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AIOFARM: Using AI for Sustainable Crops

Updated: Jun 27

Established in 2021, AIOFARM is an artificial intelligence company that creates technology to improve the agricultural industry. By assessing their customers’ needs, they provide services that will help producers and consumers in the agriculture industry with specialized solutions using AI. Their vision is to provide the highest quality of integrated sorting solutions by creating customer-oriented AI through self-designed systems.

Specifically, they use their AI system, called AIOVISION, which can sort data based on size, color, defects, and abnormalities. AIOVISION is installed on storing devices in a modular form and uses integrated monitoring on normal and defective produce. The system employs integrated monitoring with real-time AI screening to analyze specific images and numerical data related to normal and defective produce. While it thoroughly assesses the ratio of each defect, it also allows for data accumulation and input for individual products. Generally, traditional inspection systems process the light spectrum reflected from the raw materials using computer equations, requiring multiple sensors. However, AIOFARM’s system differs from standard systems by utilizing deep learning to analyze color images, enabling it to detect various forms of defects without the need for multiple sensors. This approach offers advantages such as lower cost, simultaneous analysis of visually distinguishable weaknesses, and higher accuracy compared to other inspection systems.

By harnessing the capabilities of AIOVISION, farmers can gain a significant competitive advantage and boost their income through improved product quality. This powerful technology also enables farmers to address defects in their crops promptly, ensuring that only high-quality products reach the market, raising customer trust and satisfaction. As their CEO Hojae Gwak stated, “AIOFARM is a company that embodies my concerns about sustainable agriculture.” Through utilizing their AI system, AIOFARM revolutionizes sustainable agriculture practices and empowers farmers to optimize productivity, minimize waste, and deliver high-quality products to the market.

Beyond being able to provide customer-specific AI based on their needs, AIOFARM’s technology also excels in efficiency and precision. In 2022, they received the Prime Minister Award and 20 million won in the Agri-Food Entrepreneurship Contest hosted by South Korea’s Ministry of Agriculture, Food and Rural Affairs. Their specialized artificial intelligence system employs vision inspection techniques to sort up to 33,000 agricultural products per hour, such as apples and peaches, achieving a precision rate of 99%. This system is highly anticipated to address the challenge of labor shortages when large quantities of agricultural products are harvested simultaneously.

Furthermore, organizations such as the TIPS program (Tech Incubator Program for Startups), IVX Lab, and JB Ventures have invested in AIOFARM and its mission. AIOFARM also recently signed a business agreement with the Rural Development Administration National Institute of Horticultural and Herbal Science to collect data and standardize quality control for crops, while also promoting a demonstration project for a smart agricultural distribution center. Lee Ji-won, the director of the National Institute of Horticultural and Herbal Science said, “If research institutes researching various items and companies with technologies join forces, it will be possible to advance the smart agricultural distribution center and provide an opportunity for domestic agricultural distribution to take a leap forward.” As Lotte Mart and Lotte Super announced in May 2023 that they would begin releasing apples sorted using AI, these connections and technology highlight the valuable connections and technology that AIOFARM brings to the industry. These collaborations and technological advancements position AIOFARM at the forefront of agricultural innovation and pave the way for groundbreaking strides in agricultural distribution.


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