Guest Editorial: Special Issue on Robustness and Efficiency in the Convergence of Artificial Intelligence and IoT

Today, the Internet of Things (IoT) is increasingly flourishing with establishing ubiquitous connections between smart devices and objects, and by 2020, there will be a total of 30 billion connected things reported by IDC. The unprecedented data explosion provides immense opportunities for valuable information mining. At the same time, it also floods the infrastructure with tremendous values it necessarily handles and proposes high challenges to traditional data storing or processing techniques. On the other hand, artificial intelligence (AI) has become a key component for many applications that profoundly change our lives. Machine learning, especially deep learning (DL) technologies, vastly improves traditional computer science and networking technologies. The convergence of AI and IoT enables data to be quickly explored and turned into significant decisions. For companies and enterprises, AI enhances the speed and accuracy of data processing for instant market strategies.

Automated summary

The development of the Internet of Things has made artificial intelligence a key component for applications, with deep learning technologies greatly improving traditional computer science and networking technologies. Furthermore, the convergence of AI and IoT allows data to be quickly explored and turned into significant decisions.