Abstract
The purpose of this chapter is to explore understandings of urban life and the ambient in smart, learning, and future cities in relation to urban theories, approaches, and metrics. As such, a review of the research literature is conducted in the context of smart cities and regions pertaining to urban theories, methodologies, and metrics. Issues, controversies, and problems emerging from the literature review are highlighted, contributing to formulation of a conceptual framework for theories, approaches, and metrics in relation to urban life and the ambient in smart cities. Using an exploratory case study approach combined with an explanatory correlational design, variables pertaining to the exploration are identified, and the nature of their relationship is assessed. Through the lens of urban theories, approaches, and metrics, urban life and the ambient is explored in smart cities while informing directions for future research and practice.
Top1. Introduction
Harrison and Donnelly (2011) point to the instrumentation of smart cities “as a key enabler for new theories of cities.” Schmitt (2015) identifies methodologies for smart cities and future cities such as simulation and experiment. Batty (2020) articulates the notion of high and low frequency cities where change occurs “over very fine time intervals” as in “seconds minutes, hours, days” for the former and “over years, decades, centuries” for the latter with implications for the adapting of theory, approaches, and tools more generally for the understanding of cities and more particularly, smart cities. In response, this chapter is significant in that it seeks to explore urban life and the ambient in smart cities through the lens of evolving theory, approaches, and metrics giving rise to the motivation for this work as described in the objectives below.
Objectives: The main objectives of this chapter are to: a) provide a review of the research literature for urban life and the ambient in the context of smart cities pertaining to theory, approaches, and metrics; b) formulate a conceptual framework for urban life and the ambient in smart cities in relation to theory, approaches, and metrics; and c) explore the relationship between variables in smart cities such as collaborating and data visualizations as factors shedding insight on the evolving of theory, approaches, and metrics in smart environments.
These objectives give rise to the main research question under exploration in this chapter – Why are tools such as theory needed for understanding urban life and the ambient in smart, learning, and future cities?
Top2. Background
The notion of innovating metrics for smart cities is advanced by McKenna (2019) as is the proposing of ambient theory for smart cities (McKenna, 2021) in accommodating the aware people and awareness-enabling technologies dimensions of smartness in urban environments and regions. Considerable work has been undertaken by many, such as, the United Nations, European cities, and the International Standards Organization (ISO) on metrics for smart cities as described by the OECD (2020) in the context of measuring the performance of smart cities. Lopes and Rodrigues (2020) explore methodologies for the design, development, implementation, and evaluation of smart cities, proposing a five-phase approach consisting of context analysis, capability assessment, strategy, action plan, and evaluation. Qaed (2020) describes design thinking as an approach to smart cities “to strengthen the human dimension.” Backhouse (2020) develops a taxonomy for smart cities based on the identification of four types of measures “indicator standards, models, composite indices, and other measures” in coming to an understanding of measures, their uses, differences, and potentials.
2.1 Definitions
Definitions from the practice and research literature are provided for key terms used in this chapter.
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Metrics: In the context of an online course on smart cities, The Open University (2020) describes metrics as “measurements that are based on a standardised method.”
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Theory: Gregor (2006) describes theory as that which is able “to encompass conjectures, models, frameworks, or body of knowledge” adding more recently (2017) that “theory can serve multiple purposes, from sense-making to predicting.”
Key Terms in this Chapter
Ambient Collaboration: Ambient collaboration in an urban context refers to working together in a dynamic way, possibly involving interactions with technology to create or improve one or more aspects of life in the city.
Ambient Approaches: Ambient approaches to smart cities refer to more dynamic and adaptive ways of working together in designing solutions for complex challenges.
Collaboration: Collaboration in an urban context refers to working together to create or improve some aspect of life in the city.
Ambient Metrics: Ambient metrics in the context of smart cities refer to more dynamic and adaptive ways of measuring any aspect of urban environments and spaces in-the-moment and rendering such measurements in meaningful ways.
Ambient Theory: Ambient theory in the context of smart, learning, and future cities refers to theory that takes into consideration elements such as awareness, adaptive, dynamic, emergent, interactive, and pervasive as well as meaningfulness for people.