Guest Editorial: Augmented Intelligence of Things for Smart Enterprise Systems

ENTERPRISE management systems (EMS) and big data analytics are the most promising computing platforms in artificial intelligence, information science, and statistics that use statistical pattern recognition, federated learning [A1], database management, visualization technology, and social networking. In the era of modern industrial and medical science research, there is a significant trend in developing a consortium having experts from various fields, viz., computer network management, artificial intelligence, biomedical engineering, computer vision, sensor devices, and advanced communication systems to achieve easily accessible, affordable and rapid innovative EMS system for providing better significant data handling and creating new demands and opportunities for engineering and management systems and their applications. In the last decade, the number of deployments for information science and the Internet of Things (IoT) [A2] has grown significantly. This continuous and exponential growth is facilitated by investments and research activities from industry, academia, and governments. At the same time, the dissemination of these technologies and management is also driven by the high technology acceptance rates of both consumers and technologists across disciplines. Here, one has been confronted with a new IoT—the intelligence of things. Meanwhile, the future of augmented intelligence of things (AIoT) and artificial intelligence encompasses advanced cognitive methods capable of doing what ordinary federated learning systems cannot attain easily or attain at all in parallel and distributed systems architectures for a Smart society. EMS combines sustainable Industrial IoT and intelligence of things. Augmented intelligence is used to develop a humancentered partnership model. It means that augmented intelligence and or AIoT will soon logically and effortlessly interrelate with human experts and operators, providing them with articulate clarifications and answers, increasing cognitive performance including robust decision making, learning analytics, and new experiences, even at the edge of the network or in robotic devices and navigation. Big data refers to a large set of digital information businesses use to monitor and extract patterns and predictions and correlate with human interactions and behaviors. The proper decision-making systems are required for handling the big massive data under smart EMS. This special issue focuses mainly on robust and adaptive decision-making systems for faster data processing and manipulation in every sector.