Empowering Things with Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things

TL;DR

This survey explores how artificial intelligence, especially deep learning, enhances IoT systems by improving perception, decision-making, and applications, while discussing architecture, progress, challenges, and future opportunities in AIoT.

Contribution

It provides a comprehensive overview of AIoT architecture, recent research progress, applications, challenges, and future research directions in integrating AI with IoT.

Findings

AI significantly improves IoT perception and decision-making.

AIoT applications are transforming various industries.

Challenges include data heterogeneity and real-time processing.

Abstract

In the Internet of Things (IoT) era, billions of sensors and devices collect and process data from the environment, transmit them to cloud centers, and receive feedback via the internet for connectivity and perception. However, transmitting massive amounts of heterogeneous data, perceiving complex environments from these data, and then making smart decisions in a timely manner are difficult. Artificial intelligence (AI), especially deep learning, is now a proven success in various areas including computer vision, speech recognition, and natural language processing. AI introduced into the IoT heralds the era of artificial intelligence of things (AIoT). This paper presents a comprehensive survey on AIoT to show how AI can empower the IoT to make it faster, smarter, greener, and safer. Specifically, we briefly present the AIoT architecture in the context of cloud computing, fog computing, and edge computing. Then, we present progress in AI research for IoT from four perspectives: perceiving, learning, reasoning, and behaving. Next, we summarize some promising applications of AIoT that are likely to profoundly reshape our world. Finally, we highlight the challenges facing AIoT and some potential research opportunities.