scholarly journals Fog Computing for Smart Cities’ Big Data Management and Analytics: A Review

2020 ◽  
Vol 12 (11) ◽  
pp. 190
Author(s):  
Elarbi Badidi ◽  
Zineb Mahrez ◽  
Essaid Sabir
Keyword(s):  
Big Data ◽  
Public Space ◽  
Data Storage ◽  
Smart City ◽  
Urban Areas ◽  
Smart Cities ◽  
Fog Computing ◽  
Space Management ◽  
Network Bandwidth ◽  
Edge And Fog Computing

Demographic growth in urban areas means that modern cities face challenges in ensuring a steady supply of water and electricity, smart transport, livable space, better health services, and citizens’ safety. Advances in sensing, communication, and digital technologies promise to mitigate these challenges. Hence, many smart cities have taken a new step in moving away from internal information technology (IT) infrastructure to utility-supplied IT delivered over the Internet. The benefit of this move is to manage the vast amounts of data generated by the various city systems, including water and electricity systems, the waste management system, transportation system, public space management systems, health and education systems, and many more. Furthermore, many smart city applications are time-sensitive and need to quickly analyze data to react promptly to the various events occurring in a city. The new and emerging paradigms of edge and fog computing promise to address big data storage and analysis in the field of smart cities. Here, we review existing service delivery models in smart cities and present our perspective on adopting these two emerging paradigms. We specifically describe the design of a fog-based data pipeline to address the issues of latency and network bandwidth required by time-sensitive smart city applications.

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 Big Data in Smart City: Management Challenges

2021 ◽  
Vol 11 (10) ◽  
pp. 4557
Author(s):  
Mladen Amović ◽  
Miro Govedarica ◽  
Aleksandra Radulović ◽  
Ivana Janković
Keyword(s):  
Big Data ◽  
Smart City ◽  
Urban Areas ◽  
Management System ◽  
Smart Cities ◽  
Open Data ◽  
Apache Spark ◽  
City Management ◽  
Real Time System ◽  
Data Framework

Smart cities use digital technologies such as cloud computing, Internet of Things, or open data in order to overcome limitations of traditional representation and exchange of geospatial data. This concept ensures a significant increase in the use of data to establish new services that contribute to better sustainable development and monitoring of all phenomena that occur in urban areas. The use of the modern geoinformation technologies, such as sensors for collecting different geospatial and related data, requires adequate storage options for further data analysis. In this paper, we suggest the biG dAta sMart cIty maNagEment SyStem (GAMINESS) that is based on the Apache Spark big data framework. The model of the GAMINESS management system is based on the principles of the big data modeling, which differs greatly from standard databases. This approach provides the ability to store and manage huge amounts of structured, semi-structured, and unstructured data in real time. System performance is increasing to a higher level by using the process parallelization explained through the five V principles of the big data paradigm. The existing solutions based on the five V principles are focused only on the data visualization, not the data themselves. Such solutions are often limited by different storage mechanisms and by the ability to perform complex analyses on large amounts of data with expected performance. The GAMINESS management system overcomes these disadvantages by conversion of smart city data to a big data structure without limitations related to data formats or use standards. The suggested model contains two components: a geospatial component and a sensor component that are based on the CityGML and the SensorThings standards. The developed model has the ability to exchange data regardless of the used standard or the data format into proposed Apache Spark data framework schema. The verification of the proposed model is done within the case study for the part of the city of Novi Sad.

scholarly journals Concept of implementing Big data in smart city: Applications, Services, Data Security in accordance with Internet of Things and AI

2019 ◽  
Vol 8 (3) ◽  
pp. 6819-6825
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
San Francisco ◽  
Smart City ◽  
Urban Areas ◽  
Smart Cities ◽  
Point Of View ◽  
Data Sets ◽  
Cloud Applications ◽  
The Internet Of Things

Smart cities are the current buzz phrase between infrastructure developments. With a gradually increasing inflow on populations into cities then a continuously thriving necessity to better deal with resources, countless cities kind of San Francisco, united states, Singapore, Portugal, England is experimenting together with upcoming state-of-the-art technologies after fulfill their cities smarter. Among these current trending technologies is the Internet of Things (IoT), Big Data and Artificial Intelligence (AI) which has revolutionized the way we analyze patterns yet traits between human behaviors. With Big Data, current fragmented and remoted data sets do stand well-acquainted beside an overarching point of view in accordance with provide high quality solutions in accordance with frequent issues up to expectation have an effect on rapidly growing cities today. Here are 5 ways within which Big Data could show fundamental in smart cities about the future. A lot of governments are thinking about adopting the smart city thought between theirs urban areas at that point executing impressive records services up to expectation assist smart city components in accordance with attain the required stage concerning supportability and improve the living norms. Smart cities take advantage of more than one technology in conformity with get better the concert about healthiness, transportation, power, education, and cloud applications lead after greater stages about remedy about their citizens. In addition, it attempts in accordance with pick out the necessities as assist the implementation on substantial data purposes for smart city services. The criticism displays as numerous possibilities are accessible because of making use of big data in smart cities; conversely, so are nevertheless various concerns and disputes in conformity with stay addressed to attain higher utilization about this technology.

scholarly journals Ingenious Techniques for Creation of Smart Cities by Big Data Technology & Urban Modelling Simulation by Matsim

2019 ◽  
Vol 8 (2) ◽  
pp. 1922-1927
Keyword(s):  
Big Data ◽  
Smart City ◽  
Urban Areas ◽  
Large Scale ◽  
Smart Cities ◽  
Distributed Data ◽  
Spatially Distributed ◽  
Urban Modelling ◽  
Different Sources ◽  
Big Data Technology

Ingenious Techniques for creation of Smart Cities by Big Data Technology & Urban modeling simulation by MATSimas the smart cities are on nascent stage in India. The extension of huge information and the advancement of Internet of Things (IoT) innovations have assumed a significant job in the practicality of keen city activities. Enormous information offer the potential for urban areas to get significant bits of knowledge from a lot of information gathered through different sources, and the IoT permits the joining of sensors, radiofrequency recognizable proof, and Bluetooth in reality condition utilizing exceedingly organized administrations. Thus the job of urban reenactment models and their perception are utilized to help territorial arranging offices assess elective transportation ventures, land use guidelines, and natural insurance arrangements. Typical urban simulations provide spatially distributed data about number of inhabitants, land prices, traffic, and other variables for ex- MATSim is an activity-based transport simulation framework designed to simulate large scale scenarios. Such technologies which have been developed in the past few years have proven to be very effective in smart cities of various countries. This project is an attempt to study the feasibility of such modified system, by understanding the implementation of such technologies to improve the existing smart cities and those which are about to become one. This is done by proposing an idea that is by implementing a big data server in the proposed smart city, the data will be collected through smart sensors which will then be sent to server and the mined data will be converted to simplified data for planners, engineers etc. in order to make a economic, self-sustainable & fully automated smart city

M2FBalancer: A mist-assisted fog computing-based load balancing strategy for smart cities

2021 ◽  
pp. 1-15
Author(s):  
Subhranshu Sekhar Tripathy ◽  
Diptendu Sinha Roy ◽  
Rabindra K. Barik
Keyword(s):  
Load Balancing ◽  
Resource Utilization ◽  
Smart City ◽  
Load Transfer ◽  
Smart Cities ◽  
Fog Computing ◽  
Round Robin ◽  
Healthcare Management ◽  
Optimization Strategy ◽  
Allocation Method

Nowadays, cities are intended to change to a smart city. According to recent studies, the use of data from contributors and physical objects in many cities play a key element in the transformation towards a smart city. The ‘smart city’ standard is characterized by omnipresent computing resources for the observing and critical control of such city’s framework, healthcare management, environment, transportation, and utilities. Mist computing is considered a computing prototype that performs IoT applications at the edge of the network. To maintain the Quality of Service (QoS), it is impressive to employ context-aware computing as well as fog computing simultaneously. In this article, the author implements an optimization strategy applying a dynamic resource allocation method based upon genetic algorithm and reinforcement learning in combination with a load balancing procedure. The proposed model comprises four layers i.e. IoT layer, Mist layer, Fog layer, and Cloud layer. Authors have proposed a load balancing technique called M2F balancer which regulates the traffic in the network incessantly, accumulates the information about each server load, transfer the incoming query, and disseminate them among accessible servers equally using dynamic resources allocation method. To validate the efficacy of the proposed algorithm makespan, resource utilization, and the degree of imbalance (DOI) are considered as the scheduling parameter. The proposed method is being compared with the Least count, Round Robin, and Weighted Round Robin. In the end, the results demonstrate that the solutions enhance QoS in the mist assisted cloud environment concerning maximization resource utilization and minimizing the makespan. Therefore, M2FBalancer is an effective method to utilize the resources efficiently by ensuring uninterrupted service. Consequently, it improves performance even at peak times.

scholarly journals Challenges and Barriers for Net‐Zero/Positive Energy Buildings and Districts—Empirical Evidence from the Smart City Project SPARCS

Buildings ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 78
Author(s):  
Daria Uspenskaia ◽  
Karl Specht ◽  
Hendrik Kondziella ◽  
Thomas Bruckner
Keyword(s):  
Smart City ◽  
Urban Areas ◽  
Smart Cities ◽  
Scale Up ◽  
Practical Experience ◽  
Positive Energy ◽  
Low Carbon ◽  
Net Zero ◽  
Multidimensional Representation

Without decarbonizing cities energy and climate objectives cannot be achieved as cities account for approximately two thirds of energy consumption and emissions. This goal of decarbonizing cities has to be facilitated by promoting net-zero/positive energy buildings and districts and replicating them, driving cities towards sustainability goals. Many projects in smart cities demonstrate novel and groundbreaking low-carbon solutions in demonstration and lighthouse projects. However, as the historical, geographic, political, social and economic context of urban areas vary greatly, it is not always easy to repeat the solution in another city or even district. It is therefore important to look for the opportunities to scale up or repeat successful pilots. The purpose of this paper is to explore common trends in technologies and replication strategies for positive energy buildings or districts in smart city projects, based on the practical experience from a case study in Leipzig—one of the lighthouse cities in the project SPARCS. One of the key findings the paper has proven is the necessity of a profound replication modelling to deepen the understanding of upscaling processes. Three models analyzed in this article are able to provide a multidimensional representation of the solution to be replicated.

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.

scholarly journals Smart cities IOT & Digital network connectivity devices: Optimization on business in Africa

2021 ◽  
pp. 064-071
Author(s):  
Makeri Yakubu Ajiji ◽  
Xi’an Jiaotong Victor Chang ◽  
Targio Hashem Ibrahim Abaker ◽  
Uzorka Afam ◽  
T Cirella Giuseppe
Keyword(s):  
Internet Of Things ◽  
Urban Communities ◽  
Information And Communication Technologies ◽  
Smart City ◽  
Urban Areas ◽  
Smart Cities ◽  
The Internet ◽  
City Development ◽  
Short Article ◽  
The Internet Of Things

Today the world is becoming connected. The number of devices that are connected are increasing day by day. Many studies reveal that about 50 billion devices would be connected by 2020 indicating that Internet of things have a very big role to play in the future to come Considering the perplexing engineering of Smart City conditions, it ought not to be failed to remember that their establishment lies in correspondence advancements that permit availability and information move between the components in Smart City conditions. Remote interchanges with their capacities speak to Smart City empowering advancements that give the open door for their fast and effective execution and extension as well. The gigantic weight towards the proficient city the board has triggered various Smart City activities by both government and private area businesses to put resources into Information and Communication Technologies to discover feasible answers for the assorted chances and difficulties (e.g., waste the executives). A few specialists have endeavored to characterize a lot of shrewd urban areas and afterward recognize openings and difficulties in building brilliant urban communities. This short article likewise expresses the progressing movement of the Internet of Things and its relationship to keen urban communities. Advancement in ICT and data sharing innovation are the drivers of keen city degree and scale. This quick development is changing brilliant city development with the beginning of the Internet of Things (IoT). This transformation additionally speaks to difficulties in building (Kehua, Li, and Fu ,Su et al.1). By knowing the attributes of specific advances, the experts will have the occasion to create proficient, practical, and adaptable Smart City frameworks by actualizing the most reasonable one.

Applications of Big Data and Green IoT-Enabling Technologies for Smart Cities

2019 ◽  
pp. 22-41
Author(s):  
Onur Dogan ◽  
Omer Faruk Gurcan
Keyword(s):  
Big Data ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Smart Cities ◽  
Digital Data ◽  
Rapid Urbanization ◽  
Data Resource ◽  
Parallel Data ◽  
Information And Communication

In recent years, enormous amounts of digital data have been generated. In parallel, data collection, storage, and analysis technologies have developed. Recently, there has been an increasing trend of people moving towards urban areas. By 2030 more than 60% of the world's population will live in an urban environment. Urban areas are big data resource because they include millions of citizens, technological devices, and vehicles which generate data continuously. Besides, rapid urbanization brings many challenges, such as environmental pollution, traffic congestion, health problems, energy management, etc. Some policies for countries are required to cope with urbanization problems. One of these policies is to build smart cities. Smart cities integrate information and communication technology and various physical devices connected to the network (the internet of things or IoT) to both improve the quality of government services and citizen welfare. This chapter presents a literature review of big data, smart cities, IoT, green-IoT concepts, using technology and methods, and applications worldwide.

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.

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