Publication: Development of artificial intelligence (ai) for image processing of oyster mushroom
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Date
2023-07-01
Authors
Pravin A/L Kumar
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Abstract
Mushrooms have been recognized as a valuable commodity in Malaysia's National Agro-Food Policy (2011-2020), and efforts to develop the mushroom industry have been intensified as part of the agricultural transformation program. This program aims to expand cultivation areas, improve productivity, and conduct research and development to introduce new mushroom varieties and enhance product quality. Although the mushroom business in Malaysia is still in its initial phases, the country's favorable agro-climatic conditions make it suitable for year-round mushroom cultivation. Consequently, Malaysia possesses the potential to emerge as a notable global player in mushroom production, capable of competing in the international market. Nonetheless, this business faces several concerns and obstacles. This project involves the algorithms of image processing to detect oyster mushrooms from cameras implemented at the machines. The project focuses on automating the initial stage of picking and placing oyster mushrooms using a programmed system. This involves employing algorithms to detect oyster mushrooms through the utilization of a camera. Object detection is achieved by implementing YOLOv5, an open-source Artificial Intelligence framework, throughout the project. The performance of the detection system is evaluated by comparing the results obtained with different numbers of epochs and confidence values in detecting oyster mushrooms. YOLO provides higher speed in image detection. For the development of AI, the development is divided into two phases which are for image processing and motion control. This project will focus on the first phase, where open-source AI, YOLOv5 will be trained using datasets and use microcontroller as the main processor