Aug 2026· Journal of Intelligent Computing and Networking· 0 citations· 45 references
TL;DR
This research endeavors to address challenges in ensuring reliable and efficient communication in FANET-IoT-IoT-IoV interactions within the context of 6G-enabled smart city applications by systematically evaluating the performance metrics, identifying optimization opportunities, and developing novel methodologies.
Abstract
In the wake of rapid urbanization and technological advancements, the emergence of 6G-enabled smart city applications presents unprecedented opportunities to revolutionize urban living, mobility, and sustainability. Central to the realization of smart city visions is the seamless integration and coordination of diverse communication systems, including Flying Ad Hoc Networks (FANETs), Internet of Things (IoT), and Internet of Vehicles (IoV). These interconnected systems hold the potential to enable real-time monitoring, data-driven decision-making, and proactive management of urban infrastructure and services. However, the dynamic nature of smart city environments, coupled with the heterogeneity and resource constraints of FANETs, IoT devices, and connected vehicles, pose significant challenges in ensuring reliable and efficient communication. This research endeavors to address these challenges by focusing on the performance evaluation and optimization of FANET-IoT-IoV interactions within the context of 6G-enabled smart city applications. By systematically evaluating the performance metrics, identifying optimization opportunities, and developing novel methodologies, this research paves the way for the development of robust, scalable, and resilient communication infrastructures that can underpin the future of smart urban environments.
The integration of IoT devices and the development of smart cities have brought about significant changes in urban infrastructure. Smart spaces represent a pivotal use case, exemplifying the integration of IoT sensors to enhance automation and decision-making. In these environments, interoperability is critical when incompatible devices interact, enabling seamless communication and optimized performance. To the best of our knowledge, this is the first work to present a comparative evaluation of systems with and without interoperability, focusing on end-to-end system performance and highlighting the importance of interoperability in real-time smart space control. Towards this, we implemented a multi-layered architecture consisting of a novel Controller Layer (CL) that drives the interactions between air quality sensing and actuation of the window and air purifier. Additionally, the architecture consists of the Device Layer (DL), Data Monitoring Layer (DML), and Data Storage Layer (DSL). The DML uses oneM2M as middleware to achieve interoperability among indoor and outdoor air-quality sensors and actuators, such as a window controller and an air purifier. Our focus is on assessing the end-to-end performance of interconnected dependent actions and the significance of response time across incompatible devices. Experimental results show correlations between window controller and air-purifier states based on sensor data, offering insights into achieving interoperability in smart spaces and improving real-time air-quality management.
Sasidhar Varada, Ushasri Mogadali, Deepak Gangadharan et al.· International Conference on...· 0 citations
The study examines how IoT and AI technologies support resource management, trash reduction, and energy efficiency—three important urban sustainability objectives, and indicates that IoT and AI will play a significant role in creating sustainable cities of the future with careful deployment and regulatory support.
R. K R, B. V· International Journal of Inn...· 0 citations
The results of the analysis indicate that 6G can contribute to a substantial improvement of IoT performance in smart cities, healthcare, industrial automation and control applications (manufacturing science), autonomous transportation and precision agriculture.
Md Asaduzaman, Ferdous Hossain, T. Geok· International Journal of Ele...· 0 citations
A systematic literature review of G-IoT technologies and strategies applied in urban settings is provided following PRISMA guidelines, consolidating findings across three interconnected areas: energy-saving technology, communication protocols, and security concerns with corresponding countermeasures.
S. Salih, A. H. A. Hashim, Omayma Husain et al.· Telecommunications Systems· 0 citations
Abstract
The Internet of Things (IoT) has emerged as one of the most significant technological advancements in recent years, enabling seamless communication and interaction among physical devices through the Internet. IoT technology has transformed traditional monitoring and control systems by providing real-time data collection, remote accessibility, intelligent decision-making, and automated control mechanisms. The increasing demand for smart environments in sectors such as smart homes, healthcare, agriculture, industrial automation, and smart cities has accelerated the adoption of IoT-based solutions. This dissertation presents the design and implementation of an IoT-based smart system for real-time monitoring and automation using low-cost hardware components, cloud computing platforms, and mobile applications.
The primary objective of this research is to develop an efficient, reliable, and scalable IoT-based monitoring system capable of collecting environmental data, transmitting information to cloud servers, and enabling remote monitoring and automated control. The proposed system integrates NodeMCU ESP8266 as the central processing unit with sensors such as the DHT11 temperature and humidity sensor and the PIR motion sensor. These sensors continuously monitor environmental conditions and transmit the collected data to cloud platforms through wireless communication. ThingSpeak is used as the cloud platform for data storage, visualization, and analysis, while the Blynk mobile application provides users with real-time monitoring and remote control capabilities.
The development process involved hardware configuration, software programming, cloud integration, and system testing. The NodeMCU microcontroller was programmed using Arduino IDE to acquire sensor readings, establish wireless connectivity, and communicate with cloud services. The collected data was uploaded to the cloud platform and displayed through graphical dashboards for real-time observation. Furthermore, automation functionalities were incorporated through relay modules that enable automatic control of connected devices based on predefined threshold values and environmental conditions.
Experimental investigations were conducted to evaluate the performance and effectiveness of the proposed system. The results demonstrated successful real-time monitoring of temperature, humidity, and motion detection parameters. Sensor data was accurately transmitted to the cloud platform and displayed on the mobile application with minimal delay. The automation features successfully triggered control actions whenever predefined conditions were satisfied. The system also demonstrated reliable communication between sensors, cloud servers, and end users, thereby validating the feasibility of the proposed approach.
A comparative analysis between traditional monitoring systems and the proposed IoT-based solution revealed significant improvements in terms of automation, accessibility, data management, operational efficiency, and remote monitoring capabilities. The implementation confirmed that IoT technology can substantially reduce manual intervention, improve response time, and enhance system effectiveness. Despite challenges such as network dependency, security concerns, and sensor limitations, the developed system proved to be a cost-effective and practical solution for intelligent monitoring and automation applications.
Zarreen Fatima, A. Farooqi· International Scientific Jou...· 0 citations
Urban traffic congestion is a major challenge affecting sustainability, energy efficiency, and mobility in smart cities. The emergence of 5G/6G and beyond networks, combined with intelligent wireless communication and sensing, offers unprecedented opportunities for real-time traffic monitoring, AI-driven congestion modeling, and dynamic routing optimization. Despite these advancements, existing 5G/6G-enabled intelligent transportation systems studies remain fragmented with limited integration between wireless communication, sensing, vehicular traffic modeling, which reduces their effectiveness in addressing real-world urban traffic congestion challenges. A systematic literature review was conducted using the PRISMA framework, synthesizing 49 peer-reviewed studies published between 2019 and 2026 to identify key trends, methodologies and applications that leverage 5G/6G-enabled sensing and communication for vehicular congestion reduction. However, current review studies primarily focus on isolated aspects such as communication architectures, AI techniques, or vehicular networking frameworks, and lack a comprehensive and systematic synthesis that examines intelligent wireless communication and sensing for sustainable traffic modeling. Findings indicate that existing studies widely explore the integration of 5G/6G-enabled vehicular communication, IoT sensing, AI-driven traffic prediction, and edge intelligence for real-time congestion management. Nevertheless, full integration across communication, sensing, and traffic modeling remains limited, with privacy, scalability, cost, and interoperability continuing to pose major challenges. Integration of 5G/6G, IoT sensing, and AI traffic modeling enables real-time congestion management and efficient routing, directly supporting sustainability goals such as reduced energy use, lower emissions, and improved urban mobility. To the best of our knowledge, this is the first PRISMA-guided systematic review that provides a unified cross-layer synthesis of intelligent wireless communication, sensing technologies, and AI-driven traffic modeling specifically for sustainable vehicular congestion reduction in 5G/6G-enabled ITS. By examining 5G/6G-enabled ITS, this study complements existing surveys through a unified cross-layer synthesis of communication, sensing, traffic modeling, and sustainability aspects, while providing practical insights for developing efficient and AI-driven urban traffic systems. Furthermore, the findings support policy decisions that prioritize 5G/6G infrastructure investment, edge computing deployment and interoperable ITS standards to enable scalable real-world implementation.
Benjamin Simwinga, Aaron Zimba, Mayumbo Nyirenda· Discover Networks· 0 citations
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