交通安全系统边缘AI计算

A. Liu, O.M.K. Law, Jeremiah Liao, Jeffrey Y.C. Chen, Andy Jia En Hsieh, C. Hsieh
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引用次数: 1

摘要

由于移动数据的激增,边缘人工智能的发展是为了解决云限制、实时处理、数据延迟、网络带宽和功耗。科耐龙成功实现了采用智能边缘AI架构的交通安全系统,应用智能网关弥合了云与边缘AI之间的鸿沟,并建立了进一步集成的开放平台。新的架构通过区块链方法提供额外的安全和隐私保护。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Traffic Safety System Edge AI Computing
Due to the surging of mobile data, edge AI is developed to address the cloud limitations, real-time processing, data latency, network bandwidth, and power dissipation. Kneron successfully implements the traffic safety system using the smart edge AI architecture, which applies the smart gateway to bridge the gap between cloud and edge AI, it also establishes the open platform for further integration. New architectures offer additional security and privacy protection through the blockchain approach.
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