Ang Lay Ying

Universiti Tunku Abdul Rahman

Papers

1

Total Citations

2

H-Index

1

About

Ang Lay Ying is a researcher at the forefront of agricultural automation, with a focused expertise in computer vision and robotics for precision farming. Her most notable contribution is the development of an efficient framework for counting and localizing objects of interest, designed to accelerate yield estimation in large-scale agricultural settings. This work, published in 2017, ingeniously integrates a computer, mobile phone, and a Lego Mindstorm NXT robot to create a low-cost, accessible automation solution. While the paper has garnered 2 citations to date, its practical, hands-on approach highlights the potential for democratizing agricultural technology. Ang Lay Ying’s research addresses a critical bottleneck in post-harvest management, offering a scalable method to reduce manual labor and improve data accuracy for farmers. Her work stands out for its innovative use of off-the-shelf components, bridging the gap between advanced robotics and real-world agricultural challenges. This project not only showcases her ability to solve practical problems but also lays the groundwork for future advancements in smart farming and automated crop monitoring.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Efficient counting and localizing objects of interest for agricultural automation
2 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Universiti Tunku Abdul Rahman

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago