Roadmaps to Utopia: Tales of the Smart City

Notions of the Smart City are pervasive in urban development discourses. Various frameworks for the development of smart cities, often conceptualized as roadmaps, make a number of implicit claims about how smart city projects proceed but the legitimacy of those claims is unclear. This paper begins to address this gap in knowledge. We explore the development of a smart transport application, MotionMap, in the context of a £16M smart city programme taking place in Milton Keynes, UK. We examine how the idealized smart city narrative was locally inflected, and discuss the differences between the narrative and the processes and outcomes observed in Milton Keynes. The research shows that the vision of data-driven efficiency outlined in the roadmaps is not universally compelling, and that different approaches to the sensing and optimization of urban flows have potential for empowering or disempowering different actors. Roadmaps tend to emphasize the importance of delivering quick practical results. However, the benefits observed in Milton Keynes did not come from quick technical fixes but from a smart city narrative that reinforced existing city branding, mobilizing a growing network of actors towards the development of a smart region. Further research is needed to investigate this and other smart city developments, the significance of different smart city narratives, and how power relationships are reinforced and constructed through them

A Digital Twin City Model for Age-Friendly Communities: Capturing Environmental Distress from Multimodal Sensory Data

As the worldwide population is aging, the demands of aging-in-place are also increasing and require smarter and more connected cities to keep mobility independence of older adults. However, today’s aging built environment often poses great environmental demands to older adults’ mobility and causes their distresses. To better understand and help mitigating older adults’ distress in their daily trips, this paper proposes constructing the digital twin city (DTC) model that integrates multimodal data (i.e., physiological sensing, visual sensing) on environmental demands in urban communities, so that such environmental demands can be considered in mobility planning of older adults. Specifically, this paper examines how data acquired from various modalities (i.e., electrodermal activity, gait patterns, visual sensing) can portray environmental demands associated with older adults’ mobility. In addition, it discusses the challenges and opportunities of multimodal data fusion in capturing environmental distresses in urban communities

Exploring the epistemic politics of urban niche experiments

Urban experiments have been initiated in several locations to purposively initiate and shape transitions to more sustainable urban socio-technical systems, e.g. for energy, water, mobility. Although knowledges produced within such learning spaces are often presented as logical, technical and rational (Vanolo, 2013 ; Kitchin, 2014), the actors and mechanisms which shape decisions are far from obvious, involving cultures, power relations and multiple logics that are profoundly political (Machin, 2013). This research presents a case study founded in a phronetic perspective (Flyvbjerg, 2001; Avelino and Grin, 2017), unpacking the epistemological politics of an urban experiment taking place within a ‘smart city’ programme. A ‘smart transport’ application for mobile phones, ‘MotionMap’ was developed to transform the mobility system of Milton Keynes, an expanding city located 80 km to the north of London, UK. The case study recognises power relations and reveals how various actors engaged in the development of this application have further rendered the MK mobility socio-technical system an object of urban governance

Using Ambient Geographic Information (AGI) in order to understand emotion & stress within smart cities

De Oliveira, T. H. M. (2015). The Emotion-Aware City: Using Ambient Geographic Information (AGI) in order to understand emotion & stress within smart cities. In 3rd AGILE PhD School Association of Geographic Information Laboratories for Europe, AGILE PhD School 2015 (Vol. 1598, pp. 1-5). (CEUR Workshop Proceedings).publishersversionpublishe

Noise mapping based on participative measurements

The high temporal and spatial granularities recommended by the European regulation for the purpose of environmental noise mapping leads to consider new alternatives to simulations for reaching such information. While more and more European cities deploy urban environmental observatories, the ceaseless rising number of citizens equipped with both a geographical positioning system and environmental sensors through their smartphones legitimates the design of outsourced systems that promote citizen participatory sensing. In this context, the OnoM@p system aims at offering a framework for capitalizing on crowd noise data recorded by inexperienced individuals by means of an especially designed mobile phone application. The system fully rests upon open source tools and interoperability standards defined by the Open Geospatial Consortium. Moreover, the implementation of the Spatial Data Infrastructure principle enables to break up as services the various business modules for acquiring, analysing and mapping sound levels. The proposed architecture rests on outsourced processes able to filter outlier sensors and untrustworthy data, to cross- reference geolocalised noise measurements with both geographical and statistical data in order to provide higher level indicators, and to map the collected and processed data based on web services

Spatial and Temporal Sentiment Analysis of Twitter data

The public have used Twitter world wide for expressing opinions. This study focuses on spatio-temporal variation of georeferenced Tweets’ sentiment polarity, with a view to understanding how opinions evolve on Twitter over space and time and across communities of users. More specifically, the question this study tested is whether sentiment polarity on Twitter exhibits specific time-location patterns. The aim of the study is to investigate the spatial and temporal distribution of georeferenced Twitter sentiment polarity within the area of 1 km buffer around the Curtin Bentley campus boundary in Perth, Western Australia. Tweets posted in campus were assigned into six spatial zones and four time zones. A sentiment analysis was then conducted for each zone using the sentiment analyser tool in the Starlight Visual Information System software. The Feature Manipulation Engine was employed to convert non-spatial files into spatial and temporal feature class. The spatial and temporal distribution of Twitter sentiment polarity patterns over space and time was mapped using Geographic Information Systems (GIS). Some interesting results were identified. For example, the highest percentage of positive Tweets occurred in the social science area, while science and engineering and dormitory areas had the highest percentage of negative postings. The number of negative Tweets increases in the library and science and engineering areas as the end of the semester approaches, reaching a peak around an exam period, while the percentage of negative Tweets drops at the end of the semester in the entertainment and sport and dormitory area. This study will provide some insights into understanding students and staff ’s sentiment variation on Twitter, which could be useful for university teaching and learning management