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

scholarly journals CitySpeed: A Crowdsensing-Based Integrated Platform for General-Purpose Monitoring of Vehicular Speeds in Smart Cities

Smart Cities ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 46-65 ◽  
Author(s):  
Daniel Costa ◽  
Adson Damasceno ◽  
Ivanovitch Silva
Keyword(s):  
Smart City ◽  
Urban Areas ◽  
Large Scale ◽  
Smart Cities ◽  
General Purpose ◽  
Software Application ◽  
Management Actions ◽  
Modern Cities ◽  
Time Period ◽  
Search Filters

The development of crowdsensing-based technologies has allowed for the use of smartphones in large-scale data collection for different scopes of applications, mostly in a transparent and ubiquitous way. When concerning urban areas and smart city initiatives, the collection and further analysis of information about the highest number of vehicles is of paramount importance, potentially supporting more efficient mobility planning and management actions in modern cities. In this context, this article proposes a public general-purpose platform for acquisition and visualization of vehicular speeds, which can then be exploited by any additional application. For that, a crowdsensing-based mobile software application was developed to collect instantaneous speeds provided by smartphone GPS, formatting and distributing this information to a database system. Such historical data can then be exported or visualized through a web-based comprehensive interface, which provides valuable data when planning traffic mobility in cities; for example, indicating areas with heavier traffic over a certain time period. Therefore, allowing the use of many different search filters and supporting data delivery in the JSON format, the CitySpeed platform can provide services not supported by popular applications, such as Waze and Google Maps, and potentially assist smart city initiatives in this area.

A Study of Key Attributes Accountable for Development of a Smart City Projects & Factors Impacting its Implementation in India

2018 ◽  
Vol 6 (9) ◽  
pp. 19
Author(s):  
Shubhangi Sandeep Tambe
Keyword(s):  
Water Management ◽  
Smart City ◽  
Urban Areas ◽  
Large Scale ◽  
Smart Cities ◽  
Basic Question ◽  
Political Will ◽  
The World ◽  
The Government ◽  
Will Power

he concept of Smart Cities was first thought of by IBM in 2008 when world was facing its worst economic crisis. Then it was taken up by various countries around the world. The main objective here is to build and promote the cities which will provide the core infrastructure and provide the decent quality of life along with a clean and long-lasting environment which will be supported by smart technologies & solutions. Though smart city concepts are very new to India, where technology is mostly used in urban cities. So, in such a scenario one may ask a very basic question that “How a city can be made Smart?”. So, if we look around and see what are the things that some smart cities around the world are doing differently, then we may notice that they have addressed basic issues faced by any metropolitan city in a smarter way possible. For instance, we can see that the already developed smart city projects have addressed transportation, energy, crime, water management & other issues using current technologies & applications. If we leave aside the technology gap between rural & urban India, it is certain that Urban areas are already in need of Smart City Projects because of Population. But again, this needs a strong political will power to take quick decisions and aligned with technological advances such as E governance, online tendering of the government work which will be transparent and efficient. but often it is misunderstood that use of IT in administration and governance is the only meaning of Smart City Projects, but in fact if you are able to achieve all the issues such as administration, governance, transportation, water management, energy supplies, waste management, water treatments plants, meaningful use of public private partnerships in managing transportations and road constructions and evening installations of solar panels and LED bulbs across city. So basically, there are many factors contributing to create a smart city. The main factor which will drive this kind of ambitious projects are political will powers of government, without a political will power it is very difficult to complete the bigger projects. As there is lot on stake for such a large-scale project which will easily span over next decade.

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.

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.

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.

Do Smart Cities Invest in Smarter Policies? Learning From the Past, Planning for the Future

2016 ◽  
Vol 34 (6) ◽  
pp. 657-672 ◽  
Author(s):  
Andrea Caragliu ◽  
Chiara F. Del Bo
Keyword(s):  
Smart City ◽  
Urban Areas ◽  
Large Scale ◽  
Smart Cities ◽  
Empirical Relationship ◽  
Data Set ◽  
Empirical Results ◽  
Real Effects ◽  
Definition Of ◽  
The Relationship

Research on Smart Cities has come of age. Intense discussion on this topic has been ongoing for years, and the academic prominence of this concept has also engendered several policy initiatives inspired by this label at different administrative levels. However, to date, no large-scale evaluation of the relationship between urban smartness and smart urban policies has been attempted. This article aims at filling this gap. By building on a solid definition of Smart Cities, the article tests the empirical relationship between urban smartness and the intensity of Smart City policies. A novel data set on four different types of policies and smart urban characteristics is assembled for 314 European Union cities. Empirical results suggest that Smart City policies are more likely to be designed and implemented in cities that are already endowed with smart characteristics. Our findings also point to a higher probability that Smart City policies are implemented in denser and wealthier urban areas. These empirical results call for further research on the real effects of actual implemented Smart City policies, with the aim to verify the potential of this policy concept as an overall urban development model encompassing the main drivers of endogenous urban growth.

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 Discussion on the Construction of Spatiotemporal Big Data Platform for Smart City

2020 ◽  
Vol 3 (5) ◽  
Author(s):  
Jun Li
Keyword(s):  
Big Data ◽  
Smart City ◽  
Smart Cities ◽  
Computing Technology ◽  
Construction Planning ◽  
Urban Construction ◽  
Data Platform ◽  
New Form ◽  
Internet Of Things Technology ◽  
Big Data Technology

The so-called smart city is a new form of information technology that is achieved through the integration of the contemporary advanced big data technology, Internet of Things technology, cloud computing technology, and spatial geographic information. At present, the application of this technology is important for the urban construction, planning, and services as well as management. This technology also provides great convenience in these aspects, which has allowed the cities to develop and transform towards the direction of smart cities. Based on this situation, the construction of spatiotemporal big data platforms in smart cities was analyzed in this article, and this analysis may provide a reference for the construction and development of today’s smart cities.

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.

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