Context-Aware Pervasive Services for Smart Cities

Context-Aware Pervasive Services for Smart Cities

René Meier, Deirdre Lee
DOI: 10.4018/978-1-60960-549-0.ch001
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Smart environments support the activities of individuals by enabling context-aware access to pervasive information and services. This article presents the iTransIT framework for building such context-aware pervasive services in Smart Cities. The iTransIT framework provides an architecture for conceptually integrating the independent systems underlying Smart Cities and a data model for capturing the contextual information generated by these systems. The data model is based on a hybrid approach to context-modelling that incorporates the management and communication benefits of traditional object-based context modelling with the semantic and inference advantages of ontology-based context modelling. The iTransIT framework furthermore supports a programming model designed to provide a standardised way to access and correlate contextual information from systems and ultimately, to build context-aware pervasive services for Smart Cities. The framework has been assessed based on a prototypical realisation of an architecture for integrating diverse intelligent transportation systems in Dublin and by building context-aware pervasive transportation services for urban journey planning and for visualising traffic congestion.
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Current advances in information and communication technology, where a variety of networked sensor-based systems and devices are deployed on the scale of towns, cities, and even countries, represent an excellent opportunity to support everyday life activities. Such smart environments are based on the vision of ubiquitous computing where everyday entities communicate and collaborate to provide information and services to users. They will lead to Smart Cities that can support the activities of their inhabitants to improve quality of life and ensure sustainability. Smart Cities will support activities ranging from transportation, to healthcare, to sports and entertainment, to professional and social activities. They will support people in smart workplaces, in smart cars, in smart homes, and in large geographical areas, for example, outlined by a shopping mall, by a road, or by city limits.

Smart Cities are inherently heterogeneous, as they likely will consist of a multitude of sensors, devices, networks, and ultimately systems, especially, with increasing geographical scale. People living and moving in Smart Cities may use integrated devices, such as on-board computers in a vehicle, or handheld devices, such as mobile phones, Personal Digital Assistants (PDAs), and laptop computers to interact with the environments and to use the services they provide. These devices will provide access in a pervasive manner, that is anywhere and at any time, to the contextual information and the context-aware services available in Smart Cities, ranging from personal and professional information services, to environmental monitoring and control, to social services, to city-wide information systems (Abowd et al., 1997; Cheverst, Davies, Mitchell, Friday, & Efstratiou, 2000), to traveller assistance (Kjeldskov et al., 2003; Sivaharan et al., 2004; Wong, Aghvami, & Wolak, 2008), to optimised urban traffic control (Dowling, Cunningham, Harrington, Curran, & Cahill, 2005; Dusparic & Cahill, 2009).

Transportation is one obvious domain for providing the foundation of Smart Cities since services can be built to exploit the very many heterogeneous sensor-rich systems that have already been deployed on metropolitan scale and along national road networks to support urban traffic control and highway management. Such environments might enable people to access information ranging from places of interest, to prevailing road and weather conditions, to expected journey times, to up-to-date public transport information. It might also enable suitably privileged users to interact with the infrastructure, for example, to request a change to a traffic light or to reserve a parking space.

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