2D LiDAR-based eucalyptus tree measurement and monitoring system using mobile application

Name: Pruek Vanna-iampikul

Organization : Engineering Burapha University. Department of Electrical

Email : pruek.va@eng.buu.ac.th

Name: Visutr Boonnateephisit

Organization : Asian Institute of Technology. School of Engineering and Technology

Email : visutr.boon@gmail.com

Name: Somphop Limsoontharakul

Organization : Prince of Songkla University. Dept. Computational Science

Email : somphop.l@psu.ac.th

Name: Jednipat Moonrinta

Organization : Asian Institute of Technology. Computer Science Field of Study School of Engineering and Technology

Email : jednipat.moonrinta@ait.asia

Name: Dailey, Matthew

Organization : Asian Institute of Technology. Information & Communication Tech. School of Engineering and Technology

Email : mdailey@cs.ait.ac.th

Name: Mongkol Ekpanyapong

Organization : Asian Institute of Technology. Dept. of Industrial Systems Engineering School of Engineering and Technology

Email : mongkol@ait.ac.th

keyword: LiDAR remote sensing

LCSH: Eucalyptus -- Measurement

LCSH: Trees -- Monitoring

LCSH: Mobile applications

LCSH: Forest mapping

Abstract: LiDAR technology has rapidly advanced, offering highly accurate solutions for tree geometry estimation, which is particularly valuable in agriculture and forestry. Its ability to capture precise 2D and 3D data has revolutionized tree detection and measurement. In Eucalyptus plantations, continuous monitoring is critical to maximizing growth, enhancing paper production, and mitigating environmental damage. However, existing solutions face challenges in real-time monitoring due to factors such as parasitic interference, low-light conditions, and uneven terrain. In this work, we present a novel, end-to-end framework that enhances Eucalyptus tree measurement and monitoring. Our framework significantly improves data collection efficiency by allowing measurements at walking speed, reducing measurement distance by 50% compared to traditional manual approaches. This system integrates 2D-LiDAR with additional environmental sensors to extract key tree parameters, including circumference, position, and tree count. The collected data is stored in realtime and uploaded to a centralized server for further analysis. Experimental evaluations across 160 trees, under five distinct farm conditions, demonstrate that our system achieves 89% accuracy in tree diameter estimation and 98.5% accuracy in tree counting, significantly outperforming traditional methods. These results establish our framework as a highly effective solution for improving the accuracy and efficiency of tree monitoring in challenging environments

King Mongkut's University of Technology North Bangkok. Central Library

Address: BANGKOK

Email: library@kmutnb.ac.th

Created: 2025

Modified: 2025-06-18

Issued: 2025-06-18

บทความ/Article

application/pdf

BibliograpyCitation : In Electrical Engineering Academic Association (Thailand) and King Mongkut's University of Technology North Bangkok. Department of Electrical and Computer Engineering. 13th International Electrical Engineering Congress (iEECON 2025) (P06268). Bangkok : Electrical Engineering Academic Association (Thailand), 2025

eng

©copyrights King Mongkut's University of Technology North Bangkok

ลำดับที่.	ชื่อแฟ้มข้อมูล	ขนาดแฟ้มข้อมูล	จำนวนเข้าถึง	วัน-เวลาเข้าถึงล่าสุด
1	iEECON 2025 P06268.pdf	3.26 MB	12	2026-05-26 18:16:01

ใช้เวลา

0.048466 วินาที