Smart City Components Research Articles

BEMPAS: A Decentralized Employee Performance Assessment System Based on Blockchain for Smart City Governance

In recent years, the use of blockchain has gained attention in industrial interventions and research. Blockchain technologies can be particularly utilized in the domain of Smart Governance, which is a critical component of Smart Cities. Smart Governance aims to ensure smarter decision making, openness and collaborative participation of all entities involved as well as help minimize resource usage, reduce consumption and save cost. Smart Governance involves putting in place systems for monitoring and evaluating the performance of government workers. However, government workers lack trust in these systems because they are mostly centralized systems which are prone to single-point of failure problems and also data fed into these systems can be tampered with by the higher-ups or employers to favour individual workers. With these problems, there is a need for a decentralized system that can ensure trust, tamper-resistance, accountability, reliability, transparency and security. In this paper, we propose a decentralized employee evaluation system based on blockchain. We utilized a 3-chain model, namely; ID-Chain, Behavior Chain and Credit Chain fused to make a single unified chain. Our system also makes use of an automated game-based employee evaluation approach. Our system is based on Hyperledger Fabric as the blockchain platform and operating mechanism. Our Proof of Concept (PoC) results shows that in utilizing the Blockchain system, security concerns such as trust, privacy, accountability, among others, that are present in current employee performance evaluation systems are tackled and also in the adoption of the game-based automated system, our system can make an effective decision regarding employee performance. Our system achieves trust, transparency, security and accountability among government workers under a Smart City governing environment.

Novel Multi Center and Threshold Ternary Pattern Based Method for Disease Detection Method Using Voice

Smart health is one of the most popular and important components of smart cities. It is a relatively new context-aware healthcare paradigm influenced by several fields of expertise, such as medical informatics, communications and electronics, bioengineering, ethics, to name a few. Smart health is used to improve healthcare by providing many services such as patient monitoring, early diagnosis of disease and so on. The artificial neural network (ANN), support vector machine (SVM) and deep learning models, especially the convolutional neural network (CNN), are the most commonly used machine learning approaches where they proved to be performance in most cases. Voice disorders are rapidly spreading especially with the development of medical diagnostic systems, although they are often underestimated. Smart health systems can be an easy and fast support to voice pathology detection. The identification of an algorithm that discriminates between pathological and healthy voices with more accuracy is needed to obtain a smart and precise mobile health system. The main contribution of this paper consists of proposing a multiclass-pathologic voice classification using a novel multileveled textural feature extraction with iterative feature selector. Our approach is a simple and efficient voice-based algorithm in which a multi-center and multi threshold based ternary pattern is used (MCMTTP). A more compact multileveled features are then obtained by sample-based discretization techniques and Neighborhood Component Analysis (NCA) is applied to select features iteratively. These features are finally integrated with MCMTTP to achieve an accurate voice-based features detection. Experimental results of six classifiers with three diagnostic diseases (frontal resection, cordectomy and spastic dysphonia) show that the fused features are more suitable for describing voice-based disease detection.

Smart cities development in India

The Smart Cities Mission launched in 2015 is to provide Indian cities with core infrastructure and enable a decent quality of life to its citizens. Building clean, green and sustainable environment along with the application of Smart Solutions to the cities is a major objective of this ongoing mission. One of the underlying principles of developing Smart cities is to make these cities inclusive for all- especially abled, elderly, the poor and the disadvantaged. This paper discusses the major components of Smart cities and the various technology led practises that are envisioned to be adopted. Application of ‘Smart solutions’ will enable cities to use technology, information and data to improve infrastructure and services. Comprehensive development in this way will improve quality of life, create employment and enhance incomes for all, especially the poor and the disadvantaged, leading to inclusive cities.

An optimization model for renting public parking slots to carsharing services

Smart mobility systems represent a new generation of transport systems that are strongly supported by information and communications technologies, allowing a continuous connection between the system administrators, the customers/users, the transport infrastructures and the vehicles. A major example of these systems is represented by carsharing. Carsharing can relieve people from the costly and non-sustainable burden of owning a car, especially when residing in a city. Furthermore, it can reduce pollution and traffic congestion and has been worldwide recognized as a fundamental component of smart cities by policy-makers In this study, we provide an overview of relevant regulations for carsharing, highlighting in particular the importance of parking policies. Given this importance, we propose a mathematical optimization model that can be used by a local government to analytically choose the best subset of parking slots to rent to carsharing companies, in order to improve urban mobility. We test the model on realistic data of the city of Rome, showing that we can obtain a fair territorial distribution of the parking slots that satisfies population needs. The data were defined on the basis of our collaboration with professionals of the electric utility company Enel within E-Go Car Sharing, an electrical vehicle carsharing service established at the University Roma Tre.

Frame Construction and Task Analysis of Smart Energy in the Construction of Smart City

Smart energy is the foundation and important component of smart cities, and it is the source of energy that guarantees the efficient and reliable operation of each subsystem of the city. Based on the practical experience in the exploration of the construction of smart energy at home and abroad, and the goal of achieving “three transformations and one center”, the basic principles of the frame construction as well as display construction and physical construction of smart energy have been proposed. Four main tasks of the construction of smart energy have been discussed: infrastructure, energy supply, energy consumption, and management services.

MULTI VEHICLE SPEED DETECTION USING EUCLIDEAN DISTANCE BASED ON VIDEO PROCESSING

One component of smart city is smart transportation, known as Intelligent Transportation Systems (ITS). In this study, we discuss the estimation of moving vehicle speed based on video processing using the Euclidean Distance method. In this study, we examine the effect of camera angles on the video acquisition to speed estimation accuracy. In addition, Region of Interest (ROI) will be designed into three parts to determine which area is the most appropriate to be chosen, so that the estimated vehicle speed will be better. These approaches have never been studied by previous researchers. The separation between the background and foreground is conducted using Gaussian Mixture Models method. By comparing the displacement distance and the number of frames per second (fps), we obtain speed estimate for each vehicle. According to the experimental results, our system can estimate the speed of the vehicle with an accuracy of 99.38%.

Usability of QR code in the design of Information system for recognizing historic buildings, Kota Lama, Semarang

Urban infrastructure or basic facilities such as museum is essential as the component of smart city. To support a natural museum for instances the exhibit of historical building in “Kota Lama Semarang “or The old city of Semarang, this paper used the QR code to recognising the information on the historical buildings, Kota Lama, Semarang. Leaflet map of Semarang Historic building commonly used to provide the location information. However, leaflet map has a limitations, it cannot provide enough information about the historic building. The limitations of leaflet maps is only provide little information which explaining the condition of the historic building. To expand the information about the historical building, prior research suggested the use of web technologies. However, some people suggested the usage of leaflet – map which can show the location and the web site can provide more additional information about the historical building. In this paper, the researcher purpose a design of Information System, which employs Quick Response (QR) code technologies as a link to combine the information between leaflet map and web technologies. Then, the design validated with identify the usability of design for using QR code for recognising historic building, Kota Lama, Semarang. The method that used to evaluate the design is SUS (System Usability Scale). The QR code usability test using SUS question showed the number that the design is in level usable from the user perspective.

Concept of implementing Big data in smart city: Applications, Services, Data Security in accordance with Internet of Things and AI

Smart cities are the current buzz phrase between infrastructure developments. With a gradually increasing inflow on populations into cities then a continuously thriving necessity to better deal with resources, countless cities kind of San Francisco, united states, Singapore, Portugal, England is experimenting together with upcoming state-of-the-art technologies after fulfill their cities smarter. Among these current trending technologies is the Internet of Things (IoT), Big Data and Artificial Intelligence (AI) which has revolutionized the way we analyze patterns yet traits between human behaviors. With Big Data, current fragmented and remoted data sets do stand well-acquainted beside an overarching point of view in accordance with provide high quality solutions in accordance with frequent issues up to expectation have an effect on rapidly growing cities today. Here are 5 ways within which Big Data could show fundamental in smart cities about the future. A lot of governments are thinking about adopting the smart city thought between theirs urban areas at that point executing impressive records services up to expectation assist smart city components in accordance with attain the required stage concerning supportability and improve the living norms. Smart cities take advantage of more than one technology in conformity with get better the concert about healthiness, transportation, power, education, and cloud applications lead after greater stages about remedy about their citizens. In addition, it attempts in accordance with pick out the necessities as assist the implementation on substantial data purposes for smart city services. The criticism displays as numerous possibilities are accessible because of making use of big data in smart cities; conversely, so are nevertheless various concerns and disputes in conformity with stay addressed to attain higher utilization about this technology.

IoT Based Smart Lighting System using PIR Sensors, Arduino Uno and Thingspeakcloud + Chat Bot and Dashboard to Monitor Home Remotely

As described in paper [1], I have mentioned solution to smart lighting and security using arduinouno microprocessor, Wi-Fi module and PIR Sensor.In this era, we all are fully de-pendent on electricity which is non-renewable resource. We must require some solution to save electricity and use electricity wisely. Lighting system is one of the major key component of smart cities or developing cities. Even we need to constantly monitor electrici-ty usage of our home remotely when we are not available at our home. With the development of new technologies like IOT, sen-sors etc., automation of electricity is easy and it plays very im-portant role in saving electricity. The purpose of this project is to save and monitor your home lights using IOT and other technol-ogies. Here we propose IOT and cloud based smart lighting sys-tem and bot+dashboard to monitor you home electricity very efficiently. When the person/persons in your home enters par-ticular area, the load will be activated and when they leave par-ticular area load will be deactivated of that area and this data is also sent to cloud to monitor your home.

Physical Layer Security for the Smart Grid: Vulnerabilities, Threats, and Countermeasures

Smart energy systems are becoming an important component of smart cities. The wide adoption of existing computing technologies and communication standards by a smart energy system exposes it to the plethora of threats that exist in cyberspace. In this article, we investigate the vulnerabilities and threats associated with smart energy system components, including Internet of Things enabled devices, as well as relevant communication standards, and we discuss countermeasures against adversarial attacks. We found that the existing literature has reported various attacks, including modification, denial-of-service, malware, and message replay, which can cause malfunctioning of different components of a smart energy system. In addition, we propose a framework for securing the physical layer of the smart energy system. The framework is based on advanced key generation, machine learning, and physical layer security techniques, which enhance the security of smart energy systems across different applications.

Are Smart Innovation Ecosystems Really Seeking to Meet Citizens’ Needs? Insights from the Stakeholders’ Vision on Smart City Strategy Implementation

The concept of a smart city is becoming the leading paradigm worldwide. Consequently, a creative mix of emerging technologies and open innovation is gradually becoming the defining element of smart city evolution, changing the ways in which city administrators are organizing their services and development globally. Thus, the smart city concept is becoming extremely relevant on the agendas of policy-makers as a development strategy for enhancing the quality of life of the citizen and improving the sustainability goals of their cities. Despite of the relevance of the topic, still few studies investigate how open innovation shapes the way cities become smarter or focus on the experiences of professionals to understand the concept of a smart city and its implementation. This paper fills this gap and analyzes the processes for building effective smart cities by integrating the different perspectives of smart innovations and using the core components of smart cities according to a conceptual framework developed in previous research. In so doing, it provides useful insights for smart city stakeholders in adopting social and technological innovation to improve the global competitiveness of their cities. The empirical dataset allows examining how “smart cities” are being implemented in Manchester (UK), and in Boston, Massachusetts, and San Diego City (United States of America (USA)), including archival data and in-depth interviews with core smart city stakeholders who are involved in smart city projects and programs across the cases. Results from empirical data suggest that the conceptualization of smart cities across the cases is similar with a strong emphasis on social and technological innovation aimed at addressing municipal challenges in the core sub-systems of the cities, which include mobility, environmental sustainability, entrepreneurial development, quality of life, and social cohesion. The results also reveal benefits and challenges relating to smart innovation ecosystems across the cases and the future directions of their diffusion.

University Campuses as a Test Field in the Context of “Smart Citizen” as a Component of Smart City

Bu makalenin amacı, kurulum maliyetleri yüksek olan akıllı kent projelerinde pilot uygulama gerçekleştirmenin önemini vurgulamak ve akıllı kentin bileşenlerinden birisi olan “akıllı vatandaş” bileşeni temelinde pilot projeler için üniversite kampüslerinin iyi bir uygulama alanı olabileceğini göstermektir. Bu amaca ulaşmak için ilk olarak toplum ve teknoloji ilişkisi gözetilerek sosyolojik bir analiz olan “kuşaksal farklılıklara” değinilmiş ve üniversitelerin kent ve toplumla olan ilişkisi incelenmiştir. Daha sonra üniversite kampüslerinin akıllı kent projelerinin test edilmesi ve topluma tanıtılması noktasında sahip olduğu avantaj ve dezavantajlar değerlendirilmiştir. Bisiklet ve araç paylaşımı gibi akıllı hareketlik önlemlerinin uygulanması ve akıllı kent kültürünün oluşturulması için en ideal yerlerden birisinin gençlerin hareketlilik sahası halindeki üniversite kampüsleri olduğu sonucuna varılmıştır.

Deep Learning for Reliable Mobile Edge Analytics in Intelligent Transportation Systems: An Overview

Intelligent transportation systems (ITSs) will be a major component of tomorrow's smart cities. However, realizing the true potential of ITSs requires ultralow latency and reliable data analytics solutions that combine, in real time, a heterogeneous mix of data stemming from the ITS network and its environment. Such data analytics capabilities cannot be provided by conventional cloud-centric data processing techniques whose communication and computing latency can be high. Instead, edge-centric solutions that are tailored to the unique ITS environment must be developed. In this article, an edge analytics architecture for ITSs is introduced in which data is processed at the vehicle or roadside smart sensor level to overcome the ITS's latency and reliability challenges. With a higher capability of passengers' mobile devices and intravehicle processors, such a distributed edge computing architecture leverages deep-learning techniques for reliable mobile sensing in ITSs. In this context, the ITS mobile edge analytics challenges pertaining to heterogeneous data, autonomous control, vehicular platoon control, and cyberphysical security are investigated. Then, different deep-learning solutions for such challenges are revealed. The discussed deep-learning solutions enable ITS edge analytics by endowing the ITS devices with powerful computer vision and signal processing functions. Preliminary results show that the introduced edge analytics architecture, coupled with the power of deep-learning algorithms, provides a reliable, secure, and truly smart transportation environment.

Edge Computing-Based Security Framework for Big Data Analytics in VANETs

With the exponential growth of technologies such as IoT, edge computing, and 5G, a tremendous amount of structured and unstructured data is being generated from different applications in the smart citiy environment in recent years. Thus, there is a need to develop sophisticated techniques that can efficiently process such huge volumes of data. One of the important components of smart cities, ITS, has led to many applications, including surveillance, infotainment, real-time traffic monitoring, and so on. However, its security, performance, and availability are major concerns facing the research community. The existing solutions, such as cellular networks, RSUs, and mobile cloud computing, are far from perfect because these are highly dependent on centralized architecture and bear the cost of additional infrastructure deployment. Also, the conventional methods of data processing are not capable of handling dynamic and scalable data efficiently. To mitigate these issues, this article proposes an advanced vehicular communication technique where RSUs are proposed to be replaced by edge computing platforms. Then secure V2V and V2E communication is designed using the Quotient filter, a probabilistic data structure. In summary, a smart security framework for VANETs equipped with edge computing nodes and 5G technology has been designed to enhance the capabilities of communication and computation in the modern smart city environment. It has been experimentally demonstrated that use of edge nodes as an intermediate interface between vehicle and cloud reduces access latency and avoids congestion in the backbone network, which allows quick decisions to be made based on the traffic scenario in the geographical location of the vehicles. The proposed scheme outperforms the conventional vehicular models by providing an energy-efficient secure system with minimum delay.

On Bikes in Smart Cities

In this paper, we discuss data models and data mining for bicycles in Smart Cities. Mobility issues (or Smart Mobility) are one of the main components of Smart Cities. Bicycles, as a transport component in the cities, are on the rise all over the world. At least, it is true for all areas where the climate even minimally allows it. The reasons are quite obvious. This is democratic and accessible this type of transport, it is cheap and environmental friendliness. Of course, the promotion of a healthy lifestyle also plays its role. The development of this type of transport (like any other) has many different aspects. In this paper, we dwell on the issues of tracking the movement of cyclists and planning bike-sharing systems. All this information will serve as a set of metrics for any design in Smart Cities.

LiDAR-Enhanced Connected Infrastructures Sensing and Broadcasting High-Resolution Traffic Information Serving Smart Cities

Connected-vehicle system is an important component of smart cities. The complete benefits of connected-vehicle technologies need the real-time information of all vehicles and other road users. However, the existing connected-vehicle deployments obtain the real-time status of connected vehicles, but without knowing the unconnected traffic since there are still many unconnected vehicles and pedestrians on the roads. Therefore, it is urgent to find an approach to collect the high-resolution real-time status of unconnected road users. When it is difficult for all vehicles, pedestrians, and bicyclists to broadcast their real-time status in the near future, enhancing the traffic infrastructures to actively sense and broadcast each road user's status is an intuitive solution to fill the data gap. This paper introduces a new-generation LiDAR-enhanced connected infrastructures that can actively sense the high-resolution status of surrounding traffic participants with roadside LiDAR sensors and broadcast connected-vehicle messages through DSRC roadside units. The system architecture, the LiDAR data processing procedure, the data communication, and the first pilot implementation at an intersection in Reno, Nevada are included in this paper. This research is the start of the new-generation connected infrastructures serving connected/autonomous vehicles with the roadside LiDAR sensors. It will accelerate the deployment of the connected network for the smart cities to improve traffic safety, mobility, and fuel efficiency.

Perceived Importance of Smart and Sustainable Building Features from the Users’ Perspective

Smart and sustainable buildings have been designed, built and utilized in order to consume less energy, facilitate efficient building operation, and improve the comfort, health and productivity of users. Hence, they become a critical component of smart cities. Nonetheless, perceived importance rankings of different features of smart and sustainable buildings have yet to be identified and prioritized from the users’ perspective. Based on responses from 494 building users in Hong Kong, it was found that building users tended to focus more on intelligent security systems, followed by intelligent and responsive fresh air supply and lifts and escalators. On the other hand, building users generally considered the systems that monitor people’s movement and harvest rain water to be the least important features. Exploratory factor analyses were used to identify key factors of perceived smartness and sustainability of a building. The results of factor analyses showed that different user groups would characterize a building’s smartness differently.

Intelligent transport as a key component of implementation the sustainable development concept in smart cities

European societies today face many sustainability challenges including but not limited to youth unemployment, aging populations, climate change, pollution, sustainable energy and migration. These problems are especially evident in cities. The objectives of smart development and integrated planning in European cities have been presented in the Europe 2020 strategy. It assumes restoration of European cities through stimulating innovation. In the socio-economic dimension, this means supporting the development of intelligent cities, often referred to as Smart Cities. According to the Smart City definition it is a city with the ability to adapt to the changing socio-economic conditions. This feature is extremely important in times of constant change. Progressing urbanization, globalization, technology transfer to everyday life and dwindling natural capital are the reasons why urban development is increasingly dependent on such factors as advanced technologies or territorial capital, understood as the available material and immaterial resources that determine the functioning of a given area. One of the Smart City components is intelligent transport. Improving mobility, ensuring accessibility and decreasing traffic congestion are some of the greatest challenges facing smart cities today. To respond to these challenges many city planners are glancing at smart transport solutions to reduce congestion as well as to optimize the use of city public transport. The aim of this article is to identify the challenges faced by European cities nowadays, present transport as a component of the Smart City and show its role in implementing the Smart City concept. The author presents European actions in terms of city mobility and recognizes their role in attaining the 11th SDG. Particular attention is paid to cities of the new Member States. Some examples of activities undertaken and tools used by authorities of European cities will be cited as examples of good practices. An analysis of the conditions for the transferability of such a solution will be included in the article.

A stochastic multi-agent system for Internet of Things-enabled waste management in smart cities.

The population of the Earth is moving towards urban areas forming smart cities (SCs). Waste management is a component of SCs. We consider a SC which contains a distribution of waste bins and a distribution of waste trucks located in the SC sectors. Bins and trucks are enabled with Internet of Things (IoT) sensors and actuators. Prior approaches focus mainly on the dynamic scheduling and routing issues emerging from IoT-enabled waste management. However, less research has been done in the area of the stochastic reassignment process during the four seasons of the year over a period of two years. In this paper we aim to stochastically reassign trucks to collect waste from bins through time. We treat this problem with a multi-agent system for stochastic analyses.

ITour: The Future of Smart Tourism: An IoT Framework for the Independent Mobility of Tourists in Smart Cities

Smart tourism is an important component of smart cities. However, in many cities, insecurity, safety, fraud, and the lack of availability of proper information about resources are the biggest hurdles toward independent mobility. These issues can be overcome via proactive participation of local citizens to help tourists as well as by cooperation between citizens, city administration, and tourists. As a result, a number of components of smart cities can be strengthened, from sustainable mobility in tourism development to economic development. This is very challenging, as it requires a combination of societal inputs and advanced smart and effective tools. This article presents a viable Internet of Things (IoT)-based solution called iTour that is a framework for independent tourist mobility. In the process, we analyze the difficulties in initiatives and lessons, exploring possible roles of the IoT.