Embedding a Real-Time Strawberry Detection Model into a Pesticide-Spraying Mobile Robot for Greenhouse Operation
Source abstract
Abstract
The real-time detection of fruits and plants is a crucial aspect of digital agriculture, enhancing farming efficiency and productivity. This study addresses the challenge of embedding a real-time strawberry detection system in a small mobile robot operating within a greenhouse environment. The embedded system is based on the YOLO architecture running in a single GPU card, with the Open Neural Network Exchange (ONNX) representation being employed to accelerate the detection process. The experiments conducted in this study demonstrate that the proposed model achieves a mean average precision (mAP) of over 97%, processing eight frames per second for 512 × 512 pixel images. These results affirm the utility of the proposed approach in detecting strawberry plants in order to optimize the spraying process and avoid inflicting any harm on the plants. The goal of this research is to highlight the potential of integrating advanced detection algorithms into small-scale robotics, providing a viable solution for enhancing precision agriculture practices.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Smart Agriculture and AI · Plant Virus Research Studies · Greenhouse Technology and Climate Control
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
LCS Laboratory, Physics Department, Faculty of Sciences, Mohammed 5 University in Rabat, Ibn Battouta Street, Rabat 10000, Morocco
Informatics and Applications Laboratory, Faculty of Science, Moulay Ismail University in Meknes, Zitoune Street, Meknes 11201, Morocco
IRSM, High Institute of Management, Administration, and Computer Engineering (ISMAGI), Rabat 10120, Morocco
Faculty of Science and Technology, Campus de Gambelas, Universidade do Algarve, 8005-391 Faro, Portugal
NOVA-LINCS, and Center of Intelligent Systems, IDMEC/LAETA, University of Lisbon, 1049-001 Lisboa, Portugal
Funding
Ministry of Higher Education, Scientific Research and Innovation of Morocco (MESRSI) · National Centre of Scientific and Technical Research of Morocco (CNRST) · Digital Development Agency of Morocco (ADD) through the AL-KHAWARIZMI program of Morocco · NOVA LINCS · FCT.IP
References (55)
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