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Title	Towards A Model For Intelligent Context-Sensitive Computing For Smart Cities
ID_Doc	57866
Authors	Memon S.; Olaniyan R.; Maheswaran M.
Year	2018
Published	Handbook of Smart Cities: Software Services and Cyber Infrastructure
DOI	http://dx.doi.org/10.1007/978-3-319-97271-8_8
Abstract	Smart cities is a concept that can be interpreted in many ways. One of them is to consider it as leveraging the wireless and wired Internet to streamline the operation of city-wide infrastructures to maximize their operational efficiencies and offer new services to the citizens. Many existing or ongoing smart city realizations follow this interpretation. Another more futuristic interpretation is to consider it as a large-scale context-sensitive computing infrastructure that hosts heterogeneous programs and enables the programs to interact with each other in a variety of different ways. In this chapter, we pursue such a futuristic interpretation. We are proposing a computing model for smart cities that brings together cloud computing, fogs, and mobiles to support intelligent context-sensitive computing. Our computing model has two components. The first component is a hierarchical abstract machine that spans the cloud, fogs, and devices, which can scale from a single device to many thousands of machines. The second component is an implicit learning module that observes selected data within the abstract machine to learn their characteristics. Because the implicit learning module can provide predictions based on the data in a context-sensitive manner, in certain scenarios applications can get by without explicitly incorporating machine learning into their design. In this chapter, we motivate the need for such an intelligent context-sensitive model, describe the components of the model, and present some early results. © Springer Nature Switzerland AG 2018.
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