Search

This paper explores the concept of smart cities and the role of the Internet of Things (IoT) and machine learning (ML) in realizing a data-centric smart environment. Smart cities leverage technology and data to improve the quality of life for citizens and enhance the efficiency of urban services. IoT and machine learning have emerged as key technologies for enabling smart city solutions that rely on large-scale data collection, analysis, and decision-making. This paper presents an overview of smart cities' various applications and discusses the challenges associated with implementing IoT and machine learning in urban environments. The paper also compares different case studies of successful smart city implementations utilizing IoT and machine learning technologies. The findings suggest that these technologies have the potential to transform urban environments and enable the creation of more livable, sustainable, and efficient cities. However, significant challenges remain regarding data privacy, security, and ethical considerations, which must be addressed to realize the full potential of smart cities. [ABSTRACT FROM AUTHOR]

The integration of machine learning (ML), blockchain, and the Internet of Things (IoT) in smart cities represents a pivotal advancement in urban innovation. This convergence addresses the complexities of modern urban environments by leveraging ML's data analytics and predictive capabilities to enhance the intelligence of IoT systems, while blockchain provides a secure, decentralized framework that ensures data integrity and trust. The synergy of these technologies not only optimizes urban management but also fortifies security and privacy in increasingly connected cities. This survey explores the transformative potential of ML-driven blockchain-IoT ecosystems in enabling autonomous, resilient, and sustainable smart city infrastructure. It also discusses the challenges such as scalability, privacy, and ethical considerations, and outlines possible applications and future research directions that are critical for advancing smart city initiatives. Understanding these dynamics is essential for realizing the full potential of smart cities, where technology enhances not only efficiency but also urban sustainability and resilience. [ABSTRACT FROM AUTHOR]

The design of a smart water monitoring and control system in urban areas plays a pivotal role in providing efficient distribution mechanisms to reduce leakage, especially in regions facing water scarcity and limited resources. The convergence of the Internet of Things (IoT) and blockchain technology to improve the system's performance, enhance its security, and provide a decentralized and tamper-proof environment presents an excellent opportunity to evolve the system further and form a state-of-the-art Water 4.0 ecosystem. The proposed Blockchain of Things (BCoT) water system is introduced as a pilot to explore its potential in delivering and managing Water 4.0 applications. An Ethereum platform formed the heart of the BCoT system, while a Raspberry Pi 4 acted as a node to the blockchain that collected data from various sensors and microcontrollers via MQTT programmed by Node-Red. LabVIEW software also provided supervisory control and data acquisition (SCADA). The BCoT system was tested, and its functionality was verified, showing good promise to take smart water systems to a new level of innovation that may resolve the many challenges faced by countries with limited water resources and address the challenges of the 21st-century "Water 4.0" ecosystem. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) paves the way for the modern smart industrial applications and cities. Trusted Authority acts as a sole control in monitoring and maintaining the communications between the IoT devices and the infrastructure. The communication between the IoT devices happens from one trusted entity of an area to the other by way of generating security certificates. Establishing trust by way of generating security certificates for the IoT devices in a smart city application can be of high cost and expensive. In order to facilitate this, a secure group authentication scheme that creates trust amongst a group of IoT devices owned by several entities has been proposed. The majority of proposed authentication techniques are made for individual device authentication and are also utilized for group authentication; nevertheless, a unique solution for group authentication is the Dickson polynomial based secure group authentication scheme. The secret keys used in our proposed authentication technique are generated using the Dickson polynomial, which enables the group to authenticate without generating an excessive amount of network traffic overhead. IoT devices' group authentication has made use of the Dickson polynomial. Blockchain technology is employed to enable secure, efficient, and fast data transfer among the unique IoT devices of each group deployed at different places. Also, the proposed secure group authentication scheme developed based on Dickson polynomials is resistant to replay, man-in-the-middle, tampering, side channel and signature forgeries, impersonation, and ephemeral key secret leakage attacks. In order to accomplish this, we have implemented a hardware-based physically unclonable function. Implementation has been carried using python language and deployed and tested on Blockchain using Ethereum Goerli's Testnet framework. Performance analysis has been carried out by choosing various benchmarks and found that the proposed framework outperforms its counterparts through various metrics. Different parameters are also utilized to assess the performance of the proposed blockchain framework and shows that it has better performance in terms of computation, communication, storage and latency. [ABSTRACT FROM AUTHOR]

In recent years, the rate of urbanization has increased enormously, precipitating an escalating demand for improved services and applications in urban areas to improve the quality of life. In the Internet of Things (IoT)era, cities are transforming into smart urban centers. These cities incorporate connected devices, such as intelligent public lighting systems, to enhance their urban infrastructure. Therefore, this work explores the transformative potential of an IoT-enabled smart lighting system in urban environments, emphasizing its essential role in enhancing safety, economy, and sustainability. In this sense, LoRaCELL (Long-Range Cell) is introduced. LoRaCELL is an innovative system that utilizes edge devices for data collection, such as light intensity, humidity, temperature, air quality, solar ultraviolet radiation, ammeter, and voltmeter. It stands as a pioneering solution for intelligent public lighting systems, contributing to advancing IoT-driven urban development. The outcomes showed that the proposed system could successfully synchronize the devices with each other and send IoT sensing data at a low cost compared to traditional technologies such as LoRaWAN. [ABSTRACT FROM AUTHOR]

Car dependence is a trend brought about by the desire for comfortable transportation, in many countries around the world. After the invention and acceptance of automobiles, cities were designed with layouts that favored automobiles at the expense of other forms of transportation. However, the situation has changed with research and execution of plans for smart cities, with smart mobility transition taking centre stage. The purpose of this research is to highlight the need for transition to smart mobility, provide detailed description of various aspects of smart mobility and analyse the challenges and opportunities associated with the transition to smart mobility in car-dependent countries. A thorough and critical review of the literature has been done to achieve the aim of this study. Previous research efforts indicated that car-dependent cities have experienced several challenges in their transition to smart mobility, including inadequate infrastructure, low acceptance of new technological solutions, inadequate knowledge and framework for big data, financial constraints, data quality management, integration of data from different sources, privacy issues, and development of appropriate of government policies. There are several promising recommendations, which implementation is expected to help car-dependent countries overcome the above challenges and open opportunities for a successful transition. These recommendations include implementation of aggressive government policies, practicing greater inclusivity, and planning for the future of smart mobility by investing in Internet of Things (IoT) applications and reliable infrastructure. To facilitate the decision makers, challenges have been mapped with recommendations for transition to smart mobility, in light of the review findings. [ABSTRACT FROM AUTHOR]