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    Li Xiangyang, Shang Fei, Yan Yubo, Wang Shanyue, Han Feiyu, Chi Guoxuan, Yang Zheng, Chen Xiaojiang. Survey on Low Power Sensing of AIoT[J]. Journal of Computer Research and Development, 2024, 61(11): 2754-2775. DOI: 10.7544/issn1000-1239.202440396
    Citation: Li Xiangyang, Shang Fei, Yan Yubo, Wang Shanyue, Han Feiyu, Chi Guoxuan, Yang Zheng, Chen Xiaojiang. Survey on Low Power Sensing of AIoT[J]. Journal of Computer Research and Development, 2024, 61(11): 2754-2775. DOI: 10.7544/issn1000-1239.202440396

    Survey on Low Power Sensing of AIoT

    • With the deepening integration of human-machine-object fusion, an increasing number of lightweight and large-scale sensing demands are emerging. To meet the deployment needs of multiple scenarios and large scales, low-cost and low-power sensing solutions are becoming increasingly favored. However, there are still some common and specific challenges in the field of low-power sensing that hinder their further development and practical application. Although many excellent reviews have been conducted on a specific sensing modality or application, there is still a lack of work that sorts out the entire field of low-power sensing. In this paper, we summarize recent low-power sensing, introduce three types of sensing modalities including inertial measurement unit (IMU), microphone, and radio frequency signals, summarize their related challenges, and introduce relevant solutions from hardware and software levels. Finally, we introduce the applications of sensing schemes in different scenarios from four aspects: surface sensing, property sensing, physiological sensing, and anti-sensing, along the direction from surface to inside, from object to human body, and from sensing to safety, and summarize several prospects for exploration.
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