Recent advancements in machine learning algorithms have facilitated the rapid use of blockchain technology and the Internet of Things in the design and development of smart cities [...]
As smart cities evolve, the demand for real-time, secure, and adaptive network monitoring, continues to grow. Software-Defined Networking (SDN) offers a centralized approach to managing network flows; However, anomaly detection within SDN environments remains a significant challe…
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 c…
This paper presents a novel approach to robotic control by integrating nonlinear dynamics with machine learning (ML) in an Internet of Things (IoT) framework. This study addresses the increasing need for adaptable, real-time control systems capable of handling complex, nonlinear…
Smart home devices, also known as IoT devices, provide significant convenience; however, they also present opportunities for attackers to jeopardize homeowners’ security and privacy. Securing these IoT devices is a formidable challenge because of their limited computational resou…
Healthcare professionals face numerous challenges when analyzing data and providing treatment, including determining which parameters to measure, the frequency of measurement, i.e., how frequently to measure them, and the responsibility for monitoring patient health with new medi…
The Internet of Things (IoT) has radically changed the industrial world, enabling the integration of numerous systems and devices into the industrial ecosystem. There are many areas of the manufacturing industry in which IoT has contributed, including plants’ remote monitoring an…