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.

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.

On the application of Big Data in future large-scale intelligent Smart City installations

2014 ◽  
Vol 10 (2) ◽  
pp. 168-182 ◽  
Author(s):  
Sylva Girtelschmid ◽  
Matthias Steinbauer ◽  
Vikash Kumar ◽  
Anna Fensel ◽  
Gabriele Kotsis
Keyword(s):  
Big Data ◽  
Real World ◽  
Smart City ◽  
Large Scale ◽  
Smart Cities ◽  
Sensor Data ◽  
Data Streaming ◽  
Content Type ◽  
Semantic Models ◽  
Intelligent Filtering

Purpose – The purpose of this article is to propose and evaluate a novel system architecture for Smart City applications which uses ontology reasoning and a distributed stream processing framework on the cloud. In the domain of Smart City, often methodologies of semantic modeling and automated inference are applied. However, semantic models often face performance problems when applied in large scale. Design/methodology/approach – The problem domain is addressed by using methods from Big Data processing in combination with semantic models. The architecture is designed in a way that for the Smart City model still traditional semantic models and rule engines can be used. However, sensor data occurring at such Smart Cities are pre-processed by a Big Data streaming platform to lower the workload to be processed by the rule engine. Findings – By creating a real-world implementation of the proposed architecture and running simulations of Smart Cities of different sizes, on top of this implementation, the authors found that the combination of Big Data streaming platforms with semantic reasoning is a valid approach to the problem. Research limitations/implications – In this article, real-world sensor data from only two buildings were extrapolated for the simulations. Obviously, real-world scenarios will have a more complex set of sensor input values, which needs to be addressed in future work. Originality/value – The simulations show that merely using a streaming platform as a buffer for sensor input values already increases the sensor data throughput and that by applying intelligent filtering in the streaming platform, the actual number of rule executions can be limited to a minimum.

Content analysis of literature on big data in smart cities

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pulkit Tiwari ◽  
P. Vigneswara Ilavarasan ◽  
Sushil Punia
Keyword(s):  
Big Data ◽  
Content Analysis ◽  
Conceptual Framework ◽  
Bibliometric Analysis ◽  
Smart City ◽  
Industry 4.0 ◽  
Smart Cities ◽  
Analytical Techniques ◽  
Content Type ◽  
City Model

Purpose The purpose of this paper is to provide a systematic literature review on the technological aspects of smart cities and to give insights about current trends, sources of research, contributing authors and countries. It is required to understand technical concepts like information technology, big data analytics, Internet of Things and blockchain needed to implement smart city models successfully. Design/methodology/approach The data were collected from the Scopus database, and analysis techniques like bibliometric analysis, network analysis and content analysis were used to obtain research trends, publications growth, top contributing authors and nations in the domain of smart cities. Also, these analytical techniques identified various fields within the literature on smart cities and supported to design a conceptual framework for Industry 4.0 adoption in a smart city. Findings The bibliometric analysis shows that research publications have increased significantly over the last couple of years. It has found that developing countries like China is leading the research on smart cities. The network analytics and article classification identified six domains within the literature on smart cities. A conceptual framework for the smart city has proposed for the successful implementation of Industry 4.0 technologies. Originality/value This paper explores the role of Industry 4.0 technologies in smart cities. The bibliometric data on publications from the year 2013 to 2018 were used and investigated by using advanced analytical techniques. The paper reviewS key technical concepts for the successful execution of a smart city model. It also gives an idea about various technical considerations required for the implementation of the smart city model through a conceptual framework.

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.

Systematic literature review on the security challenges of blockchain in IoT-based smart cities

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhihao Yu ◽  
Liang Song ◽  
Linhua Jiang ◽  
Omid Khold Sharafi
Keyword(s):  
Literature Review ◽  
Smart City ◽  
Smart Cities ◽  
Distributed Storage ◽  
Resource Planning ◽  
Academic Community ◽  
Security And Privacy ◽  
Content Type ◽  
Security Issues ◽  
Security Challenges

Purpose Security is the most important issue in Internet of Things (IoT)-based smart cities and blockchain (BC). So, the present paper aims to detect and organize the literature regarding security in the IoT-based smart cities and BC context. It also proposes an agenda for future research. Therefore, the authors did a statistical review of security in IoT and BC in smart cities. The present investigation aims to determine the principal challenges and disturbances in IoT because of the BC adoption, the central BC applications in IoT-based smart cities and the BC future in IoT-based smart cities. Design/methodology/approach IoT) has a notable influence on modernizing and transforming the society and industry for knowledge digitizing. Therefore, it may be perceived and operated in real time. The IoT is undergoing exponential development in industry and investigation. Still, it contains some security and privacy susceptibilities. Naturally, the research community pays attention to the security and privacy of the IoT. Also, the academic community has put a significant focus on BC as a new security project. In the present paper, the significant mechanisms and investigations in BC ground have been checked out systematically because of the significance of security in the IoT and BC in smart cities. Electronic databases were used to search for keywords. Totally, based on different filters, 131 papers have been gained, and 17 related articles have been obtained and analyzed. The security mechanisms of BC in IoT-based smart cities have been ranked into three main categories as follows, smart health care, smart home and smart agriculture. Findings The findings showed that BC’s distinctive technical aspects might impressively find a solution for privacy and security problems encountering the IoT-based smart cities development. They also supply distributed storage, transparency, trust and other IoT support to form a valid, impressive and secure distributed IoT network and provide a beneficial guarantee for IoT-based smart city users’ security and privacy. Research limitations/implications The present investigation aims to be comprehensive, but some restrictions were also observed. Owing to the use of some filters for selecting the original papers, some complete works may be excluded. Besides, inspecting the total investigations on the security topic in BC and the IoT-based smart cities is infeasible. Albeit, the authors attempt to introduce a complete inspection of the security challenges in BC and the IoT-based smart cities. BC includes significant progress and innovation in the IoT-based smart cities’ security domain as new technology. Still, it contains some deficiencies as well. Investigators actively encounter the challenges and bring up persistent innovation and inspection of related technologies in the vision of the issues available in diverse application scenarios. Practical implications The use of BC technology in finding a solution for the security issues of the IoT-based smart cities is a research hotspot. There is numerable literature with data and theoretical support despite the suggestion of numerous relevant opinions. Therefore, this paper offers insights into how findings may guide practitioners and researchers in developing appropriate security systems dependent upon the features of IoT-based smart city systems and BC. This paper may also stimulate further investigation on the challenge of security in BC and IoT-based smart cities. The outcomes will be of great value for scholars and may supply sights into future investigation grounds in the present field. Originality/value As the authors state according to their knowledge, it is the first work using security challenges on BC and IoT-based smart cities. The literature review shows that few papers discuss how solving security issues in the IoT-based smart cities can benefit from the BC. The investigation suggests a literature review on the topic, recommending some thoughts on using security tools in the IoT-based smart cities. The present investigation helps organizations plan to integrate IoT and BC to detect the areas to focus. It also assists in better resource planning for the successful execution of smart technologies in their supply chains.

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.

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.

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.

Governmentality and performance for the smart city

2019 ◽  
Vol 33 (1) ◽  
pp. 204-232 ◽  
Author(s):  
Daniela Argento ◽  
Giuseppe Grossi ◽  
Aki Jääskeläinen ◽  
Stefania Servalli ◽  
Petri Suomala
Keyword(s):  
Performance Measurement ◽  
Smart City ◽  
Smart Cities ◽  
Research Question ◽  
Longitudinal Case Study ◽  
Content Type ◽  
Measurement Systems ◽  
Performance Measurement Systems

Purpose The purpose of this paper is to explore the role of performance measurement systems as technologies of government in the operationalisation of smart city programmes. It answers the research question: how do the development and use of performance measurement systems support smart cities in the achievement of their goals? Design/methodology/approach This paper presents a longitudinal case study that uses an interventionist approach to investigate the possibilities and limitations of the use of performance measurement systems as technologies of government in a smart city. Interpretations are theoretically informed by the Foucauldian governmentality framework (Foucault, 2009) and by public sector performance measurement literature. Findings The findings address the benefits and criticalities confronting a smart city that introduces new performance measurement systems as a technology of government. Such technologies become problematic tools when the city network is characterised by a fragmentation of inter-departmental processes, and when forms of resistance emerge due to a lack of process owners, horizontal accountability and cooperation among involved parties. Research limitations/implications This paper is based on a case study of a single smart city, and outlines the need for both comparative and multidisciplinary analyses in order to analyse the causes and effects of smart city challenges. Originality/value This paper offers a critical understanding of the role of accounting in the smart city. The ineffectiveness of performance measurement systems is related to the multiple roles of such technologies of government, which may lead to a temporary paralysis in the achievement of smart city goals and programmes.

ICT and sustainability in smart cities management

2016 ◽  
Vol 29 (2) ◽  
pp. 132-147 ◽  
Author(s):  
Francesco Bifulco ◽  
Marco Tregua ◽  
Cristina Caterina Amitrano ◽  
Anna D'Auria
Keyword(s):  
Smart City ◽  
City Planning ◽  
New Technologies ◽  
Smart Cities ◽  
Research Report ◽  
City Managers ◽  
Content Type ◽  
New Research ◽  
Local Agencies

Purpose – Contemporary debate is increasingly focused on ICT and sustainability, especially in relation to the modern configuration of urban and metropolitan areas in the so-called smartization process. The purpose of this paper is to observe the connections between smart city features as conceptualized in the framework proposed by Giffinger et al. (2007) and new technologies as tools, and sustainability as the goal. Design/methodology/approach – The connections are identified through a content analysis performed using NVivo on official reports issued by organizations, known as industry players within smart city projects, listed in the Navigant Research Report 2013. Findings – The results frame ICT and sustainability as “across-the-board elements” because they connect with all of the services provided to communities in a smart city and play a key role in smart city planning. Specifically, sustainability and ICT can be seen as tools to enable the smartization process. Research limitations/implications – An all-in-one perspective emerges by embedding sustainability and ICT in smart interventions; further research could be conduct through direct interviews to city managers and industry players in order to understand their attitude towards the development of smart city projects. Practical implications – Potential approaches emerging from this research are useful to city managers or large corporations partnering with local agencies in order to increase the opportunities for the long-term success of smart projects. Originality/value – The results of this paper delineate a new research path looking at the development of new models that integrate drivers, ICT, and sustainability in an all-in-one perspective and new indicators for the evaluation of the interventions.

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