International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Automated Orange Detection Using YOLO on Raspberry Pi

Tabassum H KhanAssociate Professor, Department of Artificial Intelligence, G H Raisoni College of Engineering and Managemant, Nagpur, IndiaMaithili ManekarStudent, Department of Artificial Intelligence, G H Raisoni College of Engineering and Management, Nagpur, IndiaNainita RamkelkarStudent, Department of Artificial Intelligence, G H Raisoni College of Engineering and Management, Nagpur, IndiaVaishanavi KaradbhajneStudent, Department of Artificial Intelligence, G H Raisoni College of Engineering and Management, Nagpur, IndiaSaniya BhagatStudent, Department of Artificial Intelligence, G H Raisoni College of Engineering and Management, Nagpur, IndiaPranjal KohaleyStudent, Department of Artificial Intelligence, G H Raisoni College of Engineering and Management, Nagpur, India

Vol 8 No 12 (2024): Volume 8, Issue 12, December 2024 | Pages: 66-72

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 18-12-2024

doi Logo doi.org/10.47001/IRJIET/2024.812011

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Abstract

This research paper describes a real-time orange identification system based on the YOLO (You Only Look Once) object detection method and implemented on a Raspberry Pi. The technology attempts to improve agricultural efficiency by automating the detection and counting of oranges, saving manual labor and increasing accuracy. The YOLO model has been improved for deployment on the Raspberry Pi, ensuring real-time performance with limited processing resources. Experimental results show that the system performs well in a variety of environments, with excellent accuracy and processing speed suitable for agricultural applications.

Keywords

YOLO, Raspberry Pi, Real-Time Detection, Orange Detection, Machine Learning, Agriculture Automation


Citation of this Article

Tabassum H Khan, Maithili Manekar, Nainita Ramkelkar, Vaishanavi Karadbhajne, Saniya Bhagat, & Pranjal Kohaley. (2024). Automated Orange Detection Using YOLO on Raspberry Pi. International Research Journal of Innovations in Engineering and Technology - IRJIET, 8(12), 66-72. Article DOI https://doi.org/10.47001/IRJIET/2024.812011

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