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【2020 Application Example】 AI Bread Recognition System, machine scans, and the price is instantly calculated for you!

A brilliant idea transforming AI facial recognition technology

As artificial intelligence develops, more and more industries are embracing AI technology, even subtly entering into people's lives. As most bakeries sell freshly made bread and pastries, which typically do not have barcodes, they rely on cashiers to visually identify each item and enter the type and price of the bread. Thus, inspired by AI facial recognition technology, if such artificial intelligence could identify hundreds of types of bread, it could enhance checkout efficiency...

Diverse handmade breads delight customers but challenge clerks!

A local bakery has over 100 types of bread, regularly updating or adding new products, offering customers a variety of choices; this poses a challenge for cashiers.

It takes two months to train a cashier, but even after they start, there's still a 5 to 10% error rate due to bread recognition mistakes each month, especially during peak checkout times after work, causing bottlenecks and further errors due to the stress on cashiers. The difficulty in training cashiers and the lack of precision in the checkout process have long troubled businesses...

When baking meets artificial intelligence, it sparks a marvelous retail experience!

In typical bakeries, bread is sold 'naked' immediately after baking and then 'packaged' when it cools to room temperature. Both methods require cashiers to recognize and remember the prices and undergo two months of training before they can work the cash register. Even then, there is still a 5 to 10% error rate each month. My Dee Bakery, with its extensive range of over 100 bread types, poses a significant challenge for cashiers!

Due to Yun Kui Technology Co., Ltd.'s expertise in developing iPad POS systems, which are designed to be simple, convenient, and easy to use, they allow businesses to check out efficiently and accurately. Therefore, integrating the existing POS system with AI image recognition capabilities enables businesses to carry out transactions more efficiently and precisely.

AI bread recognition model operational schematic (Image provided by Yun Kui Technology)

▲AI bread recognition model operational schematic (Image provided by Yun Kui Technology)

The execution can be simplified into eight steps, which include:

1. Data collection: Take bread image data at bakeries.

2. Image annotation: The image data is handed over to Mu Kesi Co., Ltd. for manual annotation.

3. AI modeling and training: Managed by Mu Kesi, who adjusts AI models and training.

4. iPad POS adjustment: Simultaneous adjustments of the UI interface on the POS side and backend integration with the AI model.

5. Start testing: Once Mu Kesi reaches over 95% recognition accuracy with current data, formal integration testing begins.

6. Real scene testing: Move to the bakery to gather data and verify the correct recognition rates.

7. Planning real scene application accessories: When recognition accuracy exceeds 98%, design accessories for on-site checkout, such as remote cameras and projection light sources.

8. Official Application: Integration with electronic receipts goes live.

POS machine AI bread recognition checkout process: Start recognition - Recognition complete - Checkout - Confirm checkout, takes only 3 seconds (Image provided by Yun Kui Technology)

▲POS machine AI bread recognition checkout process: Start recognition - Recognition complete - Checkout - Confirm checkout, takes only 3 seconds (Image provided by Yun Kui Technology)

AI bread recognition system, making multitasking easy!

After adding AI capabilities, not only can it save upfront training time and costs for bakery cashiers and reduce costs from recognition errors, but it can also speed up the checkout process and efficiency, increasing customer satisfaction. This can later be promoted to various retail industries, expanding the new map of smart retail.

Comparison chart of bread checkout process before and after AI valuation (Image provided by Yun Kui Technology)

▲Before and after comparison chart of the bread checkout process with AI valuation (Image provided by Yun Kui Technology)

「Translated content is generated by ChatGPT and is for reference only. Translation date:2024-05-19」

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Droxo Tech Applies Drones in Golf Courses to Reduce Manpower by Half

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internal and external resources Only then will we be able to gradually achieve the goal of making golf courses smarter and smoothly assist the industry with transformation Zuoyi Technology's CEO, Liu Junlin 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

這是一張圖片。 This is a picture.
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In recent years, global climate change and environmental issues have become increasingly severe, causing major impacts on agricultural production Traditional agriculture heavily relies on weather conditions, facing challenges such as unstable crop quality, plummeting yields, and difficult pest control Particularly in Taiwan, agricultural biotech companies and farmers have suffered continuous losses, creating an urgent need for innovative solutions Meanwhile, Taiwan's plant factory industry faces many challenges high equipment and labor costs, an incomplete industrial chain diminishing international competitiveness, and a lack of cooperation among enterprises, all of which limit industry development Additionally, COVID-19the pandemic has highlighted the importance of remote monitoring and management Traditional manual inspections and data collection methods no longer meet the needs of modern agricultural production These issues collectively underline the urgent need for smart 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that is often disorganized, difficult to interpret and apply Human resource challenges are also severe, with young people generally lacking interest in agricultural work, making it difficult for them to recruit employees with modern agricultural skills Even existing employees often feel exhausted from tedious manual operations and monitoring tasks These problems are intertwined, creating a complex dilemma that leaves plant factory operators confused and anxious They urgently need a comprehensive solution that can enhance factory operational efficiency, reduce costs, and improve product competitiveness, helping them overcome difficulties and regain their footing in the fierce market competition In facing the various challenges of plant factory operators, Taiwan's HaiBoTe company has demonstrated exceptional technical innovation and a flexible customer-oriented development strategy They deeply understand that the solution must be able to seamlessly integrate existing equipment while 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HaiBoTe's developed smart agriculture solution not only brought revolutionary changes to plant factories but also painted an encouraging picture for the future of the entire agricultural industry The excellence of this system is evident in several aspects firstly, it achieves precise control of the plant growth environment, significantly improving crop yield and quality stability Through advanced artificial intelligence algorithms, the system can forecast and adjust optimum growth conditions based on historical data and real-time monitoring information, ensuring each plant grows in the ideal environment Secondly, it significantly reduces energy consumption and operational costs, improving resource efficiency The intelligent management system optimizes water, electricity, and nutrient supply, reducing waste and lowering manpower costs Additionally, the system's modular design and strong compatibility allow it to seamlessly integrate various new and old equipment, providing a flexible solution for gradual upgrades of plant factories Most importantly, the system injects a sense of technology and modernity into agricultural production, helping to attract the younger generation to the field and injecting new vitality into the industry Looking ahead, HaiBoTe's smart agriculture system has broad application prospects and expansion potential In addition to plant factories, this system can also be applied to traditional greenhouse cultivation, urban agriculture, and even home gardening In the field of aquaculture, similar technology can be used to monitor and optimize the breeding environments for fish or shrimp In the food processing industry, similar intelligent monitoring and forecasting systems can be used to optimize production processes and enhance food safety Even in the pharmaceutical industry, this type of precise environmental management system could be applied to drug research and production processes To further promote this system, HaiBoTe could adopt a 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technology empowering agriculture 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-12-09」