scholarly journals Multiscale Modeling in Smart Cities: A Survey on applications, Current Trends, and Challenges

Author(s):  
Asif Khan ◽  
Khursheed Aurangzeb ◽  
Sheraz Aslam ◽  
Musaed Alhussein

Megacities are complex systems facing the challenges of overpopulation, poor urban design and planning, poor mobility and public transport, poor governance, climate change issues, poor sewerage and water infrastructure, waste and health issues, and unemployment. Smart cities have emerged to address these challenges by making the best use of space and resources for the benefit of citizens. A smart city model views the city as a complex adaptive system consisting of services, resources, and citizens that learn through interaction and change in both the spatial and temporal domains. The characteristics of dynamic development and complexity are key issues for city planners that require a new systematic and modeling approach. Multiscale modeling (MM) is an approach that can be used to better understand complex adaptive systems. The MM aims to solve complex problems at different scales, i.e., micro, meso, and macro, to improve system efficiency and mitigate computational complexity and cost. In this paper, we present an overview of MM in smart cities. First, this study discusses megacities, their current challenges, and their emergence to smart cities. Then, we discuss the need of MM in smart cities and its emerging applications. Finally, the study highlights current challenges and future directions related to MM in smart cities, which provide a roadmap for the optimized operation of smart city systems.

Author(s):  
Yeji Yun ◽  
Minhwa Lee

The purpose of a Smart City is to solve its inherent problems while simultaneously reducing its expenditure and improving its quality of life. Through the 4th Industrial Revolution technology, the advantages of Smart City are estimated to overcome the city’s expenses with city platformization. While a city traditionally is the subject of creation and not consumption, a Smart City currently is the key industry in generating more than 60% of its GDP in value creation from a production viewpoint. Moreover, with the expansion of online-offline convergence, cities can grow without limitation on its size, where connectivity and innovation determine the inclination of the city’s benefit-cost curve. As a city platform is responsible for connectivity, its value drastically increases through the 4th Industrial Revolution’s O2O (online to offline convergence) platform. When a city reflects on its own as a Digital Twin in the Cloud and when complete information becomes accessible through citizen’s participation through smartphones (Edge), Self-organization takes place, an ideal linkage between the city and citizens. Cities go through the self-organizing process of complex adaptive systems like the human brain. This research proposes a future model of a “Self-organizing City,” and suggests implementing the Smart City model based on the Smart City Tech-Socio Model in implementing strategies.


Author(s):  
Marc Rabaey

This chapter introduces Complex Adaptive Systems Thinking (CAST) into the domain of Intellectual Capital (IC). CAST is based on the theories of Complex Adaptive System (CAS) and Systems Thinking (ST). It argues that the CAST, combined with Intelligence Base offers a potentially more holistic approach to managing the Intellectual Capital of an organization. Furthermore, the authors extend this IC management with additional dimensions proper to a social entity such as an organization. New organizational design methods are needed and the capability approach is such a method that supports IC in virtual and real organizations. The characteristics of Intellectual Capital are discussed in the iterative process of inquiry and the Cynefin Framework, guaranteeing a holistic view on the organization and its environment.


2017 ◽  
Vol 2 (1) ◽  
pp. 137-143
Author(s):  
Levente Bakos ◽  
Dănuț Dumitrașcu

Abstract Risk assessment is one the key activities of any project. The unexpected situations can have catastrophic consequences. Risk assessment tries to estimate to potential known unknowns, but there is no guarantee to foresee all circumstances around a project. In this situation the project team must be adaptive and find solutions by cooperation, creativity and abductive reasoning. In the paper we tried to analyse on what extent a project and a project team can be handled as a complex adaptive system. More precisely, how the scientific and practical achievements of the theory of complex adaptive systems (CAS) can be used in project management. More exactly, we analyse the applicability of the Holonic Multi-Agent Systems in risk management of the projects. We consider the way in which holons handle the unexpected situations can be a model in project management.


Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Paul Brous ◽  
Marijn Janssen ◽  
Paulien Herder

Organizations are increasingly looking to adopt the Internet of Things (IoT) to collect the data required for data-driven decision-making. IoT might yield many benefits for asset management organizations engaged in infrastructure asset management, yet not all organizations are equipped to handle this data. IoT data is collected, stored, and analyzed within data infrastructures and there are many changes over time, resulting in the evolution of the data infrastructure and the need to view data infrastructures as complex adaptive systems (CAS). Such data infrastructures represent information about physical reality, in this case about the underlying physical infrastructure. Physical infrastructures are often described and analyzed in literature as CASs, but their underlying data infrastructures are not yet systematically analyzed, whereas they can also be viewed as CAS. Current asset management data models tend to view the system from a static perspective, posing constraints on the extensibility of the system, and making it difficult to adopt new data sources such as IoT. The objective of the research is therefore to develop an extensible model of asset management data infrastructures which helps organizations implement data infrastructures which are capable of evolution and aids the successful adoption of IoT. Systematic literature review and an IoT case study in the infrastructure management domain are used as research methods. By adopting a CAS lens in the design, the resulting data infrastructure is extendable to deal with evolution of asset management data infrastructures in the face of new technologies and new requirements and to steadily exhibit new forms of emergent behavior. This paper concludes that asset management data infrastructures are inherently multilevel, consisting of subsystems, links, and nodes, all of which are interdependent in several ways.


2008 ◽  
Vol 2 ◽  
Author(s):  
Craig Newell

Educational theorists are making increasing use of the metaphors and concepts of complexity thinking in their discourses. In particular, Professors Brent Davis, Elaine Simmt, and Dennis Sumara have written extensively about using complexity thinking to shift attention from the individual student as the locus of learning (cognizing agent) to the social collective—the class—as the locus of learning. In this model, the class (students and teacher) is (potentially) a complex adaptive system. The students and teacher remain complex adaptive systems in their own right, but through dynamic local interactions there is the possibility of emergent behaviours indicative of learning that transcends that of the individuals within the class. The social collective we know as a class becomes an instance of the Aristotlean adage, “The whole is greater than the sum of its parts.” (With the coda that we cannot understand the whole by merely understanding the components.) Davis, Simmt, and Sumara have segued from complexity-informed descriptions of educational collectives to discussions about facilitating the self-organization of classes into complex adaptive systems – learning systems, in their language. In this paper, I discuss complex adaptive systems and look at how Davis, Simmt, and Sumara developed their thesis that the class collective, rather than individual student, is the appropriate level to investigate learning and teaching. We conclude by addressing some of the possibilities and challenges inherent in such a redescription of communities of learners.


2014 ◽  
Vol 37 (6) ◽  
pp. 563-564 ◽  
Author(s):  
Tobias A. Mattei

AbstractIn self-adapting dynamical systems, a significant improvement in the signaling flow among agents constitutes one of the most powerful triggering events for the emergence of new complex behaviors. Ackermann and colleagues' comprehensive phylogenetic analysis of the brain structures involved in acoustic communication provides further evidence of the essential role which speech, as a breakthrough signaling resource, has played in the evolutionary development of human cognition viewed from the standpoint of complex adaptive system analysis.


2014 ◽  
Vol 2 (1) ◽  
pp. 85 ◽  
Author(s):  
Joachim Sturmberg

Miles and Mezzich have proposed person-centered medicine as the way forward to overcome the rapidly escalating crisis of dehuminisation of medical care and the healthcare system at large. The crisis in medical care is caused by a Zeitgeist characterised by 2 themes – conquering disease and profit maximising activities. Overcoming this crisis requires a change of the prevailing worldview and its reductionist thinking about discrete diseases to a worldview that recognises the complexities arising from the interconnections and interdependencies between all facets of a person’s life – his health and illness and disease trajectories. As Kant said: each man has his particular way of being in good health.This paper presents 5 themes that argue for a complexity based framework to achieve a person/patient-centered understanding of health and healthcare: (1) health, illness and disease are complex adaptive states that impact personhood; (2) healthcare must grow health; (3) healing results from personal sense-making and must be fostered; (4) complex adaptive systems thinking allows an exploration and understanding of personal and community health issues and (5) person/patient-centeredness results in an effective and efficient healthcare system.A person/patient-centered focus, the person/patient at the centre of concern, will result in a seamlessly integrated healthcare system. Such a system will show great diversity between communities, each having emerged as a result of best adaptation to local circumstances. Such a system will have substantial benefits – for the person (in terms of staying healthy) / patient (in terms of regaining his health), the community and the economy.


2013 ◽  
Vol 5 (2) ◽  
pp. 140-153
Author(s):  
Patrick Schotanus

The aim of this paper is to contribute to Jung's later work, with a particular focus on the numerical archetypes viewed from an investor's perspective. It attempts to achieve this via a three-pronged approach. First, placing complex psychology in the framework of complexity theory allows a robust acknowledgement and treatment of ‘elusive’ macroscopic properties, i.e. archetypal dynamics, involved in the ordering of a mind as a complex adaptive system. Second, modern insights in number sense (the direct intuition of what numbers mean) provide neuroscientific support for numerical archetypes and clarify their primacy. Third, this paper points to the empirical relevance of numerical archetypes in price discovery, the self-organizing principle of the capital markets (which allocate resources in modern society). The resulting proposition is that the (collective) mind's unconscious and conscious forces can be considered as ‘intelligent’ agents. The competition between these two domains provides the necessary condition to endogenously generate innovative outcomes, the essential capability of complex adaptive systems. According to this view producing such adaptive novelty is achieved in the form of intuitive insights and imagination, which result in a vast array of symbols, e.g. prices in the case of the market's mind.


Urban Science ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 61
Author(s):  
Annetta Burger ◽  
William G. Kennedy ◽  
Andrew Crooks

Increasingly urbanized populations and climate change have shifted the focus of decision makers from economic growth to the sustainability and resilience of urban infrastructure and communities, especially when communities face multiple hazards and need to recover from recurring disasters. Understanding human behavior and its interactions with built environments in disasters requires disciplinary crossover to explain its complexity, therefore we apply the lens of complex adaptive systems (CAS) to review disaster studies across disciplines. Disasters can be understood to consist of three interacting systems: (1) the physical system, consisting of geological, ecological, and human-built systems; (2) the social system, consisting of informal and formal human collective behavior; and (3) the individual actor system. Exploration of human behavior in these systems shows that CAS properties of heterogeneity, interacting subsystems, emergence, adaptation, and learning are integral, not just to cities, but to disaster studies and connecting them in the CAS framework provides us with a new lens to study disasters across disciplines. This paper explores the theories and models used in disaster studies, provides a framework to study and explain disasters, and discusses how complex adaptive systems can support theory building in disaster science for promoting more sustainable and resilient cities.


Author(s):  
David G. White ◽  
James A. Levin

The goal of this research study has been to develop, implement, and evaluate a school reform design experiment at a continuation high school with low-income, low-performing underrepresented minority students. The complexity sciences served as a theoretical framework for this design experiment. Treating an innovative college preparatory program as a nested complex adaptive system within a larger complex adaptive system, the school, we used features of complex adaptive systems (equilibrium, emergence, self-organization, and feedback loops) as a framework to design a strategy for school reform. The goal was to create an environment for change by pulling the school far from equilibrium using a strategy we call “purposeful perturbations” to disrupt the stable state of the school in a purposeful way. Over the four years of the study, several tipping points were reached, and we developed agent-based simulation models that capture important dynamic properties of the reform at these points. The study draws upon complexity theory in multiple ways that have supported improved education for low-achieving students.


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