scholarly journals Key Factors in Big Data Implementation for Smart City: A Systematic Literature Review

2021 ◽  
Vol 006 (01) ◽  
pp. 16-22
Author(s):  
Yulida Safitri
Keyword(s):  
Big Data ◽  
Smart City ◽  
Smart Cities ◽  
Research Paper ◽  
City Government ◽  
Data Availability ◽  
Management Support ◽  
Key Factors ◽  
Privacy And Security ◽  
Technological Infrastructure

Many governments implement smart city concept in their daily operation. As the concept continues to develop, smart cities all over the world are now starting to utilize big data. Learning from their private counterparts that already ahead in harnessing the potential benefits of big data implementation, smart cities begin the transformation of implementing big data. The purpose of this research paper is to: 1) Review the possible opportunities offered by big data implementation in smart city, 2) Review the challenges that smart city need to solve in utilizing big data, 3) Develop a framework that addresses the key factors in successful big data implementation in smart city. This research paper produces a framework that addresses several key factors that smart city government should consider ensuring success when implementing big data based on the proposed model indicators in private sectors. This framework consists of key factors of big data implementation for smart city which are top management support, organizational change, privacy and security, data availability and quality, cost, skillset and knowledge, big data policy, and technological infrastructure. It is important to have an understanding that these key factors correlate each other and are equally important.

scholarly journals PROTECTION OF PRIVACY AND PERSONAL DATA IN THE BIG DATA ENVIRONMENT OF SMART CITIES

2021 ◽  
Vol XLVI-4/W5-2021 ◽  
pp. 181-186
Author(s):  
A. Denker
Keyword(s):  
Big Data ◽  
Smart City ◽  
Personal Information ◽  
Smart Cities ◽  
Personal Data ◽  
Privacy And Security ◽  
Personal Data Protection ◽  
Security Issues ◽  
Data Environment ◽  
Bifocal Lenses

Abstract. The project of smart cities has emerged as a response to the challenges of twenty-first- century urbanization. Solutions to the fundamental conundrum of cities revolving around efficiency, convenience and security keep being sought by leveraging technology. Notwithstanding all the conveniences furnished by a smart city to all the citizens, privacy of a citizen is intertwined with the benefits of a smart city. The development processes which overlook privacy and security issues have left many of the smart city applications vulnerable to non-conventional security threats and susceptible to numerous privacy and personal data spillage risks. Among the challenges the smart city initiatives encounter, the emergence of the smartphone-big data-the cloud coalescence is perhaps the greatest, from the viewpoint of privacy and personal data protection. As our cities are getting digitalized, information comprising citizens' behavior, choices, and mobility, as well as their personal assets are shared over smartphone-big data-the cloud coalescences, thereby expanding cyber-threat surface and creating different security concerns. This coalescence refers to the practices of creating and analyzing vast sets of data, which comprise personal information. In this paper, the protection of privacy and personal data issues in the big data environment of smart cities are viewed through bifocal lenses, focusing on social and technical aspects. The protection of personal data and privacy in smart city enterprises is treated as a socio-technological operation where various actors and factors undertake different tasks. The article concludes by calling for novel developments, conceptual and practical changes both in technological and social realms.

Smart Ideas for Smart City Development

2021 ◽  
pp. 83-96
Author(s):  
Andrew Omambia
Keyword(s):  
Big Data ◽  
Natural Environment ◽  
Smart City ◽  
Smart Cities ◽  
Critical Factors ◽  
City Development ◽  
Key Factors ◽  
Integrative Framework ◽  
Road Map ◽  
The World

The concept of smart city is a burgeoning strategy that is fast becoming popular as a strategy that will be able to mitigate the problems emanating from the uncontrolled population growth and urbanization. Academicians have turned their attention to the smart city concept, but an in-depth understanding of the concept is still required. There is a dearth of information on the concept and hence the phenomenon is not well understood. This study, therefore, aims to fill the gap in literature regarding smart cities and propose a framework for grasping the concept further. Based on exploratory studies on the concept of smart cities, this chapter focusses on nine key factors that will form the framework for smart cities and the smart cities initiatives. These nine critical factors include the management, organization governance, technology, people, policy, economy, natural environment, built environment, and the implications of big data on smart cities. These factors provide the basis for the development of an integrative framework that can be employed to examine the manner in which governments around the world, including Kenya, are envisioning smart city initiatives. The framework provides the agendas and directions for smart approaches that can be implemented in cities and a road map for the attainment of smart cities.

scholarly journals Partnership and governance for smart cities

2020 ◽  
Vol 338 ◽  
pp. 43-53
Author(s):  
Catalin Vrabie
Keyword(s):  
Smart City ◽  
Smart Cities ◽  
Transition Process ◽  
Shared Vision ◽  
Social Enterprises ◽  
City Government ◽  
Privacy And Security ◽  
Cultural Shift ◽  
The Road ◽  
Success Stories

Many smart city publications talk of a need for new models of partnership working: public–private partnerships that create a shared vision for the smart city, bringing together leaders from city government, national government, health services, universities, business, social enterprises and the community sector. But as it is already known, crucial to the acceptance and success of smart cities is the involvement of citizens. Cities in which citizens take a central role are creating public–private– people partnerships. There’s no clear beginning or end to the process of becoming smart: the road to smart cities is a transition process that can take 10, 15 or even 20 years. Today’s decisions on city infrastructures and services will have consequences for the future generations who live in the city. There needs to be a huge cultural shift away from working in silos and towards integration across organizations, cities and countries. Smart city partnerships need to bring people together but they also need to be a vehicle that commissions and manages smart infrastructure and technology, dealing with issues such as finance, privacy and security. This paper will discuss about this issue providing examples of success stories found in Europe and across the world.

scholarly journals Analisis Big Data untuk Kota Aman

2019 ◽  
Vol 2 (3) ◽  
pp. 203-217
Author(s):  
Setiyono
Keyword(s):  
Big Data ◽  
Smart City ◽  
Prediction Models ◽  
Smart Cities ◽  
City Government ◽  
Average Score ◽  
Maturity Level ◽  
Big City ◽  
Integrative Level ◽  
The City

Abstract—Smart solutions are needed by the city government to overcome various city problems. One solution is smart city. To realize smart city, one of the main challenges is the solution to overcome the city's security problems. Currently cities in Indonesia do not yet know the level of security of their cities. The level of city security can be obtained by surveying various cities. But surveys require personnel, time and cost that is not small. In this study the authors propose a method by designing a model to determine the level of security of cities in Indonesia by utilizing big data through the prediction of sentiment analysis of people's perceptions of city security on Twitter. This research was conducted in 25 cities in Indonesia which are divided into 8 big cities, 9 medium cities and 8 small cities. The results of the prediction models designed in this study are generally not much different from the results of the 2019 RKCI (Indonesia Smart Cities Rating) survey in the field of security and disaster. The results of this study found that 4 cities with a maturity level of security are at the Integrative level (score 60 to 79 in GSCM Maturity Level), namely Tangerang, Kediri, Parepare and Probolinggo, while the other 21 cities are at the Scattered level (score 40 to 59). The average score for the big city category is 55.41, while the middle city score is 55.48 and the small city is 53.70. The results of performance measurement of this prediction model are for an accuracy value of 80.10% while a precision value of 81.10% and a recall value of 82.62%.

YOUTH EXPECTATIONS OF SMART CITY LIVING: AN IMPORTANCE- PERFORMANCE ANALYSIS OF YOUNG RESIDENTS’ PERSPECTIVES OF CITY GOVERNMENT

2017 ◽  
Vol 14 (1) ◽  
pp. 118-128
Author(s):  
Jason Cohen ◽  
Judy Backhouse ◽  
Omar Ally
Keyword(s):  
Performance Analysis ◽  
Young People ◽  
Smart City ◽  
Smart Cities ◽  
City Government ◽  
Diagnostic Tools ◽  
City Management ◽  
Bottom Up ◽  
Starting Point ◽  
The City

Young people are important to cities, bringing skills and energy and contributing to economic activity. New technologies have led to the idea of a smart city as a framework for city management. Smart cities are developed from the top-down through government programmes, but also from the bottom-up by residents as technologies facilitate participation in developing new forms of city services. Young people are uniquely positioned to contribute to bottom-up smart city projects. Few diagnostic tools exist to guide city authorities on how to prioritise city service provision. A starting point is to understand how the youth value city services. This study surveys young people in Braamfontein, Johannesburg, and conducts an importance-performance analysis to identify which city services are well regarded and where the city should focus efforts and resources. The results show that Smart city initiatives that would most increase the satisfaction of youths in Braamfontein  include wireless connectivity, tools to track public transport  and  information  on city events. These  results  identify  city services that are valued by young people, highlighting services that young people could participate in providing. The importance-performance analysis can assist the city to direct effort and scarce resources effectively.

scholarly journals Disaster Management in Smart Cities

Smart Cities ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 819-839
Author(s):  
Luís B. Elvas ◽  
Bruno Miguel Mataloto ◽  
Ana Lúcia Martins ◽  
João C. Ferreira
Keyword(s):  
Disaster Management ◽  
Smart City ◽  
Smart Cities ◽  
Practical Implication ◽  
Data Availability ◽  
Critical Infrastructures ◽  
Cascading Effects ◽  
Data Driven Approach ◽  
New Research ◽  
The City

The smart city concept, in which data from different systems are available, contains a multitude of critical infrastructures. This data availability opens new research opportunities in the study of the interdependency between those critical infrastructures and cascading effects solutions and focuses on the smart city as a network of critical infrastructures. This paper proposes an integrated resilience system linking interconnected critical infrastructures in a smart city to improve disaster resilience. A data-driven approach is considered, using artificial intelligence and methods to minimize cascading effects and the destruction of failing critical infrastructures and their components (at a city level). The proposed approach allows rapid recovery of infrastructures’ service performance levels after disasters while keeping the coverage of the assessment of risks, prevention, detection, response, and mitigation of consequences. The proposed approach has the originality and the practical implication of providing a decision support system that handles the infrastructures that will support the city disaster management system—make the city prepare, adapt, absorb, respond, and recover from disasters by taking advantage of the interconnections between its various critical infrastructures to increase the overall resilience capacity. The city of Lisbon (Portugal) is used as a case to show the practical application of the approach.

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.

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 Explora: Interactive Querying of Multidimensional Data in the Context of Smart Cities

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2737
Author(s):  
Leandro Ordonez-Ante ◽  
Gregory Van Seghbroeck ◽  
Tim Wauters ◽  
Bruno Volckaert ◽  
Filip De Turck
Keyword(s):  
Smart City ◽  
Smart Cities ◽  
Temporal Trends ◽  
Multidimensional Data ◽  
Data Sets ◽  
Distributed Data ◽  
Key Factors ◽  
Distributed Data Processing ◽  
Spatial And Temporal Trends ◽  
Query Latency

Citizen engagement is one of the key factors for smart city initiatives to remain sustainable over time. This in turn entails providing citizens and other relevant stakeholders with the latest data and tools that enable them to derive insights that add value to their day-to-day life. The massive volume of data being constantly produced in these smart city environments makes satisfying this requirement particularly challenging. This paper introduces Explora, a generic framework for serving interactive low-latency requests, typical of visual exploratory applications on spatiotemporal data, which leverages the stream processing for deriving—on ingestion time—synopsis data structures that concisely capture the spatial and temporal trends and dynamics of the sensed variables and serve as compacted data sets to provide fast (approximate) answers to visual queries on smart city data. The experimental evaluation conducted on proof-of-concept implementations of Explora, based on traditional database and distributed data processing setups, accounts for a decrease of up to 2 orders of magnitude in query latency compared to queries running on the base raw data at the expense of less than 10% query accuracy and 30% data footprint. The implementation of the framework on real smart city data along with the obtained experimental results prove the feasibility of the proposed approach.

scholarly journals IoT Based Smart Garage Vehicle Washing Water Nestor

2020 ◽  
Vol 8 (5) ◽  
pp. 3521-3525
Keyword(s):  
Water Pollution ◽  
Cloud Computing ◽  
Big Data ◽  
Smart Cities ◽  
Human Life ◽  
Research Paper ◽  
Proper Treatment ◽  
Computing Services ◽  
Cloud Computing Services ◽  
The Government

Water is critical part of the human life. In most of the developing nation, water pollution is one of the bigger mess. These issues can be handled strictly by the Government organization, by implementing tougher action rules to the industries, were the water are released without any proper treatment. Where each industries (or) smart cities, should take up self-initiative responsibility for proper treatment of the polluted out flow water. In our research paper, we are not focusing on the wider area of the water pollution; our focus is limited within the smart cities vehicle washing garages. In very smart cities, were a regular multiple vehicles washing is done in the garage, our research paper will focus on the out flow of the populated water from these vehicle washing garages. Our design and implantation process is simpler and straightforward approach. Were we will monitor of the water quality; and how much level of the water is populated, and it requires at what level of the treatment. These process can be easily automated using the multiple IOT (internet of things) based sensors, the data can be streamed into the Big Data lake (or) it can be directly pushed into the cloud computing services for generating the real time graphs and analyses report instantly. These data collected in the Big Data lake (or) cloud computing services, can be used for detail analyses for research purpose. We will incorporate the block chain concept to keep track of the smart garage location address and the detail information of the number of garage in the smart cities details in the form of the blocks.

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