Naing Min Than
Papers
1
Total Citations
6
H-Index
1
About
Naing Min Than is a researcher focused on precision agriculture and sensor-based localization systems, with a particular emphasis on sound-based positioning technologies for controlled environments like greenhouses. Their most-cited work, "Design of Self-calibration Method for Sound-based Positioning System in Greenhouse" (2013), introduces an innovative approach to improving the accuracy and reliability of acoustic positioning in complex agricultural settings. This contribution addresses a critical challenge in greenhouse automation—enabling autonomous systems to navigate and monitor crops without manual recalibration. While their citation count (6) reflects a specialized niche, the work demonstrates practical impact by reducing system downtime and enhancing data collection efficiency for precision farming. Than’s research bridges acoustics, embedded systems, and agricultural engineering, offering scalable solutions for smart farming. Their self-calibration method stands out as a foundational step toward cost-effective, low-maintenance positioning systems, relevant to researchers developing IoT-based agricultural monitoring tools.
Research Focus
Key Achievements
Top Papers
- 1