IEEE Internet of Things Journal · 2020 · 733 citations · 238 references
ComputingCloud ComputingComputer ScienceArtificial IntelligenceEdge ComputingInternet Of ThingsDeep LearningEdge Artificial IntelligenceFog ComputingIot ArchitectureIot Data AcquisitionIot SensorsDeep Learning For IotEdge IntelligenceFog Computing ArchitectureHeterogeneous Data ManagementInternet Of Things Edge ComputingInternet Of Things NetworksMachine Learning For Iot
The Internet‑of‑Things connects billions of sensors that collect and transmit heterogeneous data to cloud centers, yet transmitting, perceiving, and making timely decisions from this data remains difficult, prompting the integration of proven AI techniques such as deep learning into the IoT to usher in the AI of Things era. This survey aims to demonstrate how AI can empower the IoT to become faster, smarter, greener, and safer. The authors outline an AIoT architecture spanning cloud, fog, and edge computing, review advances in perceiving, learning, reasoning, and behaving, and identify challenges and research opportunities. They highlight promising AIoT applications that are poised to profoundly reshape the world.
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 AI of things (AIoT). This article 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: 1) perceiving; 2) learning; 3) reasoning; and 4) 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.
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