sensing campaigns in Holland, Kosovo and Spain in 2016 and 2017. In them, we have developed a form of citizen participation in environmental monitoring and action which is bottom-up, participatory and empowering to the community: this is called citizen sensing. If you are interested in best practices and tools for community engagement and co-creation, this book if for you

Community memories for sustainable societies: The case of environmental noise

Sustainability is the main challenge faced by humanity today on global and local scales. Most environmental problems can be seen as the tragic overexploitation of a commons. In this dissertation we investigate how the latest developments within computer science and ICT can be applied to establish participatory, low-cost tools and practices that enable citizens to monitor, raise awareness about, and contribute to the sustainable management of the commons they rely on, and thereby protect or improve their quality of life. As a general approach we propose the use of community memories – as central data repositories and points of interaction for community members and other stakeholders – and the novel combination of participatory mobile sensing and social tagging – as a low-cost means to collect quantitative and qualitative data about the state of the commons and the health, well-being, behaviour and opinion of those that depend on it. Through applied, interdisciplinary research we develop a concrete solution for a specific, socially relevant problem, namely that of environmental noise – commonly referred to as noise pollution. Under the name NoiseTube we present an operational system that enables a participatory, low-cost approach to the assessment of environmental noise and its impact on citizens’ quality of life. This approach can be applied in the scope of citizen- or authority-led initiatives. The NoiseTube system consists of a sensing application – which turns mobile phones into a sound level meters and allows users to comment on their experience via social tagging – and a community memory – which aggregates and processes data collected by participants anywhere. The system supports and has been tested and deployed at different levels of scale – personal, group and mass sensing. Since May 2009 NoiseTube has been used by hundreds, if not thousands, of people all around the world, allowing us to draw lessons regarding the feasibility of different deployment, collaboration and coordination scenarios for participatory sensing in general. While similar systems have been proposed ours is the completest and most widely used participatory noise mapping solution to date. Our validation experiments demonstrate that the accuracy of mobile phones as sound level meters can be brought to an acceptable level through calibration and statistical reasoning. Through coordinated NoiseTube campaigns with volunteering citizens we establish that participatory noise mapping is a suitable alternative for, or a valuable complement to, conventional methods applied by authorities

Challenges in Complex Systems Science

FuturICT foundations are social science, complex systems science, and ICT. The main concerns and challenges in the science of complex systems in the context of FuturICT are laid out in this paper with special emphasis on the Complex Systems route to Social Sciences. This include complex systems having: many heterogeneous interacting parts; multiple scales; complicated transition laws; unexpected or unpredicted emergence; sensitive dependence on initial conditions; path-dependent dynamics; networked hierarchical connectivities; interaction of autonomous agents; self-organisation; non-equilibrium dynamics; combinatorial explosion; adaptivity to changing environments; co-evolving subsystems; ill-defined boundaries; and multilevel dynamics. In this context, science is seen as the process of abstracting the dynamics of systems from data. This presents many challenges including: data gathering by large-scale experiment, participatory sensing and social computation, managing huge distributed dynamic and heterogeneous databases; moving from data to dynamical models, going beyond correlations to cause-effect relationships, understanding the relationship between simple and comprehensive models with appropriate choices of variables, ensemble modeling and data assimilation, modeling systems of systems of systems with many levels between micro and macro; and formulating new approaches to prediction, forecasting, and risk, especially in systems that can reflect on and change their behaviour in response to predictions, and systems whose apparently predictable behaviour is disrupted by apparently unpredictable rare or extreme events. These challenges are part of the FuturICT agenda

Distributed, Low-Cost, Non-Expert Fine Dust Sensing with Smartphones

Diese Dissertation behandelt die Frage, wie mit kostengünstiger Sensorik Feinstäube in hoher zeitlicher und räumlicher Auflösung gemessen werden können. Dazu wird ein neues Sensorsystem auf Basis kostengünstiger off-the-shelf-Sensoren und Smartphones vorgestellt, entsprechende robuste Algorithmen zur Signalverarbeitung entwickelt und Erkenntnisse zur Interaktions-Gestaltung für die Messung durch Laien präsentiert. Atmosphärische Aerosolpartikel stellen im globalen Maßstab ein gravierendes Problem für die menschliche Gesundheit dar, welches sich in Atemwegs- und Herz-Kreislauf-Erkrankungen äußert und eine Verkürzung der Lebenserwartung verursacht. Bisher wird Luftqualität ausschließlich anhand von Daten relativ weniger fester Messstellen beurteilt und mittels Modellen auf eine hohe räumliche Auflösung gebracht, so dass deren Repräsentativität für die flächendeckende Exposition der Bevölkerung ungeklärt bleibt. Es ist unmöglich, derartige räumliche Abbildungen mit den derzeitigen statischen Messnetzen zu bestimmen. Bei der gesundheitsbezogenen Bewertung von Schadstoffen geht der Trend daher stark zu räumlich differenzierenden Messungen. Ein vielversprechender Ansatz um eine hohe räumliche und zeitliche Abdeckung zu erreichen ist dabei Participatory Sensing, also die verteilte Messung durch Endanwender unter Zuhilfenahme ihrer persönlichen Endgeräte. Insbesondere für Luftqualitätsmessungen ergeben sich dabei eine Reihe von Herausforderungen - von neuer Sensorik, die kostengünstig und tragbar ist, über robuste Algorithmen zur Signalauswertung und Kalibrierung bis hin zu Anwendungen, die Laien bei der korrekten Ausführung von Messungen unterstützen und ihre Privatsphäre schützen. Diese Arbeit konzentriert sich auf das Anwendungsszenario Partizipatorischer Umweltmessungen, bei denen Smartphone-basierte Sensorik zum Messen der Umwelt eingesetzt wird und üblicherweise Laien die Messungen in relativ unkontrollierter Art und Weise ausführen. Die Hauptbeiträge hierzu sind: 1. Systeme zum Erfassen von Feinstaub mit Smartphones (Low-cost Sensorik und neue Hardware): Ausgehend von früher Forschung zur Feinstaubmessung mit kostengünstiger off-the-shelf-Sensorik wurde ein Sensorkonzept entwickelt, bei dem die Feinstaub-Messung mit Hilfe eines passiven Aufsatzes auf einer Smartphone-Kamera durchgeführt wird. Zur Beurteilung der Sensorperformance wurden teilweise Labor-Messungen mit künstlich erzeugtem Staub und teilweise Feldevaluationen in Ko-Lokation mit offiziellen Messstationen des Landes durchgeführt. 2. Algorithmen zur Signalverarbeitung und Auswertung: Im Zuge neuer Sensordesigns werden Kombinationen bekannter OpenCV-Bildverarbeitungsalgorithmen (Background-Subtraction, Contour Detection etc.) zur Bildanalyse eingesetzt. Der resultierende Algorithmus erlaubt im Gegensatz zur Auswertung von Lichtstreuungs-Summensignalen die direkte Zählung von Partikeln anhand individueller Lichtspuren. Ein zweiter neuartiger Algorithmus nutzt aus, dass es bei solchen Prozessen ein signalabhängiges Rauschen gibt, dessen Verhältnis zum Mittelwert des Signals bekannt ist. Dadurch wird es möglich, Signale die von systematischen unbekannten Fehlern betroffen sind auf Basis ihres Rauschens zu analysieren und das "echte" Signal zu rekonstruieren. 3. Algorithmen zur verteilten Kalibrierung bei gleichzeitigem Schutz der Privatsphäre: Eine Herausforderung partizipatorischer Umweltmessungen ist die wiederkehrende Notwendigkeit der Sensorkalibrierung. Dies beruht zum einen auf der Instabilität insbesondere kostengünstiger Luftqualitätssensorik und zum anderen auf der Problematik, dass Endbenutzern die Mittel für eine Kalibrierung üblicherweise fehlen. Bestehende Ansätze zur sogenannten Cross-Kalibrierung von Sensoren, die sich in Ko-Lokation mit einer Referenzstation oder anderen Sensoren befinden, wurden auf Daten günstiger Feinstaubsensorik angewendet sowie um Mechanismen erweitert, die eine Kalibrierung von Sensoren untereinander ohne Preisgabe privater Informationen (Identität, Ort) ermöglicht. 4. Mensch-Maschine-Interaktions-Gestaltungsrichtlinien für Participatory Sensing: Auf Basis mehrerer kleiner explorativer Nutzerstudien wurde empirisch eine Taxonomie der Fehler erstellt, die Laien beim Messen von Umweltinformationen mit Smartphones machen. Davon ausgehend wurden mögliche Gegenmaßnahmen gesammelt und klassifiziert. In einer großen summativen Studie mit einer hohen Teilnehmerzahl wurde der Effekt verschiedener dieser Maßnahmen durch den Vergleich vier unterschiedlicher Varianten einer App zur partizipatorischen Messung von Umgebungslautstärke evaluiert. Die dabei gefundenen Erkenntnisse bilden die Basis für Richtlinien zur Gestaltung effizienter Nutzerschnittstellen für Participatory Sensing auf Mobilgeräten. 5. Design Patterns für Participatory Sensing Games auf Mobilgeräten (Gamification): Ein weiterer erforschter Ansatz beschäftigt sich mit der Gamifizierung des Messprozesses um Nutzerfehler durch den Einsatz geeigneter Spielmechanismen zu minimieren. Dabei wird der Messprozess z.B. in ein Smartphone-Spiel (sog. Minigame) eingebettet, das im Hintergrund bei geeignetem Kontext die Messung durchführt. Zur Entwicklung dieses "Sensified Gaming" getauften Konzepts wurden Kernaufgaben im Participatory Sensing identifiziert und mit aus der Literatur zu sammelnden Spielmechanismen (Game Design Patterns) gegenübergestellt