scholarly journals Research on the Application of Deep Learning Technology Oriented to the Construction and Innovation of Smart City Image Cognition

2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Dan Shi ◽  
Lixin Song
Keyword(s):  
Big Data ◽  
Deep Learning ◽  
Urban Planning ◽  
Smart City ◽  
Quantitative Research ◽  
Smart Cities ◽  
Learning Technology ◽  
City Image ◽  
Urban Image ◽  
The City

City image is the observer’s subjective impression of the city image. It is an important content of urban geography and planning research and has important guiding significance for shaping a unique urban space. Cognitive research on traditional urban imagery is mainly by means of questionnaires and image sketches. It has problems such as high cost, low update frequency, and limited data coverage, which cannot meet the needs of quantitative research on smart cities and urban economic development in the information age. With the advent of the era of big data and the development of Internet technology, there are more and more quantitative research results on smart city image cognition with the help of big data and deep learning technology. It will be a feasible way to apply it to urban image research. This article combines the development and transformation of smart cities with the transformation of urban planning and leads to an innovation in the construction of urban image cognition based on urban image, active representation data as the data source, and deep learning as the core technology. The theoretical connotation and cognitive dimension of urban imagery are expanded to establish a cognitive model of urban imagery. The city image is cognitively analyzed from three dimensions: image structure, image type, and image evaluation. Specific cities are taken as examples to verify the applicability and scientificity of the cognitive methods and models, so as to enhance the practicality and applicability of urban imagery in urban planning. At the same time, this research is used to answer the development dilemma of big data, summarize the development trend of big data, and explore the new changes that artificial intelligence brings to urban planning. The experimental results show that the model we designed efficiently evaluates the image of the city and can also effectively recognize the image of the city in the main urban area of Chongqing.

Using a distributed deep learning algorithm for analyzing big data in smart cities

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammed Anouar Naoui ◽  
Brahim Lejdel ◽  
Mouloud Ayad ◽  
Abdelfattah Amamra ◽  
Okba kazar
Keyword(s):  
Big Data ◽  
Deep Learning ◽  
Data Analysis ◽  
Data Storage ◽  
Smart City ◽  
Smart Cities ◽  
Smart Environment ◽  
Data Systems ◽  
Content Type ◽  
Big Data Systems

PurposeThe purpose of this paper is to propose a distributed deep learning architecture for smart cities in big data systems.Design/methodology/approachWe have proposed an architectural multilayer to describe the distributed deep learning for smart cities in big data systems. The components of our system are Smart city layer, big data layer, and deep learning layer. The Smart city layer responsible for the question of Smart city components, its Internet of things, sensors and effectors, and its integration in the system, big data layer concerns data characteristics 10, and its distribution over the system. The deep learning layer is the model of our system. It is responsible for data analysis.FindingsWe apply our proposed architecture in a Smart environment and Smart energy. 10; In a Smart environment, we study the Toluene forecasting in Madrid Smart city. For Smart energy, we study wind energy foresting in Australia. Our proposed architecture can reduce the time of execution and improve the deep learning model, such as Long Term Short Memory10;.Research limitations/implicationsThis research needs the application of other deep learning models, such as convolution neuronal network and autoencoder.Practical implicationsFindings of the research will be helpful in Smart city architecture. It can provide a clear view into a Smart city, data storage, and data analysis. The 10; Toluene forecasting in a Smart environment can help the decision-maker to ensure environmental safety. The Smart energy of our proposed model can give a clear prediction of power generation.Originality/valueThe findings of this study are expected to contribute valuable information to decision-makers for a better understanding of the key to Smart city architecture. Its relation with data storage, processing, and data analysis.

scholarly journals Managing Large Amounts of Data Generated by a Smart City Internet of Things Deployment

2016 ◽  
Vol 12 (4) ◽  
pp. 22-42 ◽  
Author(s):  
Jorge Lanza ◽  
Pablo Sotres ◽  
Luis Sánchez ◽  
Jose Antonio Galache ◽  
Juan Ramón Santana ◽  
...  
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Information And Communication Technologies ◽  
Smart City ◽  
Smart Cities ◽  
Communication Technologies ◽  
Added Value ◽  
Amount Of Information ◽  
Information And Communication ◽  
The City

The Smart City concept is being developed from a lot of different axes encompassing multiple areas of social and technical sciences. However, something that is common to all these approaches is the central role that the capacity of sharing information has. Hence, Information and Communication Technologies (ICT) are seen as key enablers for the transformation of urban regions into Smart Cities. Two of these technologies, namely Internet of Things and Big Data, have a predominant position among them. The capacity to “sense the city” and access all this information and provide added-value services based on knowledge derived from it are critical to achieving the Smart City vision. This paper reports on the specification and implementation of a software platform enabling the management and exposure of the large amount of information that is continuously generated by the IoT deployment in the city of Santander.

Deconstructing Smart Cities

Big Data ◽  
2016 ◽  
pp. 1957-1969
Author(s):  
Michael Batty
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Smart City ◽  
New Technologies ◽  
Smart Cities ◽  
Public Realm ◽  
The Public ◽  
Important Challenge ◽  
Urban Problems ◽  
The City

This chapter defines the smart city in terms of the process whereby computers and computation are being embedded into the very fabric of the city itself. In short, the smart city is the automated city where the goal is to improve the efficiency of how the city functions. These new technologies tend to improve the performance of cities in the short term with respect to how cities function over minutes, hours or days rather than over years or decades. After establishing definitions and context, the author then explores questions of big data. One important challenge is to synthesize or integrate different data about the city's functioning and this provides an enormous challenge which presents many obstacles to producing coherent solutions to diverse urban problems. The chapter augments this argument with ideas about how the emergence of widespread computation provides a new interface to the public realm through which citizens might participate in rather fuller and richer ways than hitherto, through interactions in various kinds of decision-making about the future city. The author concludes with some speculations as to how the emerging science of smart cities fits into the wider science of cities.

Deconstructing Smart Cities

2014 ◽  
pp. 1-13 ◽  
Author(s):  
Michael Batty
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Smart City ◽  
New Technologies ◽  
Smart Cities ◽  
Public Realm ◽  
The Public ◽  
Important Challenge ◽  
Urban Problems ◽  
The City

This chapter defines the smart city in terms of the process whereby computers and computation are being embedded into the very fabric of the city itself. In short, the smart city is the automated city where the goal is to improve the efficiency of how the city functions. These new technologies tend to improve the performance of cities in the short term with respect to how cities function over minutes, hours or days rather than over years or decades. After establishing definitions and context, the author then explores questions of big data. One important challenge is to synthesize or integrate different data about the city's functioning and this provides an enormous challenge which presents many obstacles to producing coherent solutions to diverse urban problems. The chapter augments this argument with ideas about how the emergence of widespread computation provides a new interface to the public realm through which citizens might participate in rather fuller and richer ways than hitherto, through interactions in various kinds of decision-making about the future city. The author concludes with some speculations as to how the emerging science of smart cities fits into the wider science of cities.

Big Data Utilization, Benefits, and Challenges for Smart City Implementation

2019 ◽  
pp. 42-54 ◽  
Author(s):  
Sonali Vyas ◽  
Deepshikha Bhargava
Keyword(s):  
Big Data ◽  
High Velocity ◽  
Smart City ◽  
Smart Cities ◽  
Digital Information ◽  
Data Utilization ◽  
Performance Quality ◽  
Big Data Applications ◽  
The City ◽  
Advanced Version

With the rapid advancement of technology, everything is transforming into smarter versions. The term smart city means a technologically strengthened and advanced version of the city. Smart cities utilize digital information and techniques for improving services like performance, quality, etc. Big data technology and methods are utilized for handling the vast volume, high velocity and wide variety of data related to cities. This chapter discusses the big data utilization for making smart cities and also throws light on various applications where efficient analysis of services can be carried out using Big Data techniques. The main objective of this chapter will be to provide knowledge of big data implementation for the smart city and its services. This chapter will also investigate various prospects, benefits, and challenges of absorbing big data utilization for smart cities. It will also discuss some case studies related to big data applications for smart city services. It will also propose some open issues related to big data implementation for the smart city.

scholarly journals Managing Large Amounts of Data Generated by a Smart City Internet of Things Deployment

2019 ◽  
pp. 870-892
Author(s):  
Jorge Lanza ◽  
Pablo Sotres ◽  
Luis Sánchez ◽  
Jose Antonio Galache ◽  
Juan Ramón Santana ◽  
...  
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Information And Communication Technologies ◽  
Smart City ◽  
Smart Cities ◽  
Communication Technologies ◽  
Added Value ◽  
Information And Communication ◽  
The City ◽  
Specification And Implementation

The Smart City concept is being developed from a lot of different axes encompassing multiple areas of social and technical sciences. However, something that is common to all these approaches is the central role that the capacity of sharing information has. Hence, Information and Communication Technologies (ICT) are seen as key enablers for the transformation of urban regions into Smart Cities. Two of these technologies, namely Internet of Things and Big Data, have a predominant position among them. The capacity to “sense the city” and access all this information and provide added-value services based on knowledge derived from it are critical to achieving the Smart City vision. This paper reports on the specification and implementation of a software platform enabling the management and exposure of the large amount of information that is continuously generated by the IoT deployment in the city of Santander.

scholarly journals Smart City Planning

2018 ◽  
Vol 7 (3) ◽  
pp. 1-21 ◽  
Author(s):  
Ulrik Ekman
Keyword(s):  
Urban Planning ◽  
Complexity Theory ◽  
Smart City ◽  
City Planning ◽  
Smart Cities ◽  
Urban System ◽  
Theory And Practice ◽  
Complex Adaptive ◽  
The Face ◽  
The City

This article reflects on the challenges for urban planning posed by the emergence of smart cities in network societies. In particular, it reflects on reductionist tendencies in existing smart city planning. Here the concern is with the implications of prior reductions of complexity which have been undertaken by placing primacy in planning on information technology, economical profit, and top-down political government. Rather than pointing urban planning towards a different ordering of these reductions, this article argues in favor of approaches to smart city planning via complexity theory. Specifically, this article argues in favor of approaching smart city plans holistically as topologies of organized complexity. Here, smart city planning is seen as a theory and practice engaging with a complex adaptive urban system which continuously operates on its potential. The actualizations in the face of contingency of such potential are what might have the city evolve over time, its organization, its wholeness, and its continued existence being at stake from moment to moment.

scholarly journals Digitization and urban governance: The city as a reflection of its data infrastructure

2021 ◽  
pp. 002085232110332
Author(s):  
Ali Bayat ◽  
Peter Kawalek
Keyword(s):  
Big Data ◽  
Smart City ◽  
Urban Governance ◽  
Smart Cities ◽  
Engaged Scholarship ◽  
Data Governance ◽  
Data Infrastructure ◽  
Big Data Technologies ◽  
Data Infrastructures ◽  
The City

This article introduces the ‘House Model’, an integrated framework consisting of four data governance modes, based on the urban and smart city vision, context, and big data technologies. The model stems from engaged scholarship, synthesizing and extending the academic debates and evidence from existing smart city initiatives. It provides a means for comparing cities in terms of their digitization efforts, helps the planning of more effective urban data infrastructures and guides future empirical research in this area. The article contributes to the literature examining the issue of big data and its governance in local government and smart cities. Points for practitioners Data is a vital part of smart city initiatives. Where the data comes from, who owns it and how it is used are all important questions. Data governance is therefore important and has consequences for the overall governance of the city. The House Model presented in this article provides a means for organizing data governance. It relates questions of data governance to the history and vision of smart city initiatives, and provides a typology organizing these initiatives.

scholarly journals THE URBAN PLANNING CONCEPT BASED ON SMART CITY APPROACH

2018 ◽  
Vol 3 (2) ◽  
pp. 63 ◽  
Author(s):  
Muhammad Bakri ◽  
Anita Ahmad Kasim
Keyword(s):  
Urban Planning ◽  
Urban Growth ◽  
Smart City ◽  
Urban Areas ◽  
Urban Population ◽  
Smart Cities ◽  
Main Factors ◽  
Urban Population Growth ◽  
The City ◽  
Planning Concept

<p><em>Smart City comes as a strategy to reduce the problem due to rapid urban growth and urbanization. The concept of Smart City is needed to ensure the conditions of a habitable City in the context of rapidly growing urban population growth. The urgency of this challenge prompted many cities to begin to find smarter ways of managing urban areas. One way to make the concept of the smart city is to make the city an icon that is sustainable and livable. This study aims to provide the necessary information in building and developing a city through the smart city approach. This paper clarifies the meaning of the word "smart" in the city context through an approach based on an in-depth literature review of the relevant study. This study will identify the main factors and characteristics that characterize smart cities. The method used to obtain various factors and the characteristics of the Smart City in the arrangement of a region is done by studying various kinds of the literature of various concepts and components in the Smart City. The results obtained in this study there is a concept of Smart City in urban planning by mapping various factors and characteristics in the Smart City. </em></p><p><strong>Keywords</strong><em>: Smart City, Urban planning, smart city characteristic </em></p>

Smart Dashboards for Smart City—A Platform to Engage with Citizen

2019 ◽  
Vol 16 (8) ◽  
pp. 3461-3465 ◽  
Author(s):  
Hemalata Vasudavan ◽  
Sumathi Balakrishnan ◽  
TeeWee Jing ◽  
Kartini Vijay ◽  
Saraswathy Shamini Gunasekaran
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Smart City ◽  
Data Analytics ◽  
Smart Cities ◽  
Big Data Analytics ◽  
Key Indicators ◽  
The City

Smart City is the term composed for a city that aggressively balances itself through ICT based urban solutions and solving multiple problems faced by the ever complex urban lifestyle. Big data analytics is one of the best innovation to process extracted data from this Internet of Things (IoT) Ecosystem of the smart city. In this ecosystem, the communication and engagement with the city residents are very important. The smart dashboard is a hyper connected platform to effectively project the smart city dimension’s performance to stakeholder and residents. Thus creating an instant engagement with the citizens. Although most of the smart cities has been computing all the data gathered in the city using the most sophisticated data analytics tools, it has not effectively interfaced it to the benefit of city residents. A Smart Dashboard is seen as an enabler to the smart city dimensions but many of the current smart dashboards are still elusive and faces many challenges. There will be discussions about the importance of smart dashboard, a list of key indicators and the challenges to implementing this dashboard.

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