scholarly journals Whose smart city? : A framework and discussion guide for planning open and inclusive urban digital experiments

2021 ◽  
Author(s):  
Steven Coutts
Keyword(s):  
Big Data ◽  
Citizen Participation ◽  
Smart City ◽  
Smart Cities ◽  
Popular Literature ◽  
Research Approach ◽  
New Paradigm ◽  
Urban Informatics ◽  
Planning Profession ◽  
Action Research Approach

‘Smart cities’ represent the integration of ‘big data’ collected via networked cameras, sensors, and meters into the urban fabric with the overarching goal of making infrastructure more efficient and improving citizens’ lives. While data has been used to support planning efforts for decades, this new paradigm of ‘urban informatics’ means that planning will increasingly be driven by data. However, the planning profession is still grappling with how existing practices might need to adapt to tackle the challenges of planning in the smart city. Accordingly, there is a gap in terms of educational resources on smart cities aimed at planning professionals. Through an action research approach involving a review of recent academic and popular literature on smart cities, this project synthesizes a set of ‘best practices’ and proposes a discussion guide for planning professionals to learn about the implications for their practice in a world where big data shapes our cities. Keywords: smart cities, urban informatics, planning ethics, Big Data, citizen participation

scholarly journals Whose smart city? : A framework and discussion guide for planning open and inclusive urban digital experiments

2021 ◽  
Author(s):  
Steven Coutts
Keyword(s):  
Big Data ◽  
Citizen Participation ◽  
Smart City ◽  
Smart Cities ◽  
Popular Literature ◽  
Research Approach ◽  
New Paradigm ◽  
Urban Informatics ◽  
Planning Profession ◽  
Action Research Approach

‘Smart cities’ represent the integration of ‘big data’ collected via networked cameras, sensors, and meters into the urban fabric with the overarching goal of making infrastructure more efficient and improving citizens’ lives. While data has been used to support planning efforts for decades, this new paradigm of ‘urban informatics’ means that planning will increasingly be driven by data. However, the planning profession is still grappling with how existing practices might need to adapt to tackle the challenges of planning in the smart city. Accordingly, there is a gap in terms of educational resources on smart cities aimed at planning professionals. Through an action research approach involving a review of recent academic and popular literature on smart cities, this project synthesizes a set of ‘best practices’ and proposes a discussion guide for planning professionals to learn about the implications for their practice in a world where big data shapes our cities. Keywords: smart cities, urban informatics, planning ethics, Big Data, citizen participation

scholarly journals Sustainable Smart City—Opening a Black Box

2021 ◽  
Vol 13 (2) ◽  
pp. 769
Author(s):  
Mona Treude
Keyword(s):  
Sustainable Development ◽  
Citizen Participation ◽  
Smart City ◽  
Evolutionary Economics ◽  
Smart Cities ◽  
Innovation Process ◽  
Sustainable City ◽  
Smart Services ◽  
Underlying Processes

Cities are becoming digital and are aiming to be sustainable. How they are combining the two is not always apparent from the outside. What we need is a look from inside. In recent years, cities have increasingly called themselves Smart City. This can mean different things, but generally includes a look towards new digital technologies and claim that a Smart City has various advantages for its citizens, roughly in line with the demands of sustainable development. A city can be seen as smart in a narrow sense, technology wise, sustainable or smart and sustainable. Current city rankings, which often evaluate and classify cities in terms of the target dimensions “smart” and “sustainable”, certify that some cities are both. In its most established academic definitions, the Smart City also serves both to improve the quality of life of its citizens and to promote sustainable development. Some cities have obviously managed to combine the two. The question that arises is as follows: What are the underlying processes towards a sustainable Smart City and are cities really using smart tools to make themselves sustainable in the sense of the 2015 United Nations Sustainability Goal 11? This question is to be answered by a method that has not yet been applied in research on cities and smart cities: the innovation biography. Based on evolutionary economics, the innovation biography approaches the process towards a Smart City as an innovation process. It will highlight which actors are involved, how knowledge is shared among them, what form citizen participation processes take and whether the use of digital and smart services within a Smart City leads to a more sustainable city. Such a process-oriented method should show, among other things, to what extent and when sustainability-relevant motives play a role and which actors and citizens are involved in the process at all.

scholarly journals Improving Sustainability of Smart Cities through Visualization Techniques for Big Data from IoT Devices

2020 ◽  
Vol 12 (14) ◽  
pp. 5595 ◽  
Author(s):  
Ana Lavalle ◽  
Miguel A. Teruel ◽  
Alejandro Maté ◽  
Juan Trujillo
Keyword(s):  
Big Data ◽  
Smart City ◽  
Smart Cities ◽  
Fire Department ◽  
Heterogeneous Data ◽  
Fire Extinguishing ◽  
Heterogeneous Data Sources ◽  
Iot Devices ◽  
Visualization Techniques ◽  
The Impact

Fostering sustainability is paramount for Smart Cities development. Lately, Smart Cities are benefiting from the rising of Big Data coming from IoT devices, leading to improvements on monitoring and prevention. However, monitoring and prevention processes require visualization techniques as a key component. Indeed, in order to prevent possible hazards (such as fires, leaks, etc.) and optimize their resources, Smart Cities require adequate visualizations that provide insights to decision makers. Nevertheless, visualization of Big Data has always been a challenging issue, especially when such data are originated in real-time. This problem becomes even bigger in Smart City environments since we have to deal with many different groups of users and multiple heterogeneous data sources. Without a proper visualization methodology, complex dashboards including data from different nature are difficult to understand. In order to tackle this issue, we propose a methodology based on visualization techniques for Big Data, aimed at improving the evidence-gathering process by assisting users in the decision making in the context of Smart Cities. Moreover, in order to assess the impact of our proposal, a case study based on service calls for a fire department is presented. In this sense, our findings will be applied to data coming from citizen calls. Thus, the results of this work will contribute to the optimization of resources, namely fire extinguishing battalions, helping to improve their effectiveness and, as a result, the sustainability of a Smart City, operating better with less resources. Finally, in order to evaluate the impact of our proposal, we have performed an experiment, with non-expert users in data visualization.

Practice Report “Smart Disaster Management” — Combining Smart City Data and Citizen Participation to Increase Disaster Resilience

i-com ◽  
2021 ◽  
Vol 20 (2) ◽  
pp. 177-193
Author(s):  
Daniel Wessel ◽  
Julien Holtz ◽  
Florian König
Keyword(s):  
Citizen Participation ◽  
Smart City ◽  
Development Process ◽  
Smart Cities ◽  
Government Support ◽  
Sensor Data ◽  
Specific Information ◽  
Mutual Support ◽  
The Everyday

Abstract Smart cities have a huge potential to increase the everyday efficiency of cities, but also to increase preparation and resilience in case of natural disasters. Especially for disasters which are somewhat predicable like floods, sensor data can be used to provide citizens with up-to-date, personalized and location-specific information (street or even house level resolution). This information allows citizens to better prepare to avert water damage to their property, reduce the needed government support, and — by connecting citizens locally — improve mutual support among neighbors. But how can a smart city application be designed that is both usable and able to function during disaster conditions? Which smart city information can be used? How can the likelihood of mutual, local support be increased? In this practice report, we present the human-centered development process of an app to use Smart City data to better prepare citizens for floods and improve their mutual support during disasters as a case study to answer these questions.

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.

The Smart City and Its Citizens

2019 ◽  
pp. 1407-1427
Author(s):  
Carlo Francesco Capra
Keyword(s):  
Urban Development ◽  
Citizen Participation ◽  
Smart City ◽  
Smart Cities ◽  
Modern Technology ◽  
Factors Influencing ◽  
Complex Settings ◽  
Multiple Actors

Smart cities are associated almost exclusively with modern technology and infrastructure. However, smart cities have the possibility to enhance the involvement and contribution of citizens to urban development. This work explores the role of governance as one of the factors influencing the participation of citizens in smart cities projects. Governance characteristics play a major role in explaining different typologies of citizen participation. Through a focus on Amsterdam Smart City program as a specific case study, this research examines the characteristics of governance that are present in the overall program and within a selected sample of projects, and how they relate to different typologies of citizen participation. The analysis and comprehension of governance characteristics plays a crucial role both for a better understanding and management of citizen participation, especially in complex settings where multiple actors are interacting.

Smart and Connected Cities Through Technologies

2019 ◽  
pp. 1-24 ◽  
Author(s):  
Vrushali Gajanan Kadam ◽  
Sharvari Chandrashekhar Tamane ◽  
Vijender Kumar Solanki
Keyword(s):  
Big Data ◽  
Traffic Congestion ◽  
Smart City ◽  
Smart Cities ◽  
Big Data Analytics ◽  
Crowd Sensing ◽  
The World ◽  
Important Challenge ◽  
Mobile Crowd

The world is growing and energy conservation is a very important challenge for the engineering domain. The emergence of smart cities is one possible solution for the same, as it claims that energy and resources are saved in the smart city infrastructure. This chapter is divided into five sections. Section 1 gives the past, present, and future of the living style. It gives the representation from rural, urban, to smart city. Section 2 gives the explanations of four pillars of big data, and through grid, a big data analysis is presented in the chapter. Section 3 started with the case study on smart grid. It comprises traffic congestion and their prospective solution through big data analytics. Section 4 starts from the mobile crowd sensing. It discusses a good elaboration on crowd sensing whereas Section 5 discusses the smart city approach. Important issues like lighting, parking, and traffic were taken into consideration.

Citizen Participation in Smart Sustainable Cities

2022 ◽  
pp. 967-987
Author(s):  
Ezgi Seçkiner Bingöl
Keyword(s):  
Gender Equality ◽  
Citizen Participation ◽  
Smart City ◽  
Good Governance ◽  
Smart Cities ◽  
Sustainable Cities ◽  
Sustainable City ◽  
Participation Mechanisms ◽  
The Relationship ◽  
City Literature

Citizen participation and sustainability are two main concepts used in the definitions in the smart city literature. Citizen participation is often used within the context of improving good governance in smart cities. Its relationship with sustainability is seldomly discussed. This study analyses the relationship between the concepts of smart city, smart sustainable city, and citizen participation, and discusses how citizen participation is shaped in smart sustainable cities. In light of this analysis, seven types of citizen participation mechanisms are studied. The findings of the study reveal that sustainability in smart cities is only considered within the framework of environmental matters, while citizen participation is only considered as a mechanism aimed at supporting good governance. The study recommends using these participation mechanisms to highlight other aspects of sustainability such as securing comprehensiveness, alleviating poverty, promoting gender equality and to focus on other aspects of citizen participation such as real participation and democratic effectiveness.

Active Governance and Smart Citizenship

2022 ◽  
pp. 290-296
Author(s):  
Panagiota Konstantinou ◽  
Georgios Stathakis ◽  
Maria Georgia Nomikou ◽  
Athina Mountzouri ◽  
Maria Stamataki
Keyword(s):  
Artificial Intelligence ◽  
Human Behavior ◽  
Citizen Participation ◽  
Smart City ◽  
Personal Autonomy ◽  
Smart Cities ◽  
Active Part ◽  
Urban Living ◽  
Liberal Citizenship

Cities are increasingly dependent on networks, sensors, and microcontrollers. Artificial intelligence has managed to mimic human behavior, and in a few years, many jobs may be replaced by computers or machines. Today, smart cities are evolving in all countries from the poorest to the most economically viable, and there are many smart city applications that rely on observation and participation of the citizens. Active citizens are interested in the benefits of their city, and they are involved in improving and promoting urban living. All levels of smart citizen participation are associated with liberal citizenship and personal autonomy and the choice of individuals to perform specific roles and take responsibility for their actions. The states in turn provide liberal forms of government. Smart cities need “smart people” who can take an active part in both governance and city reform. This kind of citizen participation is more than just a ritual participation in government.

Cloud-Based Big Data Analysis Tools and Techniques Towards Sustainable Smart City Services

2021 ◽  
pp. 63-90
Author(s):  
Suresh P. ◽  
Keerthika P. ◽  
Sathiyamoorthi V. ◽  
Logeswaran K. ◽  
Manjula Devi R. ◽  
...  
Keyword(s):  
Big Data ◽  
Real Time ◽  
Smart City ◽  
Traffic Management ◽  
Smart Cities ◽  
Big Data Analytics ◽  
Streaming Data ◽  
City Development ◽  
Time Data ◽  
Public And Private

Cloud computing and big data analytics are the key parts of smart city development that can create reliable, secure, healthier, more informed communities while producing tremendous data to the public and private sectors. Since the various sectors of smart cities generate enormous amounts of streaming data from sensors and other devices, storing and analyzing this huge real-time data typically entail significant computing capacity. Most smart city solutions use a combination of core technologies such as computing, storage, databases, data warehouses, and advanced technologies such as analytics on big data, real-time streaming data, artificial intelligence, machine learning, and the internet of things (IoT). This chapter presents a theoretical and experimental perspective on the smart city services such as smart healthcare, water management, education, transportation and traffic management, and smart grid that are offered using big data management and cloud-based analytics services.

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