Muscat – A group of students from the College of Engineering at Sultan Qaboos University (SQU) has developed a system that employs artificial intelligence (AI) technology integrated with robotics to identify quality of dates.
The student project’s objective is to enhance food quality by leveraging AI for automated food inspection and sorting processes. It aims to increase factory production capacity, reduce time required for inspection and sorting of dates, and boost food security.
Team member Asaad bin Saeed al Hinai highlighted the importance of the date industry in Oman as a crucial source of income and trade. However, date producers encounter challenges, particularly in the sorting process, including identifying dates unsuitable for human consumption.
Hinai emphasised the role of AI in improving the sorting process in factories and described the new system’s implementation of computer vision algorithms and robotics.
The system developed by the team automates the sorting of dates using AI, distinguishing edible dates from spoiled ones by identifying the condition of dates passing through the production line. It directs fruit to the appropriate path in the production line while keeping count of the sorted dates, both fit for consumption as well as the spoiled ones.
Ahmed bin Mohammed al Habsi, another team member, elaborated on the sorting process detailing how dates are introduced into the production line via a conveyor belt and photographed from above using a high-resolution camera. “Computer vision algorithms differentiate between good and bad dates, after which the dates are sorted through specialised gates.”
Saleh bin Yahya al Ghanami, yet another team member, spoke of the challenges faced by factories in manually sorting spoiled and unusable fruit, which can be economically burdensome and compromise quality. He highlighted the fact that the system’s performance is evaluated based on sorting speed and error rates. It has demonstrated enhanced efficiency of date sorting compared to traditional methods.
Additionally, the team has noted the potential of introducing AI systems in other sectors, particularly in inspection and quality control operations in factories that require precise examination of product quality.
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