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Artificial Intelligence and Internet of Things Using FPGA

Synopsis

FPGAs offer high throughput and low latency and have demonstrated better performance compared to GPUs and CPUs. This project applies artificial intelligence to enhance two solutions using the System-on-Chip approach with FPGA technology, namely, an automatic face-recognition (FR) system for attendance taking and an AIoT system for vertical farming applications. 

Project Video

SUPERVISORS:

Niu Tianfang (Lead) | David Hee | James Yee | Low Lee Ngo |  Paul Lee | Tee Taoyi | Wee Boon Siong | Barbera Chen | Goh Wee Meng

TEAM MEMBERS:

Baggayan Rohmina Klarisse Diza | Foong Hao Juen | Gabriel Asaween Suwanarat | Goh Yong Jun Clement | Jared Yeo Jie Hao | Lim Jian Xiong Jacky | Marcus Lee Wei | Ng Yi Zhuang Calvin | Tan Jing Heng Zenden | Tay Chun Keat Samuel

DIPLOMA:

Diploma in Aerospace Electronics
Diploma in Computing Engineering
Diploma in Electrical & Electronic Engineering
Diploma in Engineering with Business

INDUSTRY PARTNER:

Singapore Indoor Farms Pte Ltd

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