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Internet of Things (IoT) is an important technology employed in a variety of different applications, such as transportation, healthcare, and manufacturing. In recent years, the number of IoT devices deployed globally has been increasing at a rapid pace and is estimated to reach 20 billion by the end of 2025. In modern industry, IoT plays a pivotal role by monitoring the condition of industrial machines and, consequently, improving the efficiency of industrial processes. To optimize the efficiency of industrial IoT applications, various Artificial Intelligence (AI) techniques have been adopted, leading to a new computing paradigm, namely, Industrial Artificial Intelligence of Things (i.e. Industrial AIoT). In this paper, we describe the challenges to tackle and the opportunities to explore in Industrial AIoT. Specifically, we first review the use of state-of-the-art AI methods in Industrial AIoT applications, with a focus on Deep Learning (DL) and Machine Learning (ML) techniques. Thereafter, we present a series of important applications of Industrial AIoT. The key challenges associated with the implementation of Industrial AIoT applications are also discussed. In addition, the societal and economic impacts of Industrial AIoT are briefly described. Finally, we outline the future research directions in Industrial AIoT, which should be further investigated to fully utilize the potential of this innovative technology. |
