Smart City Management Systems Research Articles

Visibility-Based R-Tree Spatial Index for Consistent Visualization in Indoor and Outdoor Scenes

(1) Background: The smart city management system, with GIS technology as its core, is based on realistic visualization of multiple types of 3D model data syntheses. However, the efficiency barriers to achieving smooth and continuous visualization from outdoor scenes to small indoor scenes remain a challenge. (2) Methods: This paper uses the visibility prediction method to obtain potential visual sets at three levels—outdoor, indoor and outdoor connection, and indoor—and constructs an R-tree spatial index structure for organizing potential visual sets. By integrating these potential visible sets with spatial indexes, scene visualization can be carried out effectively. (3) Results: A near-reality indoor and outdoor scene was used for experimentation, resulting in stable 10% fluctuation visual frame rates around 90 FPS. (4) Conclusions: Spatial indexing methods that combine potential visible sets can effectively solve the continuity and stability problem of indoor and outdoor scene visualization in smart city management systems.

Enhancing Smart City Waste Management through LBBOA based RIAN Classification

Effective trash management has become a top environmental priority, especially in urban areas with significant population growth where garbage output is on the rise. As cities work to manage garbage properly, innovative waste management programmes have the potential to increase effectiveness, cut costs, and improve the aesthetic appeal of public places. This article introduces SCM-RIAN, a powerful "Smart City Management and Classification System" built on the Internet of Things (IoT) and deep learning (DL) technologies. Convolutional neural networks are used in the garbage classification model that is implemented within this smart city management and classification framework. This system for classifying waste is intended to categorise rubbish into several classes at waste collection sites, encouraging recycling. The Rotation-Invariant Attention Network (RIAN) is a unique approach presented for the categorization process to address a prevalent problem in smart city management (SCM). A Centre Spectral Attention (CSpeA) module built within RIAN isolates spectral bands from other categories of pixels' influence, reducing redundancy. As an alternative to the conventional 3 3 convolution, to obtain rotation-invariant spectral-spatial data contained in SCM patches, the Rectified Spatial Attention (RSpaA) module is also introduced. The suggested RIAN for SCM classification is built on the integration of the CSpeA, 11 convolution, and RSpaA modules. The Ladybird Beetle Optimisation Algorithm (LBBOA) is used to optimise hyperparameters. With improved results compared to other current models, this suggested SCM-RIAN achieved 98.12% accuracy (ACC) with high sensitivity (SEN), specificity (SPEC), and kappa index (KI) using the garbage classification dataset.

Implementation of world and Russian indicators of the “smart city” concept in the environmental parameters of the development of urbanized territories

In recent years, one can observe more intensive anthropogenic development of urban areas in the world and in the Russian Federation. This has led to the growth of urban agglomerations and a high level of urbanization, which negatively affects not only the environment, but also the social and economic components. One can note the trend in the development of digital technologies. The introduction of new technologies aimed at improving the lives of the population and creating sustainable development of the subject also has an environmental context. There is a noticeable similarity between the criteria of a “Smart City” and the goals of achieving sustainable development. They have a common direction - the creation of a comfortable and sustainable urban space, where the environmental, economic and social components will function in a single system and balance each other. But the main limitation of the implementation of this concept in Russia is the lack of funding and its uneven distribution across regions. The smart city management system should be a complex whole of interconnected elements, where the functioning of a separate part ensures the operation of the entire system as a whole. The result should be an increase in the efficient functioning of government bodies and an improvement in the quality of life of the population preserving the environment.

Iot Based Smart City Management System

Iot Based Smart City Management System

Response Time and Intrinsic Information Quality as Criteria for the Selection of Low-Cost Sensors for Use in Mobile Weather Stations

Smart-city management systems use information about the environment, including the current values of weather factors. The specificity of the urban sites requires a high density of weather measurement points, which forces the use of low-cost sensors. A typical problem of devices using low-cost sensors is the lack of legalization of the sensors and the resulting inaccuracy and uncertainty of measurement, which one can attempt to solve by additional sensor calibration. In this paper, we propose a different approach to this problem, i.e., the two-stage selection of sensors, carried out on the basis of both the literature (pre-selection) and experiments (actual selection). We formulated the criteria of the sensor selection for the needs of the sources of weather information: the major one, which is the fast response time of a sensor in a cyber-physical subsystem and two minor ones, which are based on the intrinsic information quality dimensions related to measurement information. These criteria were tested by using a set of twelve weather sensors from different manufacturers. Results show that the two-stage sensor selection allows us to choose the least energy consuming (due to the major criterion) and the most accurate (due to the minor criteria) set of weather sensors, and is able to replace some methods of sensor selection reported in the literature. The proposed method is, however, more versatile and can be used to select any sensors with a response time comparable to electric ones, and for the application of low-cost sensors that are not related to weather stations.

Applying distributed ledger technologies in megacities to face anthropogenic burden challenges

Distributed ledger technologies can support a rapid transition to smart cities and provide a high level of urban quality. Despite the large number of approaches to the problem of synthesizing smart city management systems, there is still no universal solution. One of the most promising areas is the construction of neural network control systems. The optimization module for a neurosimulator is developed that can operate in real time. The study of the neurosimulator on various data of anthropogenic load showed the possibility of obtaining high control accuracy.

Development of methods for evaluating the effectiveness of smart cities under the conditions of digitalization of city governance

This paper considers the processes of digitalization of urban management, which forms the prerequisites for solving the problem of the development of the concept of smart cities. As a result, the historical aspects of the formation of the Smart City concept are distinguished. Based on this, elements of the Smart City concept are highlighted at the present stage, such as vision, ecosystem, management, technological background, and financing. Generalization of the results of the study of the processes of digitalization of smart city management has made it possible to distinguish its traditional components, which include transport, energy, utilities, urban environment, security, and "smart" house. In order to ensure effective monitoring of the implementation and development of digital services in the smart city management system, it is proposed to use "city smartophores". The systematization of the Smart City formation experience provided an opportunity to distinguish the relevant models of digitalization of urban governance – decentralized, centralized, and local. The scope of application, initiators, advantages and disadvantages, and prospects for the development of each of them are determined. Unlike other results of the study of the effectiveness of the development of smart cities, it is suggested that the most vivid picture of ensuring a comfortable life in the city is demonstrated by the size of its population. It is proved that it is in the developed cities of any country in the world that there are positive rates of population growth. Quantitative criteria for determining the upper and lower limits of the efficiency of smart city development according to the selected indicator have been developed. The practical application of the results of the study is the possibility of predicting further directions of development of the smart city based on a quantitative assessment of the level of its digital transformation

Подходы к формированию системы управления Smart City в мировой практике

The purpose of the study is to systematize the ideas about the management of Smart City based on the global experience of smart cities. The article discusses approaches to the formation of a smart city management system, participants in the management system and communications between them, as well as other elements that ensure the effectiveness of management in the world's smart cities. The scientific novelty lies in determining the similarity of the approaches of smart leading cities to management, key principles and elements of the management system of a modern city. As a result, the general basic characteristics of the city management system were identified: the transition from a hierarchical model to a mechanism for the interaction of key stakeholders, including the population; implementation of the principle of openness in the development and monitoring of the implementation of the city's strategy; inclusion of business, science and education and other stakeholders in the process of developing and implementing city development projects; approbation of projects in strategic areas of city development on digital models and twins.

LSM: A Lightweight Security Mechanism for IoT Based Smart City Management Systems using Blockchain

Smart cities utilize digital technologies for the improvement of its services’ quality and performance by reducing resources’ cost and consumption, with a commitment of action and efficiency to its citizens. The increased urban migration has led to many problems in cities, such as traffic congestion, waste management, noise pollution, energy consumption, air pollution, etc., as nowadays COVID-19 pandemic has seized the whole world. So, it is necessary to carry out its standard operating procedures (SOPs), including less human interaction. Thus, technology plays a vital role via Internet-of-Things (IoT) based systems. In this paper, a lightweight security mechanism (LSM) is proposed to enrich the IoT based systems. Blockchain technology is integrated, and its completely decentralized peer-to-peer (P2P) technology enables the users’ authentication and authorizes legitimate procedures. The IoT based management system is developed to monitor some of the aforementioned problems and solve solid waste, air, and noise monitoring systems. The Ethereum blockchain is used to implement a smart contract based framework for the system’s security and access control. The evaluation of performance of the LSM demonstrates that it is an efficient and lightweight tool in terms of cost, resources, and computation and superior over related security studies.

An Investigation of Garbage Disposal Electric Vehicles (GDEVs) Integrated with Deep Neural Networking (DNN) and Intelligent Transportation System (ITS) in Smart City Management System (SCMS)

An Investigation of Garbage Disposal Electric Vehicles (GDEVs) Integrated with Deep Neural Networking (DNN) and Intelligent Transportation System (ITS) in Smart City Management System (SCMS)

Weather Sensing in an Urban Environment with the Use of a UAV and WebRTC-Based Platform: A Pilot Study.

Thanks to IoT, Internet access, and low-cost sensors, it has become possible to increase the number of weather measuring points; hence, the density of the deployment of sources that provide weather data for the needs of large recipients, for example, weather web services or smart city management systems, has also increased. This paper presents a flying weather station that carries out measurements of two weather factors that are typically included in weather stations (ambient temperature and relative humidity), an often included weather factor (atmospheric pressure), and a rarely included one (ultraviolet index). In our solution, the measurements are supplemented with a visual observation of present weather phenomena. The flying weather station is built on a UAV and WebRTC-based universal platform proposed in our previous paper. The complete, fully operational flying weather station was evaluated in field studies. Experiments were conducted during a 6-month period on days having noticeably different weather conditions. Results show that weather data coming from the flying weather station were equal (with a good approximation) to weather data obtained from the reference weather station. When compared to the weather stations described in the literature (both stationary weather stations and mobile ones), the proposed solution achieved better accuracy than the other weather stations based on low-cost sensors.

Urban management image classification approach based on deep learning

Based on the case images in the smart city management system, the advantage of deep learning is used to learn image features on its own, an improved deep convolutional neural network algorithm is proposed in this paper, and the algorithm is used to improve the smart city management system (hereinafter referred to as “Smart City Management”). These case images are quickly and accurately classified, the automatic classification of cases is completed in the city management system. ZCA (Zero-phase Component Analysis)-whitening is used to reduce the correlation between image data features, an eight-layer convolutional neural network model is built to classify the whitened images, and rectified linear unit (ReLU) is used in the convolutional layer to accelerate the training process, the dropout technology is used in the pooling layer, the algorithm is prevented from overfitting. Back Propagation (BP) algorithm is used for optimization in the network fine-tuning stage, the robustness of the algorithm is improved. Based on the above method, the two types of case images of road traffic and city appearance environment were subjected to two classification experiments. The accuracy has reached 97.5%, and the F1-Score has reached 0.98. The performance exceeded LSVM (Langrangian Support Vector Machine), SAE (Sparse autoencoder), and traditional CNN (Convolution Neural Network). At the same time, this method conducts four-classification experiments on four types of cases: electric vehicles, littering, illegal parking of motor vehicles, and mess around garbage bins. The accuracy is 90.5%, and the F1-Score is 0.91. The performance still exceeds LSVM, SAE and traditional CNN and other methods.

Big Data in Smart City: Management Challenges

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.

Addressing disasters in smart cities through UAVs path planning and 5G communications: A systematic review

UAVs are increasingly incorporated in a wide range of domains such as disaster management and rescue missions. UAV path planning deals with finding the most optimal or shortest path for UAVs such that minimum energy and resources are utilized. This paper examines the path planning algorithms for UAVs through a literature survey conducted on 139 systematically retrieved articles published in the last decade that are narrowed down to 36 highly relevant articles. As retrieved from the shortlisted articles, the path planning algorithms include RRT, Artificial Potential, Voronoi, D-Star, A-Star, Dijkstra, MILP, Neural Network, Ant Colony Optimization, and Particle Swarm Optimization that are classified into four main types: Model-based, Conventional, Learning-based, and Cell-based. Most of the disaster-related articles are focused on the post-disaster phase only and use conventional and learning-based algorithms with applications to localize victims and optimize paths. Regarding the UAV communication network (UAVCN), the key challenges are communication issues, resource allocation, UAV deployment, defining UAV trajectory, and content security. UAV path planning’s key barriers are path optimization, path completeness, optimality, efficiency, and achieving robustness. Accordingly, a holistic IoT-powered UAV-based smart city management system has been recommended in the current study where all the smart city key components are integrated to address disasters like floods, earthquakes, and bush fire. The proposed holistic system can help prepare for disasters and mitigate them as soon as these arise and help enhance the smart city governance.

Energy aware smart city management system using data analytics and Internet of Things

The rise of Internet of Things (IoT) concept founded the realization of a smart city. Energy management has lately turn out to be a vital concern for the services of a smart city as IoT devices consume massive energy constantly. This concern needs to be addressed to devise a practical method. Efficient energy utilization aims to promise smart city sustainability. Moreover, IoT devices produce enormous data that is required to be processed efficiently. In this article, a framework is proposed that assures the energy efficiency of IoT devices along with data analysis for cities. This article proposes a general design for smart city energy management that assures the energy efficiency of IoT devices along with data analysis. The proposed model includes three different components that are energy management, data processing, and service management. The energy management component is dependent on infrastructure optimization. The energy-efficient clustering, peak load shaving, optimized scheduling, and load balancing algorithms are integrated to achieve efficient energy management. The data processing is performed using distributed framework. The service management is performed using rules and thresholds. The experiments are performed using authentic datasets and the result highlights the efficiency of the proposed model.

Smart Management for Smart Cities - Synchronized Solutions

The paper observes the most updated concepts of Smart Cities. Problem of sustainable development of the cities is presented. An overview of transformation from Smart Cities to Smart Countries is given. Intelligent management system is proposed in the paper enhancing efficiency in the application of intelligent e-Government and Smart City projects in all areas. Integrated Operation Center is introduced - a new concept of operational intelligence, being able to digitize, monitor, predict, act, make better and faster decisions and engage with their citizens. Proposed concept of smart city (smart region, smart country) management system would allow if implemented to make a breakthrough change, improve efficiency in the management and operation of a city or a region.

Intelligent vehicle network system and smart city management based on genetic algorithms and image perception

By using various Internet of Things technologies and communication technologies, smart cities can respond quickly and intelligently to various service requests of cities, thus realizing the intelligent operation and management of cities, strengthening the management of urban facilities and improving the quality of urban services. To improve the operational efficiency of smart car network systems and smart city management systems. In this paper, the authors analyse the intelligent vehicle network system and smart city management based on genetic algorithms and image perception. By using distributed and parallel computing, massive urban data can be quickly stored, processed and analyzed, useful information can be extracted, which can help smart cities make effective decisions and improve the efficiency of infrastructure and resources use. The simulation results show that the proposed coordination strategy can achieve the minimum energy consumption scheduling, thus maximizing the benefits of the data center, thus effectively improving the urban road traffic capacity and alleviating urban traffic congestion.

Performance Tests of Smart City IoT Data Repositories for Universal Linear Infrastructure Data and Graph Databases

The infrastructure managed by Smart City systems includes mainly linear structures, such as pipelines, electric power lines, railway lines, etc.. In this paper, we propose the transcription of linear infrastructure to graph representation and storing needed meta-data in a graph database, merged with the traditional relational database used for device management. Such an approach enables fast acquisition of data about infrastructure’s properties and allows merging information about the structure of the managed infrastructure with information devices’ properties and statistics. We develop a graph generator that generates virtual network basing on representative examples of linear infrastructure, incorporation of a data from existing metering systems with the generated structure, which automates the deployment and allows to evaluate the performance of Smart City monitoring and management system. We present results of performance tests that show and the creation time of graph database structures in Neo4j and the difference between the performance of the Microsoft SQL Server database and the Neo4j database in a few Smart City use cases. The results show that the use of the graph database to execute queries related to linear infrastructure allows decreasing the response time up to 9 times.

An Overview of Distributed Denial of Service Traffic Detection Approaches

The availability of information and communication (IC) resources is a growing problem caused by the increase in the number of users, IC services, and the capacity constraints. IC resources need to be available to legitimate users at the required time. The availability is of crucial importance in IC environments such as smart city, autonomous vehicle, or critical infrastructure management systems. In the mentioned and similar environments the unavailability of resources can also have negative consequences on people's safety. The distributed denial of service (DDoS) attacks and traffic that such attacks generate, represent a growing problem in the last decade. Their goal is to disable access to the resources for legitimate users. This paper analyses the trends of such traffic which indicates the importance of its detection methods research. The paper also provides an overview of the currently used approaches used in detection system and model development. Based on the analysis of the previous research, the disadvantages of the used approaches have been identified which opens the space and gives the direction for future research. Besides the mentioned this paper highlights a DDoS traffic generated through Internet of things (IoT) devices as an evolving threat that needs to be taken into consideration in the future studies.

The Smart City Ecological Construction Based on Big Data in FIOT Operation Model

With the acceleration of the construction pace of China's smart cities, the construction of smart city has made many achievements. But problems such as insufficient funds for system construction, lack of sustainable operation mode, and numerous isolated islands of information have become prominent. In order to improve and solve the above problems, we draw on the international BOT model and build on urban big data based on next-generation information technologies such as artificial intelligence, cloud computing and the Internet of Things. We study the sustainable operation mode of urban big data and innovatively propose a smart city ecological construction operation and management system based on the Financing-Integration-Operation-Transfer (FIOT) model and with government-led, enterprise-led and public participation. A reference model of "one model, five cores and two standards" is constructed for the ecological construction of smart cities to better serve the people and China's economic construction. A smart city brain will be formed to achieve rapid and sustainable development of China's urbanization. We hope to promote the protection of the environment by the people of the world and the rapid and sound development of the global economy.