Open AccessArticle
Harnessing the Power of Machine Learning and Sensor Detection in a Simulation for the Design of Smart Date Harvesting Robot
Princess Nourah bint Abdul Rahman University, Computer Science Department, P.O. Box 84428, Riyadh, 11671, Saudi Arabia
*whom correspondence should be addressed. E-mail: hahassan@pnu.edu.sa
Received: 7 January 2026, Revised: 12 February 2026, Accepted: 14 February 2026, Published Online: 22 February 2026
(This article belongs to the Section Automation and Control Systems (ACS))
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APA Style
Adlan, H. H. A. , Zamanan, R. A. , Almufleh, L. , Almuqrin, T. and Alhassoun, J. (2026). Harnessing the Power of Machine Learning and Sensor Detection in a Simulation for the Design of Smart Date Harvesting Robot. Journal of Engineering Research and Sciences, 5(2), 1–8. https://doi.org/10.55708/js0502001
Adlan, H. H. A. , Zamanan, R. A. , Almufleh, L. , Almuqrin, T. and Alhassoun, J. (2026). Harnessing the Power of Machine Learning and Sensor Detection in a Simulation for the Design of Smart Date Harvesting Robot. Journal of Engineering Research and Sciences, 5(2), 1–8. https://doi.org/10.55708/js0502001
Chicago/Turabian Style
Hanan Hassan Ali Adlan, Reham Al Zamanan, Leen Almufleh, Tala Almuqrin and Jory Alhassoun. "Harnessing the Power of Machine Learning and Sensor Detection in a Simulation for the Design of Smart Date Harvesting Robot." Journal of Engineering Research and Sciences 5, no. 2 (February 2026): 1–8. https://doi.org/10.55708/js0502001
Hanan Hassan Ali Adlan, Reham Al Zamanan, Leen Almufleh, Tala Almuqrin and Jory Alhassoun. "Harnessing the Power of Machine Learning and Sensor Detection in a Simulation for the Design of Smart Date Harvesting Robot." Journal of Engineering Research and Sciences 5, no. 2 (February 2026): 1–8. https://doi.org/10.55708/js0502001
IEEE Style
H.H.A. Adlan, R.A. Zamanan, L. Almufleh, T. Almuqrin and J. Alhassoun, "Harnessing the Power of Machine Learning and Sensor Detection in a Simulation for the Design of Smart Date Harvesting Robot," Journal of Engineering Research and Sciences, vol. 5, no. 2, pp. 1–8, Feb. 2026, doi: 10.55708/js0502001.
H.H.A. Adlan, R.A. Zamanan, L. Almufleh, T. Almuqrin and J. Alhassoun, "Harnessing the Power of Machine Learning and Sensor Detection in a Simulation for the Design of Smart Date Harvesting Robot," Journal of Engineering Research and Sciences, vol. 5, no. 2, pp. 1–8, Feb. 2026, doi: 10.55708/js0502001.
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Abstract
The Traditional date harvesting is labor-intensive and inefficient, leading to losses and quality issues. This paper introduces an AI-powered robotic system that automates date harvesting using computer vision, LiDAR sensors, and a robotic arm with a suction mechanism. The robot is capable of perception, it detects, classifies, and harvests ripe dates autonomously, ensuring minimal damage and improved efficiency. The work develops a CNN architecture and a YOLO model. Propose using sensors for detection purposes. By integrating YOLO for object detection and CNN for maturity classification, the system optimizes harvesting decisions. This solution is simulated and is supposed to enhance productivity, reduces costs, and improves date quality, contributing to empowering the agriculture sector with powerful tool that encourage date planting, nourish life through economic investment in dates, provide advancement in agricultural automation, and contributing to sustain date planting.
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