scholarly journals Corrigendum on: Big Data and development of smart city: System architecture and practical public safety example [Serb. Jour. of Elect. Eng., Vol. 17, No. 3, Oct. 2020, pp. 337 - 355]

2021 ◽  
Vol 18 (1) ◽  
pp. 137-137
Author(s):  
E Editorial
Keyword(s):  
Big Data ◽  
System Architecture ◽  
Smart City ◽  
Public Safety ◽  
The Third ◽  
City System ◽  
Font Color

The authors of the paper entitled "Big Data and Development of Smart City: System Architecture and Practical Public Safety Example", Mirko Simic, Miroslav Peric, Ilija Popadic, Dragana Peric, Milos Pavlovic, Miljan Vucetic and Milos S. Stankovic, informed the Editor about the error in the position of the author Miljan Vucetic, who should be at the third position. The authors have requested for this error to be corrected. Therefore, the journal is publishing this Corrigendum. The authors of this article should be listed as follows: Mirko Simic, Miroslav Peric, Miljan Vucetic, Ilija Popadic, Dragana Peric, Milos Pavlovic, Milos Stankovic. <br><br><font color="red"><b> Link to the corrected article <u><a href="http://dx.doi.org/10.2298/SJEE2003337S">10.2298/SJEE2003337S</a></b></u>

scholarly journals Exploring the influence of big data on city transport operations: a Markovian approach

2017 ◽  
Vol 37 (1) ◽  
pp. 75-104 ◽  
Author(s):  
Rashid Mehmood ◽  
Royston Meriton ◽  
Gary Graham ◽  
Patrick Hennelly ◽  
Mukesh Kumar
Keyword(s):  
Big Data ◽  
Markov Model ◽  
Absorptive Capacity ◽  
Smart City ◽  
Smart Cities ◽  
Theoretical Framework ◽  
Social Implications ◽  
Content Type ◽  
Depth Analysis ◽  
City System

Purpose The purpose of this paper is to advance knowledge of the transformative potential of big data on city-based transport models. The central question guiding this paper is: how could big data transform smart city transport operations? In answering this question the authors present initial results from a Markov study. However the authors also suggest caution in the transformation potential of big data and highlight the risks of city and organizational adoption. A theoretical framework is presented together with an associated scenario which guides the development of a Markov model. Design/methodology/approach A model with several scenarios is developed to explore a theoretical framework focussed on matching the transport demands (of people and freight mobility) with city transport service provision using big data. This model was designed to illustrate how sharing transport load (and capacity) in a smart city can improve efficiencies in meeting demand for city services. Findings This modelling study is an initial preliminary stage of the investigation in how big data could be used to redefine and enable new operational models. The study provides new understanding about load sharing and optimization in a smart city context. Basically the authors demonstrate how big data could be used to improve transport efficiency and lower externalities in a smart city. Further how improvement could take place by having a car free city environment, autonomous vehicles and shared resource capacity among providers. Research limitations/implications The research relied on a Markov model and the numerical solution of its steady state probabilities vector to illustrate the transformation of transport operations management (OM) in the future city context. More in depth analysis and more discrete modelling are clearly needed to assist in the implementation of big data initiatives and facilitate new innovations in OM. The work complements and extends that of Setia and Patel (2013), who theoretically link together information system design to operation absorptive capacity capabilities. Practical implications The study implies that transport operations would actually need to be re-organized so as to deal with lowering CO2 footprint. The logistic aspects could be seen as a move from individual firms optimizing their own transportation supply to a shared collaborative load and resourced system. Such ideas are radical changes driven by, or leading to more decentralized rather than having centralized transport solutions (Caplice, 2013). Social implications The growth of cities and urban areas in the twenty-first century has put more pressure on resources and conditions of urban life. This paper is an initial first step in building theory, knowledge and critical understanding of the social implications being posed by the growth in cities and the role that big data and smart cities could play in developing a resilient and sustainable transport city system. Originality/value Despite the importance of OM to big data implementation, for both practitioners and researchers, we have yet to see a systematic analysis of its implementation and its absorptive capacity contribution to building capabilities, at either city system or organizational levels. As such the Markov model makes a preliminary contribution to the literature integrating big data capabilities with OM capabilities and the resulting improvements in system absorptive capacity.

scholarly journals Novosibirsk as a “Smart City”

2020 ◽  
Vol 20 (4) ◽  
pp. 46-60
Author(s):  
Elena A. Kostina
Keyword(s):  
Big Data ◽  
Smart City ◽  
Urban Population ◽  
The Internet ◽  
The Third ◽  
Skilled Workforce ◽  
The Creation ◽  
The Internet Of Things ◽  
Modern Technologies

In recent years, we have witnessed a rapid and profound growth of urban population. The challenge to improve the quality of the urban environment is becoming increasingly important. Competition among the cities for highly skilled workforce, companies, investors, and even international events is also growing. With the advancement in modern technologies, especially IT, the Internet of things and big data, the creation of a “smart city” seems to be an excellent opportunity for the urban development. More and more cities are striving to follow this path, and Novosibirsk – the third largest city in Russia – is not an exception. This article analyzes the concept of a smart city, the advantages and barriers that impede the creation of a “smart city”, and considers the prospects of Novosibirsk as a “smart city”. The article suggests possible ways for Novosibirsk development as a “smart city”.

scholarly journals Big Data and development of smart city: System architecture and practical public safety example

2020 ◽  
Vol 17 (3) ◽  
pp. 337-355
Author(s):  
Mirko Simic ◽  
Miroslav Peric ◽  
Ilija Popadic ◽  
Dragana Peric ◽  
Milos Pavlovic ◽  
...  
Keyword(s):  
Big Data ◽  
Smart City ◽  
Public Safety ◽  
Imaging System ◽  
Distributed Processing ◽  
Smart Device ◽  
Business Environments ◽  
Processing Power ◽  
Private Data ◽  
Thermal Imagers

The concept of Smart City started its development path around two to three decades ago; it has been mainly influenced and driven by radical changes in technological, social and business environments. Big Data, Internet of Things and Networked Cyber-Physical Systems, together with the concepts of Cloud, Fog and Edge Computing, have tremendous impact on the development of Smart City, reforming its frame and tasks and redefining its requirements and challenges. We consider feasible architectures of the IT infrastructure and signal processing, taking into account aspects of Big Data, followed by summary of benefits and main challenges, like security of infrastructure and private data. As a practical example we present a public safety application of multi-sensor imaging system: a smart device with target detection subsystem based on artificial intelligence used for activation of target tracking. The experiments have been performed in the cities of Abu Dhabi and Belgrade, which have very different environment. The experiments have shown the effects of videostreaming compression on thermal imagers and the importance of distributed processing power that optimizes requirements for amount of transmitted data and delay.

A Smart City System Architecture based on City-level Data Exchange Platform

2015 ◽  
Vol 8 (4) ◽  
pp. 1-25 ◽  
Author(s):  
Jinfu Chen ◽  
Yuchi Guo ◽  
Chenfei Su ◽  
Jiamei Chen ◽  
Shen Chang
Keyword(s):  
System Architecture ◽  
Smart City ◽  
Data Exchange ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Regional Health ◽  
Data Exchange Platform ◽  
Level Data ◽  
Card System ◽  
City System

With the development of information technology and urban planning, there is a higher demand for the life quality of city people. In order to meet the demand for urban facilitation and intelligence, the research on smart city system has been widely discussed in recent years. However, existing researches mostly stay at the theoretical exploration stage, so a feasible and effective framework of smart city system which is suitable for Chinese national conditions is urgently demanded. In this paper, an implementation framework of smart city system is proposed based on city-level data exchange platform. To start with, three subsystems of smart city system are proposed and described, namely citizen-card system, intelligent transportation system, and urban regional health system. The citizen-card system is the foundation to realize smart city system, the intelligent transportation system is the core part of smart city system, and the urban regional health system is the crucial part of smart city system. Then a city-level data exchange platform and its algorithms are proposed, and the data exchange algorithms are also analyzed based on subscription and publishing mechanism. Finally, the proposed system architecture has been implemented and applied to Zhenjiang city, which is a city in Jiangsu province, China. The application performance of the proposed system architecture is also analyzed and discussed. The experimental results show that the proposed framework of smart city system is feasible and effective.

Issues in security and privacy of big data

2018 ◽  
Vol 7 (12) ◽  
pp. 1
Author(s):  
Shaveta Bhatia
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Approximate Method ◽  
Biomedical Research ◽  
Cyber Security ◽  
Data Science ◽  
Third Party ◽  
Security And Privacy ◽  
Security Threats ◽  
The Third

 The epoch of the big data presents many opportunities for the development in the range of data science, biomedical research cyber security, and cloud computing. Nowadays the big data gained popularity.  It also invites many provocations and upshot in the security and privacy of the big data. There are various type of threats, attacks such as leakage of data, the third party tries to access, viruses and vulnerability that stand against the security of the big data. This paper will discuss about the security threats and their approximate method in the field of biomedical research, cyber security and cloud computing.

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.

Sign in / Sign up

Export Citation Format

Share Document