Smart City Systems Research Articles

Hybrid Model of Machine Learning Refractory Data Prediction Based on IoT Smart Cities

With the advent of the digital age in recent years, the application of artificial intelligence in urban Internet of Things (IoT) systems has become increasingly important. The concept of smart cities has gradually formed, and smart firefighting under the smart city system has also become important. The method of machine learning is now applied in various fields, but seldom to the data prediction of smart firefighting. Various types of applications including data applications of machine learning algorithms in smart firefighting have yet to be explored. In this article, we propose using machine learning algorithms to predict building fire-resistance data, aiming to provide more theoretical and technical support for IoT smart cities. This article adopts the fire-resistance data of building beam components in a real fire environment, using three integrated machine learning algorithms, Extreme random Tree (ET), AdaBoost, and Gradient Boosting Machine (GBM), and the grey wolf optimization algorithm to optimize. We improve the grey wolf algorithm and combine the grey wolf algorithm with the machine learning model. The algorithm constitutes three machine learning hybrid models: GWO-ET, GWO-AdaBoost, and GWO-GBM. Compared with traditional grid tuning, particle swarm optimization (PSO), and genetic algorithm (GA) optimization, the robustness and accuracy of the three optimization algorithms and the machine learning hybrid algorithm on the data set are compared and analyzed. Performance is measured through various performance comparisons and experimental result comparisons. For various building beam component data sets under real fires, the optimization and comparison show that the mean square error (MSE) of the proposed algorithm is extremely small. The results indicate that the GWO machine learning hybrid model is superior to other models and has a smaller prediction error.

Net Zero Energy Districts: Connected Intelligence for Carbon-Neutral Cities

Net-Zero Energy Districts (NZEDs) are city districts in which the annual amount of CO2 emissions released is balanced by emissions removed from the atmosphere. NZEDs constitute a major component in a new generation of “smart-green cities”, which deploy both smart city technologies and renewable energy technologies. NZEDs promote environmental sustainability, contribute to cleaner environments and reduce global warming and the threats from climate change. This paper describes a model to assess the feasibility of the transition of city districts to self-sufficient NZEDs, based on locally produced renewable energy suitable for cities. It also aims to identify threshold conditions that allow for a city district to become a self-sufficient NZED using smart city systems, renewable energy, and nature-based solutions. The significance of transition to self-sufficient NZEDs is extremely important as it considerably decentralises and multiplies the efforts for carbon-neutral cities. The methodology we follow combines the literature review, model design, model feed with data, and many simulations to assess the outcome of the model in various climate, social, technology, and district settings. In the conclusion, we assess whether the transition to NZEDs with solar panel energy locally produced is feasible, we identify thresholds in terms of climate, population density, and solar conversion efficiency, and assess the compatibility of NZEDs with compact city planning principles.

End-to-end chiller fault diagnosis using fused attention mechanism and dynamic cross-entropy under imbalanced datasets

Fault diagnosis techniques play an increasingly important role in the operation and maintenance of smart city systems. Artificial intelligence improves the efficiency of chiller system fault diagnosis, and greatly reduces the energy consumption of urban buildings. The existing intelligent fault diagnosis methods of chiller mostly rely on balanced training datasets; lacking fault samples makes these methods incompetent to extract reliable features to recognize abnormal machine conditions, resulting in the degraded performance. To overcome the deficiencies of reported studies, a new method, called end-to-end chiller fault diagnosis, is proposed using a fused attention mechanism and dynamic cross-entropy. Firstly, a one-dimensional convolution network (1D-CNN) and long-short term memory (LSTM) are combined to capture the spatial-temporal features from the original data directly. Afterwards, a fused attention mechanism is developed to further refine the extracted features to increase the contribution of crucial features and achieve high-quality diagnostic information mining. Finally, the dynamic cross-entropy (DCE) is designed for updating the imbalance factor in real-time, with more focus on the hard-classified types. The experimental analysis results demonstrate the feasibility and superiority of the proposed method in identifying chiller system faults with imbalanced datasets.

Integrating Embedded Multiagent Systems with Urban Simulation Tools and IoT Applications

The smart city systems development connected to the Internet of Things (IoT) has been the goal of several works in the multi-agent system field. Nevertheless, just a few projects demonstrate how to deploy and make the connection among the employed systems. This paper proposes an approach towards the integration of a MAS through the JaCaMo framework plus an Urban Simulation Tool (SUMO), IoT applications (Node-RED, InfluxDB, and Grafana), and an IoT platform (Konker). The integration presented in this paper applies in a Smart Parking scenario with real features, where is shown the integration and the connection through all layers, from agent level to artifacts, including real environment and simulation, as well as IoT applications. In future works, we intend to establish a methodology that shows how to properly integrate these different applications regardless of the scenario and the used tools.

Investigation of The Sufficiency of Antalya Parks

Urban green spaces are areas established to meet the recreational needs of urban people. Although green spaces vary from country to country and region in terms of plan and design features, they were basically created to allow people to meet with nature. Parks are the basic components of urban landscapes that provide environmental and social functional value. Urban parks, in particular, provide spaces for outdoor physical activities. In order to take advantage of the opportunities of activities in the parks, users must have convenient access to these resources. One of the most important aspects for researching the use and potential benefits of urban green spaces is the assessment of their geographic accessibility. The widespread use of smart city systems and the gradual expansion of their usage areas increase the importance of spatial analysis. Spatial analyses are used in today’s urban management in the processes of determining social needs, identifying current problems, and putting forward solutions. When spatial analyses are used together with GIS, the field of application develops even more, and it supports local governments in responding to the changing demands of the society for a better life. In the study, the adequacy and accessibility of 160 city parks in Konyaaltı District of Antalya Province were examined. In terms of the adequacy of the parks, the area value of 10 m2 per person determined with the Construction Plan numbered 3194 was taken as basis. In terms of accessibility, distance values of 200, 400, 800, 1,200 meters were examined. Neighborhood boundaries and population information were obtained from the relevant units, and Arc-GIS software was used in the analysis. It was determined that the parks in Konyaaltı district were insufficient in terms of adequacy and accessibility. Finally, suggestions were made in terms of increasing the adequacy of the parks and ensuring accessibility.

Toward an Ontological Cyberattack Framework to Secure Smart Cities with Machine Learning Support

With the emergence and the movement toward the Internet of Things (IoT), one of the most significant applications that have gained a great deal of concern is smart cities. In smart cities, IoT is leveraged to manage life and services within a minimal, or even no, human intervention. IoT paradigm has created opportunities for a wide variety of cyberattacks to threaten systems and users. Many challenges have been faced in order to encounter IoT cyberattacks, such as the diversity of attacks and the frequent appearance of new attacks. This raises the need for a general and uniform representation of cyberattacks. Ontology proposed in this paper can be used to develop a generalized framework, and to provide a comprehensive study of potential cyberattacks in a smart city system. Ontology can serve in building this intended general framework by developing a description and a knowledge base for cyberattacks as a set of concepts and relation between them. In this article we have proposed an ontology to describe cyberattacks, we have identified the benefits of such ontology, and discussed a case study to show how we can we utilize the proposed ontology to implement a simple intrusion detection system with the assistance of Machine Learning (ML). The ontology is implemented using protégé ontology editor and framework, WEKA is utilized as well to construct the inference rules of the proposed ontology. Results show that intrusion detection system developed using the ontology has shown a good performance in revealing the occurrence of different cyber-attacks, accuracy has reached 97% in detecting cyber-attacks in a smart city system.

IoT-based smart parking system in smart city

IoT-based smart parking system in smart city

Towards intelligent public transport systems in Smart Cities; Collaborative decisions to be made

The global context of cooperative intelligent public transport systems (C-ITS) in Smart Cities calls for a solution that integrates the perspectives of the travelers, public administration, vehicle manufacturers and transport operators in the joint effort of standardization, interconnection and assimilation of emerging technologies to meet operational, safety and environmental objectives at metropolitan, national or international level. The article proposes a definition for the capabilities maturity levels of the mobility ecosystem, and functional architecture for the collaborative decision-making system for implementing the C-ITS in the future Smart Cities. The paper contributes to the literature and practice in four manners. The first one is enhancing the awareness and understanding of maturity capability model (CMM) for all the stakeholders throughout the mobility ecosystem, emphasizing the key capabilities required for each maturity level. The second way is manifested throughout public and private companies acting on the same territory in the mobility ecosystem assess the existing capabilities and collaborate for achieving a superior maturity level of mobility processes, stable and repeatable results. In addition, the third one, based on CMM, is that governments regulate, conduct and control, establishing a stable and mature processes institutionalization for C-ITS. Finally, the fourth practice is defining a C-ITS functional architecture for the future Smart Cities to support collaborative decision-making applied for public transport implementation in big Smart Cities with the final objective of increasing the citizen’s quality of life.

IoT-based smart parking system in smart city

IoT-based smart parking system in smart city

A Survey of Emergencies Management Systems in Smart Cities

The rapid urbanization process in the last hundred of years has deeply changed the way we live and interact with each other. As most people now live in urban areas, cities are experiencing growing demands for more efficient and sustainable public services that may improve the perceived quality of life, specially with the anticipated impacts of climatic changes. In this already complex scenario with increasingly overcrowded urban areas, different types of emergency situations may happen anywhere and anytime, with unpredictable costs in human lives and properties damages. In order to cope with often unexpected and potentially dangerous emergencies, smart cities initiatives have been developed in different cities, addressing multiple aspects of emergencies detection, alerting, and mitigation. In this scenario, this article surveys recent smart city solutions for crisis management, proposing definitions for emergencies-oriented systems and classifying them according to the employed technologies and provided services. Additionally, recent developments in the domains of Internet of Things, Artificial Intelligence and Big Data are also highlighted when associated to the management of urban emergencies, potentially paving the way for new developments while classifying and organizing them according to different criteria. Finally, open research challenges will be identified, indicating promising trends and research directions for the coming years.

Vibration Energy Harvester with Double Frequency-Up Conversion Mechanism for Self-Powered Sensing System in Smart City

Vibration Energy Harvester with Double Frequency-Up Conversion Mechanism for Self-Powered Sensing System in Smart City

Cyber-Physical Systems Enabled Transport Networks in Smart Cities: Challenges and Enabling Technologies of the New Mobility Era

Wireless communication technologies, smart sensors, enormously enhanced computational capabilities, intelligent controls merge to form Cyber-Physical Systems (CPSs). The synergy achieved due to this integration will considerably transform how humans’ interaction with engineered systems in future smart cities. Such cities will leverage technologies to design, develop, and implement intelligent solutions to provide inclusive development, efficient community infrastructure, and a clean and sustainable environment. One of the domains likely to witness paradigm- shift in future smart cities is transport. The development of urban structures, functionality, and prosperity are intricately connected to how the city designs its mobility infrastructure. Shortly, all vehicles and roadside infrastructures in a city-wide ITS will be enabled with integrated smart sensors, edge computing devices and communication units to provide diversified and inclusive services to its residents. Nonetheless, due to the high heterogeneity and complexity of cross-cutting aspects of CPS, the transportation domain is susceptible to cyber vulnerabilities, threats, illegal access, cyber-attacks, unauthorized information sharing, and so on. This paper attempts to understand smart CPS-enabled transportation systems, it’s conceptual framework, the connected and automated vehicles and other associated technologies and communication networks. Finally, we present the expected demands of the transportation domain in a future smart city and the capabilities of CPS in a demand-supply framework. However, the major intellectual challenge lies in effectively designing-developing-deploying models and algorithms to harness the powers of the integrated TCPS system implemented in the intended environment.

An Intelligent Security Framework Based on Collaborative Mutual Authentication Model for Smart City Networks

With the advent of smart city networks and increased utilization of vehicles, the Internet of Vehicles (IoV) has attracted more attention from researchers. But, providing security to this type of network is one of the challenging and demanding tasks in the present day. For this purpose, the conventional works developed many networking frameworks and methodologies to enhance the privacy and security of smart city systems. Still, it has the significant limitations of high complexity in algorithm design, requires more time consumption for processing, reduced maintenance, and does not require proper authentication verification. Therefore, the primary purpose of this work is to develop a new security model for smart city networks using a combination of methodologies. Here, the Collaborative Mutual Authentication (CMA) mechanism is used to validate the identity of users based on the private key, public key, session key, and generated hash function. In addition, the Meta-heuristic Genetic Algorithm – Random Forest (MGA-RF) technique is deployed to detect the attacks in the network, ensuring the security of the smart city. During an evaluation, the proposed authentication-based security mechanism’s performance is validated using various parameters, and the results are compared with the recent state-of-the-art models.

Three-way Naive Bayesian collaborative filtering recommendation model for smart city

Smart city construction has penetrated all aspects of human life. People can continue to feel the convenience of life brought by new technologies and new services. In order to further optimize the smart city system, aiming at the sparsity of scoring data and the difficulty of two-way decisions to deal with uncertain decisions in the recommendation algorithm, a three-way Naive Bayesian Collaborative Filtering Recommendation model (3NBCFR) for smart city is constructed by integrating Naive Bayesian, three-way decisions and collaborative filtering algorithm. Firstly, we consider the influence of item attributes on user scoring. Naive Bayesian classifier is used to score unrated items, which can effectively fill in the missing values in the score matrix and solve the problem of data sparsity. Secondly, to ensure sustainable recommendations for uncertain goals, the three-way decisions is introduced into the collaborative filtering recommendation system, three-way recommendation rules are formulated, and 3NBCFR is constructed. Finally, the model is applied to the movie recommendation system. The experiment on Movielens shows that compared with the traditional collaborative filtering recommendation algorithm, 3NBCFR algorithm reduces the recommendation cost and improves the recommendation quality. At the same time, it lays a foundation for promoting the construction of smart city.

Formal Verification of CHAP PPP authentication Protocol for Smart City/Safe City Applications.

A smart city is a technologically advanced metropolitan region with several connected devices that collects data using various electronic technologies, voice activation methods, and sensors. The information obtained from the data is utilised to efficiently manage assets, resources, and services; in turn, the data is used to enhance operations throughout the city. Achieving security for smart cities is one of the major challenges as the number of connected devices increases the vulnerability also increases. The security of a smart city system depends on the reliability of the security protocols used by the security systems. To design and develop a highly secure system for a smart city the security protocols used must be highly reliable. To prove the reliability of a security protocol the validation technique is not desirable because of its several drawbacks, these drawbacks can be overcome using the formal verification technique which provides the mathematical proof for its correctness. In this work, The Challenge-Handshake Authentication Protocol Point-to-Point (CHAP PPP) which is more commonly used in PPP authentication of smart cities is formally verified using the well-known verification technique known as the model checking technique. The Scyther model checker is the tool used to build the abstract security protocol model.

Assessment of the risks of losing investments aimed at the development of Smart city systems

The article proposes a model for the computational core of the decision support system (DSS) in assessing the risks of investment loss during the dynamic planning (DP) of Smart City development. In contrast to the existing solutions, the proposed model provides specific recommendations when assessing the risks of loss. In case of an unsatisfactory risk forecast, it is possible to flexibly adjust the parameters of the investment process in order for the parties to achieve an acceptable financial result. The scientific novelty of the results is that for the first time it is proposed to apply a new class of bilinear multistep games. This class allowed us to adequately describe the process of assessing the risks of investment loss, using the example of dynamic planning for the placement of financial resources of players in Smart City projects. A distinctive feature of the considered approach is the use of tools based on the solution of a bilinear multistep game of both quality with several terminal surfaces, and a game of degree solved in the class of mixed strategies. Computational experiments were carried out in the Maple mathematical modeling package, and a DSS was developed in which a risk assessment model was implemented. The developed DSS allows to reduce the discrepancies between the data for predicting the risks of investment loss during the Smart City DP and the real return on investment.

Coordinating energy management systems in smart cities with electric vehicles

The rapid proliferation of Electric Vehicles (EVs) creates an inherent link between the previously independent transport and power sectors. This is especially relevant in the smart cities paradigm, which focuses on optimizing resource management using modern software tools and communication infrastructures. The optimal management of energy resources is of key importance, and with mobile EVs playing a pivotal role in smart city power flows, the coordination of energy management systems (EMSs) at their parking locations can bear global benefits. In this study the coordination between home energy management systems (HEMSs) and EV parking lot management systems (PLEMS) is proposed, modeled, and simulated, as a new contribution to earlier studies. The EMSs coordinate through partially sharing individual EV schedules and without sharing private information. Missing information is completed through public cloud repositories and services. The HEMS and PLEMS are implemented using mixed-integer linear programming (MILP). The proposed coordination framework is computationally implemented and simulated based on a real-life case study. The results show that the proposed EMS coordination framework is both technically beneficial for power grids and economically beneficial for EV owners.

Optimal operation and simultaneous analysis of the electric transport systems and distributed energy resources in the smart city

Today due to population growth as well as air pollution and lack of energy many countries are motivated to use technology to provide services and solve city problems. The idea of a smart city allows to interact directly with urban infrastructure and monitoring whatever that happens and is in progress. A smart city is a city, based on information and communication technology. In this paper, optimal operation of electrical transportation system and energy distribution resources has been studied. The major energy consumption systems in a smart city are electrical transportation systems such as Electric Vehicles in power systems and Electric Railway systems. Analyses the interaction of an interconnected systems using a linear model for co-optimization planning and operation of subway system. For optimal operation of the smart city, an optimization problem that minimizes the total cost of all the energy systems and maximizes the Regenerative Braking energy to recover subway is solved. In this paper, considering the electric vehicles such as vehicle to Grid and Subway technology located in the special depot, the traffic and length of the routes are modeled. Based on degradation model has been presented to rise battery life of Electric vehicles. Also, a machine learning technique based on the long short-term memory (LSTM) is used to forecast the hourly solar radiation and wind speed. To depict the uncertain behavior of electric vehicles, electric transportation system and loads in smart city, Point Estimate Method, as a stochastic framework is suggested. All in all, using uncertainty and deterministic method the proposed model is analyzed.

Improve Security in Smart Cities Based on IoT, Solve Cyber Electronic Attacks with Technology by using Packet Tracer

Smart cities are expected to significantly improve people's quality of life, promote sustainable development, and enhance the efficiency of operations. With the implementation of many smart devices, c problems have become a serious challenge that needs strong treatments, especially the cyber-attack, which most countries suffer from it. My study focuses on the security of smart city systems, which include equipment like air conditioning, alarm systems, lighting, and doors. Some of the difficulties that arise daily may be found in the garage. This research aims to come up with a simulation of smart devices that can be and reduce cyber attach. Use of Cisco Packet tracer Features Simulated smart home and c devices are monitored. Simulation results show that smart objects can be connected to the home portal and objects can be successfullymonitored which leads to the idea of real-life implementation and see. In my research make manysolutions for attachingissues,which was great, and apply some wirelessprotocol.

Reinventing Smart Water Management System through ICT and IoT Driven Solution for Smart Cities

Purpose: Worldwide water scarcity is one of the major problems to deal with. Smart Cities also faces this challenging problem due to its ever-increasing population and limited sources of natural water. Additionally, careless usage of water and large water wastage has made the water issues as a serious concern. Today Smart Cities are using advanced technical solutions to deal with various problems, to deal with water shortage problems, Smart Cities uses Smart Water Management System, an intelligent system which distributes and control existing water supply on need basis, and also it facilitates recycling of water for again using for specific activities. In this paper I have provided the overview of Smart Water Management System, its features, and functionalities. I also reviewed available literature on Water Management Systems for Smart Cities and considering the latest tools and technologies and understanding some of the limitations of existing Smart Water Management Systems, I proposed an easy to develop, operate and maintain Smart Water Management Solution called as "iWMS". The proposed conceptual framework of iWMS is modular and is based on secure Blockchain based Application Layer. The iWMS solution supports entire water management and recycling functioning cycle and can easily integrate with other services of Smart Cities. The evaluation of iWMS framework provided very encouraging results. It is revealed that iWMS meets the stated objectives of water savings through automated operation and also through controlled water recycling. Unlike other Smart Water Management Systems, iWMS also carefully complies the cybersecurity requirements. Based on evaluation, the advantages, and limitations of iWMS are also stated in this paper. Finally, I have also specified the future plans about iWMS to undertake its full-fledged implementation and addressing of its limitations. Design/Methodology/Approach: Primary Data collection through Interviews and Questionnaire responses from Industry Professionals, SMEs, and Researchers working on development, operation, and maintenance of Water Management Systems in Smart Cities and secondary data collected through detailed review of existing literature containing Journal Papers, Conference Papers, and Whitepapers available on Water Management Solutions for Smart Cities, are used to derive the new findings and results presented in this research paper. Findings/Result: Smart Water Management System not only efficiently handles water distribution across Smart Cities but also plays an active role in Water Recycling, Water Control and Monitoring, Estimation of the peak water requirements, and detection of water leakage if any. Smart Water Management System is an essential system in Smart Cities and is the backbone behind Smart Water Service of Smart Cities. Originality/Value: The Information presented in this paper is original and genuine and completely based on own data analysis and findings. It is derived from a systematic literature review of existing research papers and whitepapers on Smart Water Management System and interactions carried out with industry professionals, SMEs, and Researchers working on Water Management Solutions. Paper Type: Technology oriented Research