AI-On-Skin: Towards Enabling Fast and Scalable On-body AI Inference for Wearable On-Skin Interfaces-Reference-Cited by-同舟云学术

AI-On-Skin: Towards Enabling Fast and Scalable On-body AI Inference for Wearable On-Skin Interfaces

Published:2023-06-14 Issue:EICS Volume:7 Page:1-34
ISSN:2573-0142
Container-title:Proceedings of the ACM on Human-Computer Interaction
language:en
Short-container-title:Proc. ACM Hum.-Comput. Interact.

Author:

Balaji Ananta Narayanan¹^ORCID,Peh Li-Shiuan¹^ORCID

Affiliation:

1. National University of Singapore, Singapore, Singapore

Abstract

Existing artificial skin interfaces lack on-skin AI compute that can provide fast neural network inference for time-critical applications. In this paper, we propose AI-on-skin - a wearable artificial skin interface integrated with a neural network hardware accelerator that can be reconfigured to run diverse neural network models and applications. AI-on-skin is designed to scale to the entire body, comprising tiny, low-power, accelerators distributed across the body. We built 7 AI-on-Skin application prototypes and our user trials show AI-On-Skin achieving 20X and 50X speedup over off-body inference via Bluetooth and on-body centralized microprocessor based inference approach respectively. We also project the power performance of AI-on-skin with our accelerator fabricated as silicon chips instead of emulated on FPGAs and show 10X further power savings. To the best of our knowledge, AI-on-Skin is the first ever wearable prototype to demonstrate skin interfaces with on-body AI inference.

Funder

Advanced Research and Technology Innovation Centre (ARTIC), the National University of Singapore

National Research Foundation Singapore

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Human-Computer Interaction,Social Sciences (miscellaneous)

Link

https://dl.acm.org/doi/pdf/10.1145/3593239

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