Brilliance: Research of Artificial Intelligence
Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025

TreeRTTSys: A Low Cost Sensor To Measure Tree Trunk Quality Using Strain Gauge Sensors

Candra, Rudi Arif (Unknown)
Ilham, Dirja Nur (Unknown)
Budiansyah, Arie (Unknown)



Article Info

Publish Date
15 Dec 2025

Abstract

Tree health monitoring is essential to ensure environmental safety, sustainability, and the prevention of hazards caused by structurally weakened trees. Visual inspection alone is often insufficient to detect internal defects such as decay or reduced mechanical strength within tree trunks. This study presents the design and implementation of TreeRTTSys, a low-cost sensor-based system for evaluating tree trunk quality using strain gauge and load cell sensors integrated with an Arduino microcontroller. The proposed system aims to measure tensile force characteristics of tree trunks as an indicator of structural integrity and mechanical performance. The experimental method was employed by conducting tensile tests on five different types of tree trunks, namely Meranti, Beringin, Rambutan, Durian, and Kapok. A load cell sensor combined with an HX711 signal conditioning module was used to acquire force data, which were processed and recorded in real time by an Arduino-based data acquisition system. The applied tensile load and resistance duration were analyzed to evaluate the strength and deformation behavior of each wood type. The results show significant variation in tensile strength and load resistance among the tested tree species. Meranti wood exhibited the highest tensile strength of 11.13 kN and the longest resistance time of 151 seconds, indicating superior load-bearing capacity and stability. Rambutan wood demonstrated high ductility, sustaining tensile loading for 149 seconds despite a lower maximum force. In contrast, Kapok and Durian woods showed relatively low tensile resistance and shorter failure durations.These findings confirm that the proposed TreeRTTSys is capable of accurately capturing the mechanical behavior of tree trunks in real time. The system offers a reliable, cost-effective solution for tree health assessment, with potential applications in urban forestry management, environmental monitoring, and preventive safety inspections.

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Journal Info

Abbrev

brilliance

Publisher

Subject

Decision Sciences, Operations Research & Management Mathematics Other

Description

Brilliance: Research of Artificial Intelligence is The Scientific Journal. Brilliance is published twice in one year, namely in February, May and November. Brilliance aims to promote research in the field of Informatics Engineering which focuses on publishing quality papers about the latest ...