scholarly journals DCluster: Geospatial Analytics with PoI Identification

2021 ◽  
Vol 12 (2) ◽  
Author(s):  
Cláudio Gustavo S. Capanema ◽  
Fabrício A. Silva ◽  
Thais R. M. Braga Silva ◽  
Antonio A. F. Loureiro
Keyword(s):  
Smart Cities ◽  
Human Mobility ◽  
Geospatial Data ◽  
Mobile Users ◽  
Data Types ◽  
Mobile Objects ◽  
Points Of Interest ◽  
Web System ◽  
Home Work

The generation of geospatial data is an inherent aspect for several applications that aim to track people, automobiles, or other mobile objects. Mining information from this type of data is a crucial factor for the development of Smart Cities. In many cases, it can help improve human mobility and the quality of citizens. In this sense, there is a growing demand for systems capable of extracting information from several data types, including the geospatial one. In this work, we present DCluster, a web system that aims to assist data analysts in exploring and visualizing the main types of data, including the geospatial one. Additionally, DCluster has the capability of discovering points of interest based on data of mobile users and classifying them as Home, Work, and Other locations. Data analysts can take advantage of DCluster to explore their data and extract knowledge from it.

scholarly journals Mobile Networks and Internet of Things Infrastructures to Characterize Smart Human Mobility

Smart Cities ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 894-918
Author(s):  
Luís Rosa ◽  
Fábio Silva ◽  
Cesar Analide
Keyword(s):  
Internet Of Things ◽  
Mobile Networks ◽  
Smart Cities ◽  
Human Mobility ◽  
Rapid Development ◽  
Disruptive Technology ◽  
New Paradigm ◽  
Design And Optimization ◽  
High Level

The evolution of Mobile Networks and Internet of Things (IoT) architectures allows one to rethink the way smart cities infrastructures are designed and managed, and solve a number of problems in terms of human mobility. The territories that adopt the sensoring era can take advantage of this disruptive technology to improve the quality of mobility of their citizens and the rationalization of their resources. However, with this rapid development of smart terminals and infrastructures, as well as the proliferation of diversified applications, even current networks may not be able to completely meet quickly rising human mobility demands. Thus, they are facing many challenges and to cope with these challenges, different standards and projects have been proposed so far. Accordingly, Artificial Intelligence (AI) has been utilized as a new paradigm for the design and optimization of mobile networks with a high level of intelligence. The objective of this work is to identify and discuss the challenges of mobile networks, alongside IoT and AI, to characterize smart human mobility and to discuss some workable solutions to these challenges. Finally, based on this discussion, we propose paths for future smart human mobility researches.

Spatial Autocorrelation in the Study of Neighbourhoods towards Smart Cities: Empirical Evidence from Kerman, Iran

2012 ◽  
Vol 9 (2) ◽  
pp. 1
Author(s):  
Asra Hosseini
Keyword(s):  
Spatial Autocorrelation ◽  
Urban Areas ◽  
Smart Cities ◽  
Moran’S I ◽  
Moran's I ◽  
Urban Planner ◽  
Universal Feature ◽  
Autocorrelation Method ◽  
Selection Of

From earliest cities to the present, spatial division into residential zones and neighbourhoods is the universal feature of urban areas. This study explored issue of measuring neighbourhoods through spatial autocorrelation method based on Moran's I index in respect of achieving to best neighbourhoods' model for forming cities smarter. The research carried out by selection of 35 neighbourhoods only within central part of traditional city of Kerman in Iran. The results illustrate, 75% of neighbourhoods' area in the inner city of Kerman had clustered pattern, and it shows reduction in Moran's index is associated with disproportional distribution of density and increasing in Moran's I and Z-score have monotonic relation with more dense areas and clustered pattern. It may be more efficient for urban planner to focus on spatial autocorrelation to foster neighbourhood cohesion rather than emphasis on suburban area. It is recommended characteristics of historic neighbourhoods can be successfully linked to redevelopment plans toward making city smarter, and also people's quality of life can be related to the way that neighbourhoods' patterns are defined. 

Spatial Autocorrelation in the Study of Neighbourhoods towards Smart Cities: Empirical Evidence from Kerman, Iran

2012 ◽  
Vol 9 (2) ◽  
pp. 1
Author(s):  
Asra Hosseini
Keyword(s):  
Spatial Autocorrelation ◽  
Smart Cities ◽  
Moran’S I ◽  
Moran's I ◽  
Urban Planner ◽  
Universal Feature ◽  
Autocorrelation Method ◽  
Selection Of ◽  
Monotonic Relation

From earliest cities to the present, spatial division into residential zones and neighbourhoods is the universal feature ofurban areas. This study explored issue ofmeasuring neighbourhoods through spatial autocorrelation method based on Moran's I index in respect of achieving to best neighbourhoods' model for forming cities smarter. The research carried out by selection of 35 neighbourhoods only within central part of traditional city of Kerman in Iran. The results illustrate, 75% ofneighbourhoods, area in the inner city of Kerman had clustered pattern, and it shows reduction in Moran's index is associated with disproportional distribution of density and increasing in Moran's I and Z-score have monotonic relation with more dense areas and clustered pattern. It may be more efficient for urban planner to focus on spatial autocorrelation to foster neighbourhood cohesion rather than emphasis on suburban area. It is recommended characteristics of historic neighbourhoods can be successfully linked to redevelopment plans toward making city smarter, and also people's quality of life can be related to the way that neighbourhoods' patterns are defined.

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 iBikeSafe: A Multi-Parameter System for Monitoring, Evaluation and Visualization of Cycling Paths in Smart Cities Targeted at Cycling Adverse Conditions

Smart Cities ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 1058-1086
Author(s):  
Franklin Oliveira ◽  
Daniel G. Costa ◽  
Luciana Lima ◽  
Ivanovitch Silva
Keyword(s):  
Urban Areas ◽  
Smart Cities ◽  
Large City ◽  
Health And Safety ◽  
Parameter System ◽  
Urban Centers ◽  
Adverse Conditions ◽  
Last Mile ◽  
Real Scenario

The fast transformation of the urban centers, pushed by the impacts of climatic changes and the dramatic events of the COVID-19 Pandemic, will profoundly influence our daily mobility. This resulted scenario is expected to favor adopting cleaner and flexible modal solutions centered on bicycles and scooters, especially as last-mile options. However, as the use of bicycles has rapidly increased, cyclists have been subject to adverse conditions that may affect their health and safety when cycling in urban areas. Therefore, whereas cities should implement mechanisms to monitor and evaluate adverse conditions in cycling paths, cyclists should have some effective mechanism to visualize the indirect quality of cycling paths, eventually supporting choosing more appropriate routes. Therefore, this article proposes a comprehensive multi-parameter system based on multiple independent subsystems, covering all phases of data collecting, formatting, transmission, and processing related to the monitoring, evaluating, and visualizing the quality of cycling paths in the perspective of adverse conditions that affect cyclist. The formal interactions of all modules are carefully described, as well as implementation and deployment details. Additionally, a case study is considered for a large city in Brazil, demonstrating how the proposed system can be adopted in a real scenario.

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.

Robust Networking: Dynamic Topology Evolution Learning for Internet of Things

2021 ◽  
Vol 17 (3) ◽  
pp. 1-23
Author(s):  
Ning Chen ◽  
Tie Qiu ◽  
Mahmoud Daneshmand ◽  
Dapeng Oliver Wu
Keyword(s):  
Internet Of Things ◽  
Smart Cities ◽  
Evolutionary Process ◽  
Small Error ◽  
Cyber Attacks ◽  
Communication Capacity ◽  
Error Ratio ◽  
The Internet Of Things ◽  
Evolution Learning

The Internet of Things (IoT) has been extensively deployed in smart cities. However, with the expanding scale of networking, the failure of some nodes in the network severely affects the communication capacity of IoT applications. Therefore, researchers pay attention to improving communication capacity caused by network failures for applications that require high quality of services (QoS). Furthermore, the robustness of network topology is an important metric to measure the network communication capacity and the ability to resist the cyber-attacks induced by some failed nodes. While some algorithms have been proposed to enhance the robustness of IoT topologies, they are characterized by large computation overhead, and lacking a lightweight topology optimization model. To address this problem, we first propose a novel robustness optimization using evolution learning (ROEL) with a neural network. ROEL dynamically optimizes the IoT topology and intelligently prospects the robust degree in the process of evolutionary optimization. The experimental results demonstrate that ROEL can represent the evolutionary process of IoT topologies, and the prediction accuracy of network robustness is satisfactory with a small error ratio. Our algorithm has a better tolerance capacity in terms of resistance to random attacks and malicious attacks compared with other algorithms.

scholarly journals Acknowledgment to Reviewers of Smart Cities in 2020

Smart Cities ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. 192-194
Author(s):  
Keyword(s):  
Peer Review ◽  
Driving Force ◽  
Smart Cities ◽  
High Quality

Peer review is the driving force of journal development, and reviewers are gatekeepers who ensure that Smart Cities maintains its standards for the high quality of its published papers [...]

Machine learning techniques based on security management in smart cities using robots

Work ◽  
2021 ◽  
pp. 1-12
Author(s):  
Zhang Mengqi ◽  
Wang Xi ◽  
V.E. Sathishkumar ◽  
V. Sivakumar
Keyword(s):  
Machine Learning ◽  
Information And Communication Technologies ◽  
Smart City ◽  
Smart Cities ◽  
Security Management ◽  
Machine Learning Techniques ◽  
Quality Of Services ◽  
Learning Techniques ◽  
Learning Concept

BACKGROUND: Nowadays, the growth of smart cities is enhanced gradually, which collects a lot of information and communication technologies that are used to maximize the quality of services. Even though the intelligent city concept provides a lot of valuable services, security management is still one of the major issues due to shared threats and activities. For overcoming the above problems, smart cities’ security factors should be analyzed continuously to eliminate the unwanted activities that used to enhance the quality of the services. OBJECTIVES: To address the discussed problem, active machine learning techniques are used to predict the quality of services in the smart city manages security-related issues. In this work, a deep reinforcement learning concept is used to learn the features of smart cities; the learning concept understands the entire activities of the smart city. During this energetic city, information is gathered with the help of security robots called cobalt robots. The smart cities related to new incoming features are examined through the use of a modular neural network. RESULTS: The system successfully predicts the unwanted activity in intelligent cities by dividing the collected data into a smaller subset, which reduces the complexity and improves the overall security management process. The efficiency of the system is evaluated using experimental analysis. CONCLUSION: This exploratory study is conducted on the 200 obstacles are placed in the smart city, and the introduced DRL with MDNN approach attains maximum results on security maintains.

Land-uses as Quality of Making Successful Streets in Sulaimaniya City Centre, Iraq

2021 ◽  
Author(s):  
Musaab Al-Obeidy ◽  
Keyword(s):  
Global Positioning System ◽  
Structured Interview ◽  
City Centre ◽  
Key Factors ◽  
City Center ◽  
Qualitative And Quantitative ◽  
Points Of Interest ◽  
Global Positioning ◽  
Questionnaire Surveys

Although, the diverse activities and uses are one of the significant key factors to improve quality of streets, some places and shops in Mawlawi Street are disappeared or used by few number of people, while others are used by high number of people. Moreover, just some attractions and points of interest (POIs) are located in the Global Positioning System (GPS). This issues lead to lake of finding urban diversity in Mawlawi Street. This paper examines and find out the diversity of activities and uses that improves the quality of streets and makes successful streets in Sulaimaniya City Centre. It is also to identify POIs provided in GPS. The study employed a mix-methodology method. 330 questionnaire surveys, 20 semi-structured interview, and qualitative and quantitative observation, were conducted in Mawlawi Street. The results show that the diverse activities and choices are important key to make streets of Sulaimaniya City Center successful. There is also a need to define and insert many places on map for enhancing diversity. To secure the quality of the Street, this study suggests to improve the quality of goods and shops, provide night activities, and refresh some left places and shops along the Street.

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