报告详情
TinyML Hardware Architectures for Sustainable Smart Cities
编号：70
访问权限：仅限参会人
更新：2026-10-04 23:31:53 浏览：9次
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摘要
The emergence of smart cities has resulted in the increasing use of IoT devices for environmental monitoring, intelligent transport, public safety, energy control, and healthcare applications. Nevertheless, the perpetual streaming of sensor data to cloud servers creates high energy costs, latency, communication overhead, and privacy issues. TinyML is a novel paradigm that allows for AI inference in small edge devices that operate with a power budget of only a few milliwatts. In this paper, we present an extensive study of TinyML hardware architectures towards sustainable smart city applications. Our framework combines low-power microcontrollers, edge AI accelerators, efficient communication components, and renewable energy harvesting technologies for enabling on-the-fly inference at the edge of the network. The analysis shows that compared to traditional cloud-based AI systems, the energy consumption and latency can be reduced by up to 70% and 90%, respectively, while reducing network traffic by 80% and increasing the lifetime of sensor nodes by more than 300%.
关键词
TinyML,Smart Cities,Edge AI,Low-Power Computing,Artificial Intelligence,Process Innovation
报告人
Wai Yie Leong
researcher INTI International University稿件作者
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重要日期
-
会议日期
10月11日
2026
至10月14日
2026
-
12月30日 2025
报告提交截止日期
-
09月28日 2026
提前注册日期
-
10月10日 2026
初稿截稿日期
-
10月14日 2026
注册截止日期
主办单位
United Societies of Science
承办单位
Posts and Telecommunications Institute of Technology
协办单位
IEEE Section
IEEE Vietnam Section
IEEE Vietnam Section
联系方式
- ASIANComNet 2026
- as******@usssociety.org
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