Systems thinking for developing sustainable complex smart cities based on self-regulated agent systems and fog computing

Abbas, Hosny A.; Shaheen, Samir I.; Elhoseny, Mohamed; Singh, Amit Kumar; Alkhambashi, Majid

doi:10.1016/j.suscom.2018.05.005

Cited by 27 publications

(16 citation statements)

References 20 publications

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“…Systems thinking enables an articulation of causes and effect, action, and impact of cybernetic decisions [75][76][77][78]. It contains loops which result in archetypes of causalities derived from prevailing attributes of a system [79,80].…”

Section: Systems Thinking: Swot Causal Loop Diagrammentioning

confidence: 99%

Facilitating Successful Smart Campus Transitions: A Systems Thinking-SWOT Analysis Approach

et al. 2021

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An identification of strengths, weakness, opportunities, and threats (SWOT) factors remains imperative for enabling a successful Smart Campus transition. The absence of a structured approach for analyzing the relationships between these SWOT factors and the influence thereof on Smart Campus transitions negate effective implementation. This study leverages a systems thinking approach to bridge this gap. Data were collected through a stakeholder workshop within a University of Technology case study and analyzed using qualitative content analysis (QCA). This resulted in the establishment of SWOT factors affecting Smart Campus transitions. Systems thinking was utilized to analyze the relationships between these SWOT factors resulting in a causal loop diagram (CLD) highlighting extant interrelationships. A panel of experts drawn from the United Kingdom, New Zealand, and South Africa validated the relationships between the SWOT factors as elucidated in the CLD. Subsequently, a Smart Campus transition framework predicated on the CLD archetypes was developed. The framework provided a holistic approach to understanding the interrelationships between various SWOT factors influencing Smart Campus transitions. This framework remains a valuable tool for facilitating optimal strategic planning and management approaches by policy makers, academics, and implementers within the global Higher Education Institution (HEI) landscape for managing successful Smart Campus transition at the South African University of Technology (SAUoT) and beyond.

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Section: Systems Thinking: Swot Causal Loop Diagrammentioning

confidence: 99%

Facilitating Successful Smart Campus Transitions: A Systems Thinking-SWOT Analysis Approach

et al. 2021

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“…The study adopts a system-thinking approach along with self-regulating agent systems and fog computing techniques for molding the futuristic concept of complex smart systems. (Abbas, Shaheen, Elhoseny, & Singh, 2018) 03.…”

Section: Why Systems Thinking and How It Workmentioning

confidence: 99%

A system thinking approach for harmonizing smart and sustainable city initiatives with United Nations sustainable development goals

Kutty

Abdella

Küçükvar

et al. 2020

Sustainable Development

101

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Technology has indispensably been a part of the city evolution throughout history. In recent years, there has been a shift in the pattern of development in smart cities, where smart cities attempt to embrace practices of sustainability using Information and Communication Technologies and other smart solutions. Past studies reveal that these smart cities have failed in successfully incorporating sustainable development goals into their smart strategies, where they tend to focus more on achieving smartness goals rather than sustainability goals and targets. This paper presents a multifaceted interrogative study on several ongoing smart city initiatives around the globe that supports United Nations Urban Sustainability Agenda. This paper aims to focus on harmonizing smart and sustainable city initiatives with the United Nations Sustainable Development Goals using a systems thinking approach. The study develops conceptual models that support the city transition into being a sustainable smart city. These conceptual models were designed based on the fundamentals of system thinking for a system of several elements under the key catalyzers "Policy and Governance," "Research & Development," and "Partnership." The causalities and interrelationships among elements in developed conceptual models justify the dynamicity and the impact of these elements within a system. The outcome of this research paper would support industry experts, policymakers, and city planners to adopt robust policy interventions and best practices for developing strategies that support the transition of smart cities to the futuristic label of sustainable cities.

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“…e clustering rules of panel data can effectively avoid clustering sequences with small association degree into a group and can deal with unequal data. However, this method is easy to be affected by dimensionality reduction results, and the introduction of new uncertainties will affect the final clustering accuracy [13].…”

Section: Introductionmentioning

confidence: 99%

Research on Grey Relational Clustering Model of Multiobjective Human Resources Based on Time Constraint

Wang

2021

Scientific Programming

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The existing grey relational clustering method has limitations in the application of multidimensional sequences and cannot directly calculate the grey correlation degree between unequal-length sequences. In this paper, by introducing the multidimensional dynamic DTW distance into the existing 3D grey relational model, a new grey relational analysis model that can be applied to multidimensional data is proposed, which is based on DTW distance. The model does not require one-to-one correspondence of data points but evaluates the similarity of its geometric curves by calculating the shortest distance between sequences. In addition, since the traditional grey correlation clustering method is implemented, the method first extracts the reference sequence from the observation sequence and then calculates the similarity between the observation objects by calculating the grey correlation degree between each sequence and the reference sequence, so each object only needs to be calculated once. The experimental results show that the multidimensional grey correlation degree based on DTW distance and the grey relational clustering model oriented to multidimensional data are more accurate than other existing methods. Finally, the grey relation clustering method of multidimensional data is used to analyze the multiobjective human resource grey relational clustering model under time constraints, and the validity of the model is verified.

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Systems thinking for developing sustainable complex smart cities based on self-regulated agent systems and fog computing

Cited by 27 publications

References 20 publications

Facilitating Successful Smart Campus Transitions: A Systems Thinking-SWOT Analysis Approach

Facilitating Successful Smart Campus Transitions: A Systems Thinking-SWOT Analysis Approach

A system thinking approach for harmonizing smart and sustainable city initiatives with United Nations sustainable development goals

Research on Grey Relational Clustering Model of Multiobjective Human Resources Based on Time Constraint

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