scholarly journals PADL: A Modeling and Deployment Language for Advanced Analytical Services

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6712
Author(s):  
Josu Díaz-de-Arcaya ◽  
Raúl Miñón ◽  
Ana I. Torre-Bastida ◽  
Javier Del Ser ◽  
Aitor Almeida
Keyword(s):  
Smart City ◽  
Flood Control ◽  
Smart Cities ◽  
Big Data Analytics ◽  
Heterogeneous Environments ◽  
Iot Devices ◽  
Definition Of ◽  
Definition Of Information ◽  
Analytical Services

In the smart city context, Big Data analytics plays an important role in processing the data collected through IoT devices. The analysis of the information gathered by sensors favors the generation of specific services and systems that not only improve the quality of life of the citizens, but also optimize the city resources. However, the difficulties of implementing this entire process in real scenarios are manifold, including the huge amount and heterogeneity of the devices, their geographical distribution, and the complexity of the necessary IT infrastructures. For this reason, the main contribution of this paper is the PADL description language, which has been specifically tailored to assist in the definition and operationalization phases of the machine learning life cycle. It provides annotations that serve as an abstraction layer from the underlying infrastructure and technologies, hence facilitating the work of data scientists and engineers. Due to its proficiency in the operationalization of distributed pipelines over edge, fog, and cloud layers, it is particularly useful in the complex and heterogeneous environments of smart cities. For this purpose, PADL contains functionalities for the specification of monitoring, notifications, and actuation capabilities. In addition, we provide tools that facilitate its adoption in production environments. Finally, we showcase the usefulness of the language by showing the definition of PADL-compliant analytical pipelines over two uses cases in a smart city context (flood control and waste management), demonstrating that its adoption is simple and beneficial for the definition of information and process flows in such environments.

scholarly journals Urban Planning and Smart City Decision Management Empowered by Real-Time Data Processing Using Big Data Analytics

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2994 ◽  
Author(s):  
Bhagya Silva ◽  
Murad Khan ◽  
Changsu Jung ◽  
Jihun Seo ◽  
Diyan Muhammad ◽  
...  
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Real Time ◽  
Smart City ◽  
Data Analytics ◽  
Smart Cities ◽  
Big Data Analytics ◽  
Time Data ◽  
Real Time Data

The Internet of Things (IoT), inspired by the tremendous growth of connected heterogeneous devices, has pioneered the notion of smart city. Various components, i.e., smart transportation, smart community, smart healthcare, smart grid, etc. which are integrated within smart city architecture aims to enrich the quality of life (QoL) of urban citizens. However, real-time processing requirements and exponential data growth withhold smart city realization. Therefore, herein we propose a Big Data analytics (BDA)-embedded experimental architecture for smart cities. Two major aspects are served by the BDA-embedded smart city. Firstly, it facilitates exploitation of urban Big Data (UBD) in planning, designing, and maintaining smart cities. Secondly, it occupies BDA to manage and process voluminous UBD to enhance the quality of urban services. Three tiers of the proposed architecture are liable for data aggregation, real-time data management, and service provisioning. Moreover, offline and online data processing tasks are further expedited by integrating data normalizing and data filtering techniques to the proposed work. By analyzing authenticated datasets, we obtained the threshold values required for urban planning and city operation management. Performance metrics in terms of online and offline data processing for the proposed dual-node Hadoop cluster is obtained using aforementioned authentic datasets. Throughput and processing time analysis performed with regard to existing works guarantee the performance superiority of the proposed work. Hence, we can claim the applicability and reliability of implementing proposed BDA-embedded smart city architecture in the real world.

scholarly journals Cyberattacks Detection in IoT-Based Smart City Applications Using Machine Learning Techniques

2020 ◽  
Vol 17 (24) ◽  
pp. 9347 ◽  
Author(s):  
Md Mamunur Rashid ◽  
Joarder Kamruzzaman ◽  
Mohammad Mehedi Hassan ◽  
Tasadduq Imam ◽  
Steven Gordon
Keyword(s):  
Machine Learning ◽  
Smart City ◽  
Service Providers ◽  
Detection System ◽  
Smart Cities ◽  
Machine Learning Algorithms ◽  
Machine Learning Techniques ◽  
Increased Risk ◽  
Iot Devices

In recent years, the widespread deployment of the Internet of Things (IoT) applications has contributed to the development of smart cities. A smart city utilizes IoT-enabled technologies, communications and applications to maximize operational efficiency and enhance both the service providers’ quality of services and people’s wellbeing and quality of life. With the growth of smart city networks, however, comes the increased risk of cybersecurity threats and attacks. IoT devices within a smart city network are connected to sensors linked to large cloud servers and are exposed to malicious attacks and threats. Thus, it is important to devise approaches to prevent such attacks and protect IoT devices from failure. In this paper, we explore an attack and anomaly detection technique based on machine learning algorithms (LR, SVM, DT, RF, ANN and KNN) to defend against and mitigate IoT cybersecurity threats in a smart city. Contrary to existing works that have focused on single classifiers, we also explore ensemble methods such as bagging, boosting and stacking to enhance the performance of the detection system. Additionally, we consider an integration of feature selection, cross-validation and multi-class classification for the discussed domain, which has not been well considered in the existing literature. Experimental results with the recent attack dataset demonstrate that the proposed technique can effectively identify cyberattacks and the stacking ensemble model outperforms comparable models in terms of accuracy, precision, recall and F1-Score, implying the promise of stacking in this domain.

scholarly journals The functioning of smart city in the context of global city rankings

2020 ◽  
Vol 2020 (146) ◽  
pp. 413-425
Author(s):  
Barbara ROŻAŁOWSKA ◽  
Keyword(s):  
Smart City ◽  
Urban Areas ◽  
Smart Cities ◽  
Life Quality ◽  
Theoretical Models ◽  
Operational Definition ◽  
Quality Of Living ◽  
Definition Of ◽  
City Rankings

Purpose: This paper raises theoretical issues related to the functioning of cities that are determined as smart in order to find a better operational definition for further research. Design/methodology/approach: In search of the essence of the term, the paper refers to variety of definitions of smart city, and also to the theoretical models in operation enabling the measurement and comparison of indicators among urban areas in the different world locations. The analysis was performed on three rankings: Cities in Motion Index, Mercer Quality of Living, Arcadis The Sustainable Index. Findings: The conclusions indicate that the Smart City concept is connected with sustainable development more than to the quality of life. The city rankings concerning the highest life quality is completely different from the hierarchy of smart cities. Originality/value: The paper extends the definition of smart city and it may be valuable for researchers who develop the concept of smart city in their research.

scholarly journals Smart Cities Marketing and Its Conceptual Grounds

2019 ◽  
Vol 65 (4) ◽  
pp. 110-116
Author(s):  
Anita Maček ◽  
Rasto Ovin ◽  
Urška Starc-Peceny
Keyword(s):  
Quality Of Life ◽  
Smart City ◽  
Smart Cities ◽  
City Management ◽  
Endogenous Growth Theory ◽  
Definition Of ◽  
Smart Communities ◽  
Changing Role

AbstractThe most frequent definition of the smart city in the literature defines it as a developed urban area that creates sustainable economic development and high quality of life. Therefore, a city should always be capable of identifying and effectively resolving its key development challenges in order to improve the quality of life of its citizens. Regarding economics approach, the authors rely on endogenous growth theory derived from Arrow. The authors explore the role of smart city management and governance, which will have to combine the need for capital with the need to ensure the environment that this capital will enhance modern urban producing factors. Hence, the authors discuss communication aspects and the importance of the evolution toward smart communities, where the idea is not on making places smart anymore, but rather focus on humans and their needs. For an emerging smart city, market built up of smaller cities and municipalities describes the changing role of marketing and the shift of roles in its processes in order to show the urge to become familiar with the spirit of open innovation and rethink marketing strategy in this emerging reality.

Big Data Analytics and Internet of Things for Urban Transportation

2019 ◽  
pp. 244-277
Author(s):  
Jyoti Chandiramani ◽  
Sushma Nayak
Keyword(s):  
Big Data ◽  
Public Transportation ◽  
Traffic Congestion ◽  
Smart City ◽  
Traffic Management ◽  
Smart Cities ◽  
Big Data Analytics ◽  
Considerable Impact ◽  
The Government

The idea of smart city has assumed popularity in numerous countries across the globe. In 2015, the Government of India embarked on a mission of creating 100 smart cities to sustain the burgeoning urban population. While a wide-ranging set of fundamentals has a key role in enhancing the quality of life of citizens, the chapter revolves around transportation issues and traffic management concerns in one of India's smart cities, Pune. Transport is one of the few areas where Pune lags behind compared to its urban counterparts in the country. Public transportation in the city has been ineffectual, and auto rickshaws have been unyielding and pricey, thus making it imperative to possess personal vehicles or resort to app-based cab services. A palpable outcome of this has been traffic congestion that leads to slower travelling speeds, extended trip times, and amplified vehicular queuing. Big data and IoT can make a considerable impact in realizing the smart city objectives for efficient transportation in Pune by serving as complementary measures to supply-side policies.

scholarly journals Tendencies of Technologies and Platforms in Smart Cities: A State-of-the-Art Review

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Pablo Chamoso ◽  
Alfonso González-Briones ◽  
Sara Rodríguez ◽  
Juan M. Corchado
Keyword(s):  
Smart City ◽  
Large Scale ◽  
New Technologies ◽  
State Of The Art ◽  
Smart Cities ◽  
Clear Understanding ◽  
Smart Systems ◽  
Definition Of

Technology is starting to play a key role in cities’ urban sustainability plans. This is because new technologies can provide them with robust solutions that are of benefit to citizens. Cities aim to incorporate smart systems in their industrial, infrastructural, educational, and social activities. A Smart City is managed with intelligent technologies which allow improving the quality of the services offered to citizens and make all processes more efficient. However, the Smart City concept is fairly recent. The ideas that it encompasses have not yet been consolidated due to the large number of fields and technologies that fit under this concept. All of this led to confusion about the definition of a Smart City and this is evident in the literature. This article explores the literature that addresses the topic of Smart Cities; a comprehensive analysis of the concept and existing platforms is performed. We gain a clear understanding of the services that a Smart City must provide, the technology it should employ for the development of these services, and the scope that this concept covers. Moreover, the shortcomings and needs of Smart Cities are identified and a model for designing a Smart City architecture is proposed. In addition, three case studies have been proposed: the first is a simulator to study the implementation of various services and technologies, the second case study to manage incidents that occur in a Smart City, and the third case study to monitor the deployment of large-scale sensors in a Smart City.

Systematization of the smart city civil engineering infrastructure

2020 ◽  
Vol 18 (4) ◽  
pp. 765-779
Author(s):  
E.V. Popov ◽  
K.A. Semyachkov ◽  
K.V. Zhunusova
Keyword(s):  
Smart City ◽  
Process Management ◽  
Smart Cities ◽  
Digital Technologies ◽  
Urban Infrastructure ◽  
Infrastructure Development ◽  
Economic Innovation ◽  
Civil Engineering Infrastructure ◽  
Functional Transformations

Subject. This article explores the basic elements of the engineering infrastructure of smart cities. Objectives. The article aims to systematize theoretical descriptions of the engineering infrastructure of a smart city. Methods. For the study, we used a logical analysis and systematization. Results. The article highlights the main areas of infrastructure development of smart cities. Conclusions. Improving process management mechanisms, optimizing urban infrastructure, increasing the use of digital technologies, and developing socio-economic innovation improve the quality of the urban environment in a digitalized environment. And improving the efficiency of urban planning and security, studying its properties and characteristics, and forming an effective urban information system lead to its functional transformations.

scholarly journals Sustainable Smart City—Opening a Black Box

2021 ◽  
Vol 13 (2) ◽  
pp. 769
Author(s):  
Mona Treude
Keyword(s):  
Sustainable Development ◽  
Citizen Participation ◽  
Smart City ◽  
Evolutionary Economics ◽  
Smart Cities ◽  
Innovation Process ◽  
Sustainable City ◽  
Smart Services ◽  
Underlying Processes

Cities are becoming digital and are aiming to be sustainable. How they are combining the two is not always apparent from the outside. What we need is a look from inside. In recent years, cities have increasingly called themselves Smart City. This can mean different things, but generally includes a look towards new digital technologies and claim that a Smart City has various advantages for its citizens, roughly in line with the demands of sustainable development. A city can be seen as smart in a narrow sense, technology wise, sustainable or smart and sustainable. Current city rankings, which often evaluate and classify cities in terms of the target dimensions “smart” and “sustainable”, certify that some cities are both. In its most established academic definitions, the Smart City also serves both to improve the quality of life of its citizens and to promote sustainable development. Some cities have obviously managed to combine the two. The question that arises is as follows: What are the underlying processes towards a sustainable Smart City and are cities really using smart tools to make themselves sustainable in the sense of the 2015 United Nations Sustainability Goal 11? This question is to be answered by a method that has not yet been applied in research on cities and smart cities: the innovation biography. Based on evolutionary economics, the innovation biography approaches the process towards a Smart City as an innovation process. It will highlight which actors are involved, how knowledge is shared among them, what form citizen participation processes take and whether the use of digital and smart services within a Smart City leads to a more sustainable city. Such a process-oriented method should show, among other things, to what extent and when sustainability-relevant motives play a role and which actors and citizens are involved in the process at all.

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 Sustainable Virtual Reality Patient Rehabilitation Systems with IoT Sensors Using Virtual Smart Cities

2021 ◽  
Vol 13 (9) ◽  
pp. 4716
Author(s):  
Moustafa M. Nasralla
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Virtual Reality ◽  
Time Series Analysis ◽  
Smart City ◽  
Smart Cities ◽  
Rehabilitation Services ◽  
Simulation Scenario ◽  
Common Problems ◽  
Iot Devices

To develop sustainable rehabilitation systems, these should consider common problems on IoT devices such as low battery, connection issues and hardware damages. These should be able to rapidly detect any kind of problem incorporating the capacity of warning users about failures without interrupting rehabilitation services. A novel methodology is presented to guide the design and development of sustainable rehabilitation systems focusing on communication and networking among IoT devices in rehabilitation systems with virtual smart cities by using time series analysis for identifying malfunctioning IoT devices. This work is illustrated in a realistic rehabilitation simulation scenario in a virtual smart city using machine learning on time series for identifying and anticipating failures for supporting sustainability.

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