الصفحة 1
الصفحة 1
Intelligent connectivity : AI, IoT, and 5G
Explores the economics and technology of AI, IOT, and 5G integration. Delivers a comprehensive technological and economic analysis of intelligent connectivity and the integration of artificial intelligence, Internet of Things (IoT), and 5G. It covers a broad range of topics, including Machine-to-Machine (M2M) architectures, edge computing, cybersecurity, privacy, risk management, IoT architectures, and more. Will also get access to: A thorough introduction to technology adoption and emerging trends in technology, including business trends and disruptive new applications / Comprehensive explorations of telecommunications transformation and intelligent connectivity, including learning algorithms, machine learning, and deep learning / Practical discussions of the Internet of Things, including its potential for disruption and future trends for technological development / In-depth examinations of 5G wireless technology, including discussions of the first five generations of wireless tech
Design and implementation of an array of patch antenna
Wireless technology is one of the main areas of research in global communication systems today and the study of communication systems is incomplete without an understanding of the process and manufacture of antennas. This was the main reason for choosing this project to focus on this area. This paper presents the design and implementation of an antenna array consisting of 4 patch antenna elements that work on 2.4GHz frequency,the substrate FR4, It was analyzed using HFSS (High Frequency Simulator Structure). In order to achieve a gain of 7 db, and a reflection coefficient of s11 of -10db Then the board was printed And he made measurements in the laboratory on the spectrum analyzer and the kit for the antennas As a result of the measurements, we obtained the antenna gain, the antenna radiation pattern, and the s11
Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks
Communication and network technology has witnessed recent rapid development and numerous information services and applications have been developed globally. These technologies have high impact on society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication. Machine learning and cognitive computing have converged to give some groundbreaking solutions for smart machines. With these two technologies coming together, the machines can acquire the ability to reason similar to the human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.
