Requirements Of Smart City Research Articles

System Architecture Design of IoT-Based Smart Cities

The integration of Internet of Things (IoT) networks into smart cities is crucial to enhance the efficiency of city operations and services. Designing a smart city architecture that can adapt to the constantly changing functional and quality requirements of city services is essential. However, critical decisions must be made during this process, such as selecting communication protocols, ensuring security and safety, optimizing time performance, and processing data capacity. To address these challenges, this paper proposes a systematic approach to guide the system architecture design of IoT-based smart cities. The approach starts with feature-driven domain analysis to model smart city requirements, followed by the design of a reference architecture for IoT-based smart cities. The architecture is modeled using selected architectural views, while considering key stakeholders and their concerns. Additionally, this paper presents valuable insights into lessons learned and challenges encountered during the process of creating IoT-based smart cities. This information can assist practitioners in developing such smart cities and pave the way for future research in this field. By following this proposed approach, smart city architects can design a robust and adaptable system architecture that can meet the evolving needs of smart city services.

Towards a reliable smart city through formal verification and network analysis

With the immense increase of population density, many challenges facing organizations and governments. Thus, it has become mandatory to turn up our cities to be intelligent by introducing IoT and smart grids to build smart buildings, smart communication technologies, smart healthcare systems, smart transportation, etc. Smart cities guarantee the healthy living of indoor inhabitants by sensing, processing and controlling all possible indoor–outdoor measures. In this paper, we develop a framework that systematically builds a reliable and secure Smart City Model (SCM) to be integrated then exploited by the building information model (BIM). SCM encloses both physical and digital models which highlight smart buildings in particular. First, the proposed solution identifies and models SCM components including their appropriate architectures that are responsible for communication, extension, information flow, and protection. To ensure SCM functional and security requirements, we develop a sound hybrid approach that relies on formal methods and network analysis. Uppaal model checker is used to verify the satisfiability of the smart city requirements whereas Cooja is deployed to simulate the connectivity and the communication coverage of the developed SCM. The obtained results, in Uppaal, showed that the different implemented scenarios are satisfying the functional correctness and security policies. Moreover, the simulation through Cooja showed that how different obstacles and positions of nodes affect the communication coverage and the energy consumption regarding the deployed nodes. Experimentally, the effectiveness of the developed framework has been shown through practical scenarios that are difficult to model and analyze.

A Novel Spatial–Temporal Specification-Based Monitoring System for Smart Cities

With the development of the Internet of Things, millions of sensors are being deployed in cities to collect real-time data. This leads to a need for checking city states against city requirements at runtime. In this article, we develop a novel spatial-temporal specification-based monitoring system for smart cities. We first describe a study of over 1000 smart city requirements, some of which cannot be specified using the existing logic, such as the signal temporal logic (STL) and its variants. To tackle this limitation, we develop spatial aggregation STL (SaSTL)-a novel spatial aggregation STL-for the efficient runtime monitoring of safety and performance requirements in smart cities. We develop two new logical operators in SaSTL to augment STL for expressing spatial aggregation and spatial counting characteristics that are commonly found in real city requirements. We define the Boolean and quantitative semantics for SaSTL in support of the analysis of city performance across different periods and locations. We also develop efficient monitoring algorithms that can check the SaSTL requirement in parallel over multiple data streams (e.g., generated by multiple sensors distributed spatially in a city). Additionally, we build an SaSTL-based monitoring tool to support decision making of different stakeholders to specify and runtime monitor their requirements in smart cities. We evaluate our SaSTL monitor by applying it to three case studies with large-scale real city sensing data (e.g., up to 10 000 sensors in one study). The results show that SaSTL has a much higher coverage expressiveness than other spatial-temporal logics, and with a significant reduction of computation time for monitoring requirements. We also demonstrate that the SaSTL monitor improves the safety and performance of smart cities via simulated experiments.

Data-Augmentation-Based Cellular Traffic Prediction in Edge-Computing-Enabled Smart City

With the massive deployment of 5G cellular infrastructures, traffic prediction has become an indispensable part of the cellular resource management system in order to provide reliable and fast communication services that can meet the increasing quality-of-service requirements of smart city. A promising approach for handling this problem is to introduce intelligent methods to implement a highly effective and efficient cellular traffic prediction model. Meanwhile, integrating the multiaccess edge computing framework in 5G cellular networks facilitates the application of intelligent traffic prediction models by enabling their implementation at the network edge. However, the data shortage and privacy issues may still be obstacles for training a robust and accurate prediction model at the edge. To address these issues, we propose a data-augmentation-based cellular traffic prediction model (ctGAN-S2S), where an effective data augmentation submodel based on generative adversarial networks is proposed to improve the prediction performance while protecting data privacy, and a long-short-term-memory-based sequence-to-sequence submodel is used to achieve the flexible multistep cellular traffic prediction. The experimental results on a real-world city-scale cellular traffic dataset reveal that our ctGAN-S2S model achieves up to 48.49% improvement of the prediction accuracy compared to four typical reference models.

Instigating Smart City Infrastructure in Oman: Considering Social Benefits and Economic Values

Smart city is a group of technologies application used to improve the quality of people life by making services easier. The main requirements of smart city are both of physical infrastructure and technology infrastructure. Smart cities are including such as renewable energy, water quality, sewage management, transportation management, smart health, smart parking, waste management, electric vehicle charging, smart home, air pollution management, intelligent shopping, traffic management, smart environment, public safety, smart building, and internet of things. Through evaluating of main cities in Oman, it is time to develop the life style and living of people. This led to change of human life culture in dealing with a smart infrastructure. Smart city is concentered to connect the living city with some factors which improve high quality life and sustainable development services to citizens. The research will focus in analysis and identify the ability of converting capital cities like Muscat to smart city and trying to find common barriers of implement the smart city infrastructure. Also, it will evaluate economics and social effects of smart cities to the human life of Oman culture and develop the framework of smart city infrastructure in Oman. The methodology was used triangulation data method in this study which conducting the data received from three parts include data collection, quantitative method and qualitative method. Each analysis was done through different method to reach main results. The significant Findings discussed to cover the requirements of research objectives. Most of findings indicates that smart cities are popular from public because of its benefits in different sides. The results found that main cities in Oman can be converting to smart cities by developing the both physical and technology infrastructures. In addition, smart cities require a strategic plan to attract the global investment and improving the local business such as tourism and industrial areas. It is recommended that smart cities can improve public service and required to make facilities faster and cheaper.

Heterogeneity in IoT-based Smart Cities Designs

<span class="fontstyle01"><span>Smart city is a strategy of supporting new way of living using data that are collected from different types of electronic devices, analyzed and utilized to enable efficient resource usability and service optimization. Applications of various nature are elaborated in the smart cities, such as traffic planning applications, crowd monitoring, public health care, security, economy and urban planning. Thus, various requirements are needed to incorporate and facilitate efficient development of these applications in the smart city design. Accordingly, smart city can be distinguished via the requirements that support these applications. In this study, the requirements of smart city in relations to the involved applications and its influence on the smart city design are discussed. A list of smart city requirements is concluded and the potentials of various network architecture to facilitate such requirements are discussed. </span></span><span class="fontstyle01"><span>Based on the requirements and the architectures, the existing smart city designs are evaluated and compared. </span></span>

Designing smart city mobile applications

The software architecture community has played a crucial role in the development of mobile software. Many of the ideas used in the design of these systems came from traditional software architecture and those ideas have contributed to mobile computing becoming ubiquitous. Mobile applications in the context of smart cities are very challenging since they need to operate within the power, processor, and capacity limitations of mobile devices, the exacting demands of life critical smart city requirements, and the constantly changing and exposed environment which may not always be trusted. Since there are no widely accepted design models for this type of software, developers must resort to primitive design decisions to meet all the needs of these applications, which takes additional time and expertise. For this reason, this study aims to investigate the design process for mobile applications in the context of smart cities. In order to address the lack of verified information about designing mobile apps, we conducted a multi-case study with 9 applications from 4 different development groups to build a grounded theory. The applications were reverse engineered to expose the architecture of each application. Based on all the data, an initial grounded theory was constructed to explain how the selected design process produces an app with the desired characteristics. The resulting theory offers explanations for how software engineering teams design mobile apps for smart cities. This knowledge will serve as a basis to further understand the phenomena and advances towards more effective design and development process definitions.

IoT as a Service for Smart Cities and Nations

Nowadays, smart city requirements foresee an intelligent framework that enables integrated models toward an Internet of Things (IoT) as a service (IoTaaS) standardization. The tailored selection of each IoT component inside the selected IoT world can solve adoption and monetization issues pushing forward to integrated and intelligent IoT solutions, creating the highest values for secure smart cities.