CrowdTransfer: Enabling Crowd Knowledge Transfer in AIoT Community

知识转移 计算机科学 传输(计算) 知识管理 并行计算
作者
Yan Liu,Bin Guo,Nuo Li,Yasan Ding,Zhouyangzi Zhang,Zhiwen Yu
出处
期刊:IEEE Communications Surveys and Tutorials [Institute of Electrical and Electronics Engineers]
卷期号:: 1-1
标识
DOI:10.1109/comst.2024.3423319
摘要

Artificial Intelligence of Things (AIoT) is an emerging frontier based on the deep fusion of Internet of Things (IoT) and Artificial Intelligence (AI) technologies. Although advanced deep learning techniques enhance the efficient data processing and intelligent analysis of complex IoT data, they still suffer from notable challenges when deployed to practical AIoT applications, such as constrained resources, and diverse task requirements. Knowledge transfer is an effective method to enhance learning performance by avoiding the exorbitant costs associated with data recollection and model retraining. Notably, although there are already some valuable and impressive surveys on transfer learning, these surveys introduce approaches in a relatively isolated way and lack the recent advances of various knowledge transfer techniques for AIoT field. This survey endeavors to introduce a new concept of knowledge transfer, referred to as Crowd Knowledge Transfer (CrowdTransfer), which aims to transfer prior knowledge learned from a crowd of agents to reduce the training cost and as well as improve the performance of the model in real-world complicated scenarios. Particularly, we present four transfer modes from the perspective of crowd intelligence, including derivation, sharing, evolution and fusion modes. Building upon conventional transfer learning methods, we further delve into advanced crowd knowledge transfer models from three perspectives for various AIoT applications. Furthermore, we explore some applications of AIoT areas, such as human activity recognition, urban computing, multi-robot system, and smart factory. Finally, we discuss the open issues and outline future research directions of knowledge transfer in AIoT community.
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