Smart City Design Research Articles

Design and Development of Multi-Objective Hybrid Clustering Framework for Smart City in India Using Internet of Things

The drastic growth of smart city has considerably gained attention around the world in the international policies and systematic literature. Numerous specialists should include diverse opinions owing to the hurdles to the design of smart cities in India. Thus, these experts have also offered their opinions regarding public, agriculture, industry and academia-fields, which help in developing the smart cities. Generally, more limitations have to be faced with offering energy optimisation and superior performance in Internet of Things (IoT)-enabled smart cities. In wireless sensor networks (WSNs) and IoT, the sensors or IoT devices or nodes are often grouped into clusters that result in selecting the cluster head, which gathers information from the entire nodes in cluster and plainly transmits with the base station. This paper makes an attempt on the development of smart cities in India using the hybrid meta-heuristic-based multi-objective cluster head selection model. The proposed model focusses on the design and development of new smart city model applicable for India by considering a multi-objective function using the constraints like distance, delay, energy, load and temperature of the IoT devices. The optimisation of these variables during the smart city development model by IoT is accomplished by a new hybrid Deer Hunting-Tunicate Swarm Optimisation (DH-TSO) algorithm. The performance of the proposed model is verified through a comparative analysis using various state-of-the-art optimisation models by concerning the number of alive nodes, and normalised energy, and thus ensures the overall lifetime of the network.

Research on Architectural Planning and Landscape Design of Smart City Based on Computational Intelligence.

City brain is a complex system, including online center, server network, and system with given algorithm. The core of the city brain is the intelligent system. After putting the urban brain into the intelligent nerve center, on the basis of not changing its original data structure, combining its own characteristics for design and then integrating into application, it can intelligently change the urban management mode. Urban planning leads the development of smart cities on a certain meaning, and smart city planning must have scientific and rational urban planning. The intelligent model is used to make urban planning form a more modern, convenient, and reasonable urban architectural planning. Some influential books on classical architectural theory are the theoretical basis of intelligent urban planning and even the trend and implementation blueprint of how smart cities will develop in the future. In this paper, four algorithms, ant colony algorithm, particle swarm optimization algorithm, genetic algorithm, and improved ant colony algorithm, are proposed to optimize the characteristics of urban architectural planning and landscape design; especially the security research of architecture and landscape characteristics is very important. The improved ant colony algorithm has the shortcoming of insufficient optimization ability in the face of complex path selection. By improving the influencing factors, a new ant colony algorithm is created. The improved ant colony algorithm achieves the best in security features, so it is advocated to use this algorithm for planning and design. The urban form in smart city aims to create a beautiful and comfortable urban environment, improve the competitiveness of cities in the rapid urbanization process, improve the living standards of the public, and shape the image of this beautiful city.

Kolaborasi Model Quadpel Helix Dalam Pengembangan Smart City; Sebuah Tinjauan Teoritis

The idea of Smart City Development has become a trend for the last 10 years. The key concept in this development emphasizes collaboration. Providing concepts, building designs, up to the implementation of building cities that are able to accommodate various interests. But how does this vision relate to current practice in cities? This paper discusses the role of stakeholders who collaborate and build cooperation networks for the development of Smart City. The approach used in this article is a form of collaboration and the idea of a "quadruple helix" for urban innovation. quadruple helix model as a smart city design principle in which technological and social innovations result from cooperation and synergy between four stakeholder groups: administration, business, science, and residents. This study finds information that each entity has a major role in the development of Smart City. Then there is the need for other entities in other helix models that need to be involved in the development of smart cities in urban settings.

The Smart in Smart Cities: A Framework for Image Classification Using Deep Learning.

The need for a smart city is more pressing today due to the recent pandemic, lockouts, climate changes, population growth, and limitations on availability/access to natural resources. However, these challenges can be better faced with the utilization of new technologies. The zoning design of smart cities can mitigate these challenges. It identifies the main components of a new smart city and then proposes a general framework for designing a smart city that tackles these elements. Then, we propose a technology-driven model to support this framework. A mapping between the proposed general framework and the proposed technology model is then introduced. To highlight the importance and usefulness of the proposed framework, we designed and implemented a smart image handling system targeted at non-technical personnel. The high cost, security, and inconvenience issues may limit the cities’ abilities to adopt such solutions. Therefore, this work also proposes to design and implement a generalized image processing model using deep learning. The proposed model accepts images from users, then performs self-tuning operations to select the best deep network, and finally produces the required insights without any human intervention. This helps in automating the decision-making process without the need for a specialized data scientist.

DEVELOPMENT OF A SMART CITY CONCEPT IN VIRTUAL REALITY ENVIRONMENT

Abstract. There is an increasing interest in smart city concept as a technology-based alternative to conventional urban planning approaches. The design and implementation of smart cities require multidisciplinary efforts. As one of the first examples, a smart city concept was developed in Turkey in the year 2018 in collaboration with researchers and experts from various disciplines, such as geomatics and civil engineers, architects, computer scientists and urban planners. The developed concept aimed at designing a city district that targets sustainability, human-centricity, smartness, and safety, along with a sense of place and reflects local expectations in an unconstructed sub-urban area. In the project, the collaborative design process and the usability issues of the presentation environments have been of importance for geomatics professionals. Within the study, the existing settlement areas were modelled by using aerial photogrammetric data and combined with elements designed in various Computer-aided design (CAD) software. In this paper, the smart city design elements, which originate from the design principles such as ensuring nature conservation, green, cultural, safe and smart living spaces, and social responsibility, are explained briefly. The city was presented to the stakeholders via Unity game engine for a realistic experience prior to construction. The potential of Virtual Reality (VR) environments for the design, modelling, and visualization of very high detailed smart city concept is presented and various issues are discussed. The model experiment videos with VR, web-based model and project video can be accessed via the web page www.bizimsehir.org.

Internet of Things Driven Smart Cities in Post Pandemic Era

The rise of the Internet of Things (IoT) driven smart cities is progressively revolutionizing different aspects of human life, including transportation, communication, health, automotive and security. Several IoT initiatives and experimental setting have been proposed in recent years to establish digital and smart infrastructures. Despite the hype, the COVID-19 pandemic still has an impact on many aspects of urban life, raising concerns about the viability of past and contemporary patterns of urban design and growth. The COVID-19 epidemic has significantly altered everyday lives, damaged the economy of several countries, affected global economic goals, and so on. In such cases, it is highly required to initiate a research discussion on the influence of COVID-19 in smart cities. Several researchers and policymakers have previously recognized the need for improved smart city infrastructure. This research study reviews the multiple research discussions that design and develop new urban planning and smart city design paradigms and models in the post-COVID period that reflect the insights gained from the pandemic. The study also discussed how smart cities innovation, operations, and preventive maintenance will be influenced after COVID-19. Finally, the proposed study concluded that the smarter cities equipped with IoT driven technologies will be able to prevent pandemics in the near future.

Smart Bus Terminus: Sustainable Urban Public Transport Solution Through BIM and GIS Integrated Approach

Smart city / digital city is engaging in Big Data which will be utilized in monitoring and optimizing the urban systems to minimize resource consumption and maximize the quality of life. To implement the concept of “smart cities”, smart city components, design innovation and prototypes must be studied in detail which will be beneficial in understanding the features. India is moving towards becoming one of the developed nations, the source of revenue is highly dependent on public contributions, especially through the transportation sector. The population of India is majorly comprised of the middle-class income category. Their livelihood mainly depends on the regional level jobs and for commute, they prefer public transportation especially Buses. For lodging these buses that are huge in number, Bus Terminus become an integral infrastructure component. In Indian cities, the existing bus terminus appears to be poorly designed and highly congested irrespective of their sizes. Interventions of modern methodologies to improve the conditions in the existing bus terminus in various Indian cities and reconstructing them is of utmost priority for urban planners and policymakers to reach sustainable cities. The objective of adopting smart innovative solutions in Bus Terminus is to reduce pollution, congestion of traffic, improve safety, time optimization and cost reduction. Modern bus terminus must accommodate some key features such as green buildings and utilization of eco-friendly materials for construction, incorporating real-time response, installing solar panels for energy efficiency and power generation, waste segregation and recycling, the hybrid modal form of transport i.e., both traditional and electric vehicles, etc. In the present study, the attempt has been made to develop an artistic view of a “Smart Bus Terminus” prototype that can be adopted at regional and global levels. Autodesk REVIT Architecture and AutoCAD have been used to design and create 3D models; Geographical Information System tools have been adopted for the recommendation of site selection.

An Optimization Model for Landscape Planning and Environmental Design of Smart Cities Based on Big Data Analysis

This paper adopts “digital landscape design logic,” analyzes and researches smart city and digital landscape design, and builds a digital city based on design logic, design basis, environment analysis, and results in a presentation based on the dilemma of landscape garden planning and design at this stage and the development trend of the smart garden and digital landscape design. The optimization model of the landscape and environment design is constructed based on design logic, design basis, environment analysis, and result presentation. First, on the Hadoop distributed computing platform based on the MapReduce parallel processing framework, we implement the massive small file processing methods (Hadoop Archives, CombineFileInputFormat, and Sequence Files) to compensate for the inherent defects of Hadoop and experimentally compare the memory consumption and execution efficiency of the three methods to propose a choice. The memory consumption and execution efficiency of the three methods are experimentally compared to propose a selection strategy. Finally, based on the MR-PFP algorithm, we parallelize the frequent itemset in-cab trajectory big data to generate interesting strong association rules. The experimental results show that the MR-PFP algorithm has better speedup ratio performance and higher mining efficiency than the parallel frequent pattern (PFP) growth algorithm. The research and analysis focused on the digital implementation of the standalone environmental analysis, using Rhino software and Grasshopper visual programming language to build parametric logic, establish parametric analysis models, and conduct a comprehensive analysis of the current environment. The study explores the use of digital landscape design methods and technologies in the landscape design process. Using Rhino + Grasshopper parametric and visualization programming software, we built parametric analysis models around elevation, slope, slope direction, water catchment, and viewable area and used mapping and overlay techniques to quantify the urban space. Finally, the purpose of collecting, monitoring, analyzing, simulating, creating, and reproducing landscape information is achieved.

Internet of things based smart city design using fog computing and fuzzy logic

• “Internet of Things based Smart City Design using Fog Computing and Fuzzy Logic”. • An edge computing paradigm using human interactions for their decision-making process. • Employs probabilistic history-based parameters that keep track of node interactions. • Context-aware smart paradigm considering predictability ratios. • A nature-inspired algorithm used to make the routing considerations. • A fuzzy rule-based system using power-buffer capacity-based index to make classes. The prevalence of IoT based technology in contemporary society allows for the planning of smart city infrastructure with individually owned devices as participating nodes in a social smart network. Edge computing application into such an IoT network facilitates the distributed computing framework by bringing the computational application closer to the end-users in form of Fog sub-networks, comprising the local participating end-user IoT nodes as service requesters and specialized servers catering to the requests, modelled for the infrastructure category they are delivering (Smart healthcare, ITS, Smart architecture, etc.). Opportunistic-based last-mile connectivity between the Fog servers and participating nodes aides the dynamicity of the topology for efficient information. Aiding the same, the proposed edge computing enabled, sustainable, opportunistic IoT-based intuitive data exchange, collection and operation scheme that employs a dynamic routing procedure that considers human interactions, their movement patterns and their decision-making process. The proposed scheme employs probabilistic history-based parameters that keep track of node interactions. The interactions are modelled on the Firefly PSO, allowing exploitation of the social mobility. The Fuzzy logic is used for hop decision making based on the social and attribute-based parameters which mimic intuitive and pragmatic decision making of humans in terms of social interactions and mobility.

Smart City Dimensions and Associated Risks: Review of literature

Countries have been working on implementing smart city concepts in different regions. The need for the use of information and communication technology in various forms is needed in such cities. There are different dimensions that are to be considered for smart city planning and implementation. This complexity of the dimension, the use of technology, and their integration bring the risk perspectives into the implementation of the smart city concept. If such risks are not adequately understood and addressed, they can create issues in terms of privacy and security and, therefore, the functioning of smart cities. In this review, the identification of dimensions, smart city assessment tools, the available technologies, and the technical and non-technical risk parameters related to smart cities implementation are discussed. The current methods of risk assessment and the possible enhancements are highlighted. The findings of the literature review illustrate that not all smart cities adapt all of the smart city dimensions. The dominant technology used in smart cities’ applications is found to be the Internet of Things, Artificial Intelligence, and blockchain. The paper also provides some research directions for the design, implementation, and operation of smart cities.

(Retracted) Role of video sensors in observing visual image design in the construction of smart cities

Due to the advancement of software and hardware technologies such as geographic information systems, for example, optical fiber storage, mobile network, digital camera, and high-definition network, it has promoted the establishment of a data digital management system. Network sharing, to a certain extent, makes it the smart city video sensor of today’s era. It is a key component of the city’s smart management system. In the context of the rapid development of the information age, I explore the role of video sensors in the visual design of smart cities. I propose three methods to analyze the theory of big data video sensors: theoretical analysis of big data video sensors, information visualization, and visual signal output, and then model the video signal output to visualize the complex multilayer network decision. Starting from the RBF neural network, I simulate a video perception prediction model system, import the data into Matlab for experimental analysis and simulation, and compare RBF and BP are based on both data predictions. RBF obviously has stronger predictive video perception. Experimental data show that the error between video perception and actual data is within 3%. It can be seen that video sensors play a key role in the construction of smart cities.

Smart City Public Art Planning and Design in a Multimedia Internet of Things Environment Integrating Scene Elements

Public art planning and design in the context of smart cities need to keep pace with the times, but the integrity of the original scene needs to be maintained in the process of public art design. Therefore, this paper combines the elements of the scene and integrates the Internet of Things smart city to conduct public art planning and design research. Moreover, based on the multimedia Internet of Things environment, this paper analyzes the effects of virtual reality technology in urban public art planning and design and gives the overall optimization ideas for the organization and rendering of VR scene data. Then, this paper studies the organization and rendering optimization methods of the terrain scene model and the scene model, respectively. The experimental research results show that the smart city public art planning and design system under the multimedia Internet of Things environment designed in this paper has a good smart city public art planning and design effect.

Research on the Application of AI Artificial Intelligence Technology in Intelligent Buildings

This study aims to reveal the application of artificial intelligence, and determine the opportunities and challenges of artificial intelligence application in the construction industry, and proposes the design of applying artificial intelligence technology, which provides a research basis for future smart city design and development. Additionally, AI applications in construction are pointed to in this study, and the study provides insights into key applications of AI for construction-specific challenges.

Changing the Rules of Play in Long Beach, California: Smart Cities, Infrastructure, and the Well-Played Game

ABSTRACT Drawing on insights from focus group interviews (n = 82) conducted during the development of Long Beach, California’s Smart City Strategic Initiative (SCSI), we examine the extent to which the four guiding principles of the SCSI correspond to Long Beach residents’ perceptions and concerns about the smart city: design for equity; earn public interest; cultivate local expertise; build civic resilience. Participants expressed widespread wariness of the fairness of smart city technologies. We find that Bernard De Koven’s theory of the well-played game constitutes a promising framework for the fair deployment and maintenance of smart city technologies. Based on De Koven’s work and participant insights, we provide a series of empirically-grounded and theoretically informed implications for design intended to leverage the collaborative spirit of play communities in the design of smart cities.

Non-human Personas. Including Nature in the Participatory Design of Smart Cities

For the past decades humans have been placed at the centre of designing information and communication technologies (ICT), leading to the rise in prominence of human-centred design. The field of smart cities has equally adopted notions of citizen participation as a way to ensure that technological solutions improve people’s livelihoods. However, these kinds of processes treat the urban environment as separate from nature, promoting human comfort and convenience over planetary health and wellbeing. Motivated by these growing concerns that highlight the urgency to reconsider how we define and practice participation in smart cities and in human-centred ICT solutions more broadly, this article assesses how the personas method can be adapted to include more-than-human perspectives in the design process. Based on a case study, which involved designing smart urban furniture for human and non-human use, we introduce a framework for developing and employing non-human personas. As a key element of the framework, we describe a middle-out approach for forming a coalition that can speak on behalf of the non-human species that are impacted by design decisions. We demonstrate how the framework can be used through its retrospective application on two research-led smart city projects. The article concludes with a discussion of key principles for creating and using non-human personas in design projects.

URBAN ENVIRONMENTAL DESIGN STRATEGIES DURING THE COVID-19 PANDEMIC

The article indicates that from the beginning of the COVID-19 crisis, the scientific community has been continuously trying to assess the virus, its socio-environmental impacts, regulatory/adaptation policies, and plans. The emergency is to develop pandemic-resilient city planning and management in order to tackle the infectious diseases during COVID-19. Such development includes the reframing of unsustainable urban patterns, hazards, and social inequalities to be prepared for the emerging cases. In this study, we focus on the assessment of disaster risk management (DRM), which will help to develop pandemic-resilient urban strategies (response, mitigation, and preparedness phase) through analyzing previously published literature. The article presents the Short- and long-term recommendations for pandemic resilience urban planning and design have also been provided. In the response phase, implementation of the smart and resilient city design and policies has been highlighted to identify disease transmission. In the mitigation phase, new technological approaches can be adopted for better management of present and future pandemics. The physical (urban access, infrastructure, environmental factors, and land use patterns) and non-physical (socio-cultural, governance, and economic factors) aspects of resilient urban strategies have been focused, which may help to develop understanding of health- and disaster-related risks in pandemic. In the preparedness phase, proactive measures such as capacity building of people toward any outbreak and different simulation processes (models of transmission pattern) can be adopted for future pandemics. We also discuss about the enhancement of urban resiliency in housing, public spaces, and cities that may bring the effective outcome of DRM framework to combat pandemic. The study focuses on the major lessons that can be adopted for post-pandemic urban resilient planning related to disaster management and climate change adaptation, preventing extensive challenges of sustainability apart. In the following months and years, it will be difficult to assess various changes to develop urban planning and design in the post-COVID-19 world. However, this study expresses the possibility of creating good opportunities for policymakers and city planners to undertake significant transformative and advanced actions during the three different phases of DRM. This study presents a novel approach to delineate the scope of DRM framework in achieving more resilient cities (RC) to tackle future pandemics. This study will also crucially help the planners and decision-makers in better assessing and addressing the strategic and resilient urban design and planning approach in future.

Barriers of big data analytics for smart cities development: a context of emerging economies

ABSTRACT Smart cities use Big Data Analytics (BDA) for efficient and effective utilisation of resources and the adoption of big data analytics faces several barriers. Therefore, the main purpose of this research is to investigate the key barriers towards the adoption of BDA in smart cities development. To fulfil this objective, initially, 13 barriers of BDA adoption is identified and then prioritise using Best Worst Method (BWM). The finding shows that data complexity, framework for BDA adoption, lack of technologies for BDA are the important barriers that hinder the incorporation of BDA in smart city development. The main contribution of this study is that it proposes a framework for the evaluation of the BDA adoption barrier related to smart city development. The proposed framework can be helpful for policy and decision-makers to analyse the barriers of BDA adoption in smart city design and development. This study is helpful in undertaking these barriers in an optimised manner for the accelerated development of smart cities.

Smart-City Regulation

Consider that 26.3 million people live in Shanghai and 20 million live in Beijing as of 2019. Now consider that these 46.3 million people live within an area of approximately 23,000 km². By comparison, Canada’s population in 2019 was 37.6 million and the area of Canada is approximately 10 million km². China is on the leading edge of smart-city projects because population density gives it little choice. China must take bold steps in terms of both technology and regulation to cope with the demands for social management, which these megacities create. Accordingly, about half of the Smart City Projects globally are in China. 
 Many smart cities pilot projects are underway across China addressing many infrastructures and other organizational concerns. One such organizational concern is coping with the solid waste generated in cities. China produces more than 300 million tons of solid waste per year, and much of it comes from its cities.
 
 This research project explores China's food and beverage delivery online platforms and the waste they cause. In 2019, this industry has developed rapidly, generating economic activity valued at ¥ 653.6 billion that year ($CAD 121 billion). Out of a total population of 1.4 billion, 460 million people are currently consumers of these online platforms. Most of these consumers live in China’s megacities. This consumption is not projected to decrease post-pandemic. The problem is that solid waste from this industry in 2019 weighed approximately 2.7 million tons.
 
 This paper analyzes reasons why the online food take-out industry has caused a plastic waste surge from the perspective of China's environmental legislation, law enforcement efficiency, and recycling subsidies. At the same time, through the case study of the German Packaging Law, this paper suggested on the management and recycling of Chinese take-out packaging were put forward.
 
 The Chinese government has issued national standards for the design and construction of smart cities. This paper explores how to use legal governance and supervision in smart city design and operation to assist in implementing environmental regulations to control the take-out waste. The take-out waste problem does not only exist in China. Almost all major cities in the world are facing this problem. China's experiences may provide a new path for the city's solid waste disposal and other environmental issues and lead the cities to explore more environmental protection possibilities.

Affective computing scholarship and the rise of China: a view from 25 years of bibliometric data

Affective computing, also known as emotional artificial intelligence (AI), is an emerging and cutting-edge field of AI research. It draws on computer science, engineering, psychology, physiology, and neuroscience to computationally model, track, and classify human emotions and affective states. While the US once dominated the field in terms of research and citation from 1995–2015, China is now emerging as a global contender in research output, claiming second place for the most cited country from 2016–2020. This article maps the rhizomatic growth and development of scientific publications devoted to emotion-sensing AI technologies. It employs a bibliometric analysis that identifies major national contributors and international alliances in the field over the past 25 years. Contrary to the ongoing political rhetoric of a new Cold War, we argue that there are in fact vibrant AI research alliances and ongoing collaborations between the West and China, especially with the US, despite competing interests and ethical concerns. Our observations of historical data indicate two major collaborative networks: the “US/Asia-Pacific cluster” consisting of the US, China, Singapore, Japan and the “European” cluster of Germany, the UK, and the Netherlands. Our analysis also uncovers a major shift in the focus of affective computing research away from diagnosis and detection of mental illnesses to more commercially viable applications in smart city design. The discussion notes the state-of-the-art techniques such as the ensemble method of symbolic and sub-symbolic AI as well as the absence of Russia in the list of top countries for scientific output.

Comparison on Land-Use/Land-Cover Indices in Explaining Land Surface Temperature Variations in the City of Beijing, China

The urban thermal environment is closely related to landscape patterns and land surface characteristics. Several studies have investigated the relationship between land surface characteristics and land surface temperature (LST). To explore the effects of the urban landscape on urban thermal environments, multiple land-use/land-cover (LULC) remote sensing-based indices have emerged. However, the function of the indices in better explaining LST in the heterogeneous urban landscape has not been fully addressed. This study aims to investigate the effect of remote-sensing-based LULC indices on LST, and to quantify the impact magnitude of green spaces on LST in the city built-up blocks. We used a random forest classifier algorithm to map LULC from the Gaofen 2 (GF-2) satellite and retrieved LST from Landsat-8 ETM data through the split-window algorithm. The pixel values of the LULC types and indices were extracted using the line transect approach. The multicollinearity effect was excluded before regression analysis. The vegetation index was found to have a strong negative relationship with LST, but a positive relationship with built-up indices was found in univariate analysis. The preferred indices, such as normalized difference impervious index (NDISI), dry built-up index (DBI), and bare soil index (BSI), predicted the LST (R2 = 0.41) in the multivariate analysis. The stepwise regression analysis adequately explained the LST (R2 = 0.44) due to the combined effect of the indices. The study results indicated that the LULC indices can be used to explain the LST of LULC types and provides useful information for urban managers and planners for the design of smart green cities.