Conclusion

This book presented applications, technologies, challenges, and implementation design models of intelligent networks design by Big Data, Internet of Things, artificial intelligence (AI), and cloud computing approaches in different sectors. Research into real-time fault tolerance, security, and data analytics by addressing significant data volume and velocity measurement are essential in intelligent networks, for example, where different analytical models and AI and machine learning algorithms improve end-to-end performance, efficiency, and quality of service (QoS) [1-10].The availability of Big Data, AI, cloud computing, low-cost commodity hardware, and new information management and analytic software has produced a unique moment in the history of intelligent networks [11-21]. The convergence of these trends means that we have the capabilities required to analyze unique data sets quickly and cost-effectively. They represent a genuine leap forward and a clear opportunity to realize enormous efficiency, productivity, revenue, and profitability.This book also discussed issues and challenges that can be addressed and overcome in the future using the new upcoming technologies. The age of intelligent networks is here, and these are truly revolutionary times if business and technology professionals continue to work together and deliver on the promise.Thank you for taking the time to read this book, and we hope you enjoyed reading it as much as we did write it.