Booktopia has been placed into Voluntary Administration. Orders have been temporarily suspended, whilst the process for the recapitalisation of Booktopia and/or sale of its business is completed, following which services may be re-established. All enquiries from creditors, including customers with outstanding gift cards and orders and placed prior to 3 July 2024, please visit https://www.mcgrathnicol.com/creditors/booktopia-group/
Add free shipping to your order with these great books
Future Communication Systems Using Artificial Intelligence, Internet of Things and Data Science - Inam Ullah

Future Communication Systems Using Artificial Intelligence, Internet of Things and Data Science

By: Inam Ullah (Editor), Inam Ullah Khan (Editor), Mariya Ouaissa (Editor), Mariyam Ouaissa (Editor), Salma El Hajjami (Editor)

Hardcover | 14 June 2024

Sorry, we are not able to source the book you are looking for right now.

We did a search for other books with a similar title, however there were no matches. You can try selecting from a similar category, click on the author's name, or use the search box above to find your book.

Future Communication Systems Using Artificial Intelligence, Internet of Things and Data Science mainly focuses on the techniques of artificial intelligence (AI), Internet of Things (IoT) and data science for future communications systems.

The goal of AI, IoT and data science for future communications systems is to create a venue for industry and academics to collaborate on the development of network and system solutions based on data science, AI and IoT. Recent breakthroughs in IoT, mobile and fixed communications and computation have paved the way for a data-centric society of the future. New applications are increasingly reliant on machine-to-machine connections, resulting in unusual workloads and the need for more efficient and dependable infrastructures. Such a wide range of traffic workloads and applications will necessitate dynamic and highly adaptive network environments capable of self-optimization for the task at hand while ensuring high dependability and ultra-low latency.

Networking devices, sensors, agents, meters and smart vehicles/systems generate massive amounts of data, necessitating new levels of security, performance and dependability. Such complications necessitate the development of new tools and approaches for providing successful services, management and operation. Predictive network analytics will play a critical role in insight generation, process automation required for adapting and scaling to new demands, resolving issues before they impact operational performance (e.g., preventing network failures and anticipating capacity requirements) and overall network decision-making. To increase user experience and service quality, data mining and analytic techniques for inferring quality of experience (QoE) signals are required.

AI, IoT, machine learning, reinforcement learning and network data analytics innovations open new possibilities in areas such as channel modeling and estimation, cognitive communications, interference alignment, mobility management, resource allocation, network control and management, network tomography, multi-agent systems and network ultra-broadband deployment prioritization. These new analytic platforms will aid in the transformation of our networks and user experience. Future networks will enable unparalleled automation and optimization by intelligently gathering, analyzing, learning and controlling huge volumes of information.

More in Machine Learning

Learning Spark : Lightning-Fast Data Analytics - Jules S. Damji

FREE SHIPPING

RRP $152.00

$69.35

54%
OFF
Scaling Python with Dask : From Data Science to Machine Learning - Holden Karau
Implementing MLOps in the Enterprise : A Production-First Approach - Yaron Haviv
Practical MLOps : Operationalizing Machine Learning Models - Noah Gift
Practical Data Privacy : Enhancing Privacy and Security in Data - Katharine Jarmul