Abstract
The palm oil industry in Malaysia is encountering challenges that need innovative and technology-driven solutions. This study focuses on palm tree detection where 2D LiDAR sensors are utilized to collect data like distance and reflection strength. Through analysis, the gathered data are compared with an array of trend lines to ascertain the optimal data relationship. Among the equations considered, including linear, logarithmic, polynomial, and power equations, the power equation emerges to fit more for the detection algorithm. The chosen equation is integrated into the ESP32 firmware. The evaluation of the algorithm’s efficacy transpires through its accuracy in identifying palm trees. The algorithm exhibits an accuracy rate of 98%, attesting to its proficiency in discerning palm trees within plantations.
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The authors thank UNITAR International University for the publication of this research.
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Yusof, L.H.B., Al-Nahari, A.Y.Y., Yao, D.N.L., Mohamad, N. (2024). Harvest Palm Tree Based on Detection Through 2D LiDAR Sensor Using Power Equation. In: Bee Wah, Y., Al-Jumeily OBE, D., Berry, M.W. (eds) Data Science and Emerging Technologies. DaSET 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 191. Springer, Singapore. https://doi.org/10.1007/978-981-97-0293-0_6
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DOI: https://doi.org/10.1007/978-981-97-0293-0_6
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