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【2021 Solutions】 Hyson Technology uses AI to help fishermen farm fish

Lian Wei-Cheng, the founder and CEO of Hyson Technology, was once an IC design engineer in the semiconductor industry, working in front of a computer all day long in Hsinchu Science Park. Although he was busy, he still had a sense of uncertainty and felt anxious about his life goals. He couldn’t help but think about whether the technological capabilities he learned can directly connect with people and the land, solve various social issues, improve human life, and further change the world.

He took the plunge and left the semiconductor industry, a job that everyone envied, and founded Hyson Technology. He stayed at the fish farms in Qigu, Tainan, his hometown for a long time, and built relationships with the fishermen. He was eventually able to talk about "fishing knowledge" and gained the trust of the fishermen. The "Aquaculture Monitoring and Rearing System" was developed by Hyson Technology by combining artificial intelligence (AI), Internet of Things (IoT), and mechanism design. The system uses a method friendly to fish, shrimp, and the environment to reduce risk and increase yield, achieving sustainable farming production.

Schematic diagram of the AIoT aquaculture rearing management system of Hyson Technology

▲ Schematic diagram of the AIoT aquaculture rearing management system of Hyson Technology

Lian Wei-Cheng, who was wearing a sun hat and walking among the fish ponds under the scorching sun, was asked: Why did you make the change from the tech worker to an entrepreneur who helps fishermen farm fish? He answered shyly with a smile: The chairman of a certain semiconductor company also asked him the same question. "I want to have more contact with people, directly understand people's needs, and find places where technology is needed to improve people's lives," he said, so he resolutely left his envied job in the semiconductor industry and became "half tech worker, half fisherman."

The annual output value of Taiwanese fishermen is relatively low, but there is great potential to increase output value through technology

Why did you choose aquaculture for entrepreneurship? Citing a report in "CommonWealth Magazine", he pointed out that to show the value of an industry, we can observe whether the industry has prospects based on the per capita annual output value of employees. For example, Qualcomm has a per capita annual output value of NT$23 million, and Microsoft is NT$23 million. The per capita annual output value of Norwegian fishermen reaches approximately NT$24 million, which is three times the per capital annual output value of Taiwan's electronics industry (NT$8 million). The current average of Taiwan's aquaculture industry is only about NT$400,000. There is considerable room for growth from NT$400,000 to NT$24 million.

Thinking about it from another perspective, Taiwan’s electronic hardware and IoT equipment technology lead the world. If these technologies can be combined to give smart aquaculture full play, the average annual output value of fishermen is expected to increase significantly. The expertise of Hyson Technology’s team is AI image processing technology and data analysis technology. They use these technologies to solve the risks and labor problems caused by not being able to see fish and shrimp underwater. The team sets out from being able to see, to measure, and to control, and allows fishermen to quickly monitor the growth status of fish and shrimp using their mobile phones. It can also be combined with automated equipment to reduce labor and risks.

When Lian Wei-Cheng was a student in the Department of Electrical Engineering, National Cheng Kung University, he loved raising ornamental fish and watching birds, often going to Qigu to watch birds. He observed the environment and found that more and more fish farms in Qigu were being abandoned. This was mainly due to two major factors, one is that it is difficult for young people to enter the industry without experience. The other is that the older generation did not keep records and it is difficult to pass on experience. This has resulted in an aging population in Taiwan’s fishing villages and prevented an increase in output volume. The most effective way to solve the problems above is to introduce an automated system to assist with fish farming.

Hyson Technology's fish farming system uses self-designed IoT underwater cameras to monitor fish in the farms. It also uses Edge-AI image defogging technology to make the images of fish in ponds clearer, allowing fishermen to use their mobile phones to see fish activities and feeding, and determine if the fish are sick. The images are synchronized to the cloud, and Cloud-AI automatically identifies, samples, and measures biological information, such as the length and weight of each fish, automatically recording and compiling statistics of the growth status of the fish. The information is visualized in reports and images. It can also analyze the feed conversion ratio in different farming stages. The AI expert system can also predict harvest dates based on growth data, control sales and shipment schedules, and ensure stable and sufficient supply.

The fish farming system is like a ruler, taking into account every detail of fish farming

The fish farming system creates an objective ruler for the fish farming industry. Using this ruler, fishermen can measure and compare the effects of different farming methods, see parts that they have not paid attention to before, and create more usages and value. In the past, the traditional approach of manually catching fish samples was labor-intensive and time-consuming. It usually took two people an hour to sample only 30-40 fish, and often caused accidental fish casualties. Field verification results show that Hyson Technology’s fish farming system can automatically sample and measure the biological information of 300 fish in 5 minutes without disturbing the activities of the fish. It is extremely efficient and can ensure zero damage to the fish.

Fish farmers use the system’s AI growth statistics as the basis for decision-making in determining the size of fish entering the pond and shipping. It replaces the original traditional method of manually catching and measuring 30 fish, which can save about 75% of manual work time. In the fish farming industry with extremely scarce manpower, the benefits of saving manpower are very significant. Hyson Technology is gradually expanding the AI technology it developed to other fields. For example, Hyson Technology participated in the AI+ New Talent Selection of the Ministry of Economic Affairs Industrial Development Bureau’s AI Program, in which major companies provide problems and startups provide solutions.” The company combined its proprietary fully automatic AI underwater image defogging algorithm with an AI model, and applied it to the solution of an optoelectronics company for removing rainbow film from LED panels. The company thus won the biggest award for meeting all technical thresholds.

Lian Wei-Cheng pointed out that the defogging technology can automatically estimate the degree of color distortion in water and automatically adjust the contrast of each area to improve image quality. Compared with AI models that consider underwater physics and methods based on adversarial network model, the method proposed by Hyson Technology provides clearer image details, and also received better scores in multiple objective image quality evaluation standards, such as NIQE and PSNR.

Underwater image defogging algorithm favored by major companies due to its superiority

This defogging technology combined with AI technology can effectively improve the accuracy of fish recognition. For groupers with colors similar to the background and difficult to distinguish, the accuracy can be significantly increased by more than 3%. For batfish with clear features and high recognition accuracy already reaching 98% and above, the accuracy can be further increased by nearly 1%. Using this technology to make the images of farmed fish clearer, it can be used as the basis for determining fish diseases. If the technology for underwater defogging is built into the AI model recognition layer, it can also be used to solve the problem of rainbow patterns appearing when taking photos of screens, which prevents panel defects from being detected. This will effectively solve the problem of AUO with rainbow pattern interference during panel inspection.

What are the challenges of Hyson Technology in business promotion? Lian Wei-Cheng believes that the biggest difficulty is how to expand into a new industry. Hyson Technology often faces customers from traditional industries. When recommending or cooperating with traditional industry customers on a new technology product, the key is gaining the trust of customers and achieving the goal of customers are partners. Frequent visits are needed to gradually build trust and understand customer needs. Only then will the company have the opportunity to further assist customers in solving their pain points.

Hyson Technology's excellent image recognition and AI technologies have gradually gained recognition from customers. It has built relationships with major companies in verification, and it will continue to gain a foothold in the market in the short term with its own image processing products, such as the fish farming system. In the medium term, it hopes to expand the scope of products and business services, and provide one-stop production and marketing services from underwater to on land, and from the production end to the consumer end. In the long term, Hyson Technology will duplicate its successful experiences in Taiwan and integrate resources of partners to expand into the international market.

Lian Wei-Cheng, founder and CEO of Hyson Technology, working in a fish farm

Lian Wei-Cheng, founder and CEO of Hyson Technology, working in a fish farm

Lian Wei-Cheng and Chiu Yu-Shao join the ranks of smart aquaculture with their technological expertise

Lian Wei-Cheng and Chiu Yu-Shao join the ranks of smart aquaculture with their technological expertise

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【解決方案】2秒鐘完成結帳動作 Viscovery AI影像辨識助攻智慧零售
Complete checkout in 1 second, Viscovery AI image recognition assists smart retail

Artificial intelligence AI has gradually changed the way various industries operate in recent years However, most of the work is still done by humans, with AI playing a supporting role This has led to emergence of the term "AI Copilot," which stands for "AI-driven tools or assistants" that aim to assist users in completing various tasks and improve productivity and efficiency The concept of AI Copilot comes from the role of "co-pilot" During flight, the co-pilot assists the main pilot in completing various tasks to ensure flight safety and efficiency In fact, there have been signs of various "machines" beginning to play the role of "copilot" in different fields since the Industrial Revolution, assisting humans in completing heavy physical and repetitive tasks, greatly improving factory production efficiency, and driving rapid economic development Following the advancement of computing equipment and breakthroughs in machine learning, deep learning, and image recognition technologies, the concept of AI Copilot has gradually taken shape The development of AI Copilot marks the transition from "machine-assisted to AI-assisted" Early robots could only complete preset repetitive tasks, but today's AI copilot can learn and adapt to new environments and tasks, and continuously optimize its performance in practical applications This transformation not only changes human-machine interactions, but also has a profound impact on various industries The application scope of AI copilot covers various industries, including finance, healthcare, manufacturing, education, retail, etc, and are everywhere to be seen Application of AI copilot in the retail industry AI image recognition checkout In the retail industry, the application of AI copilot has begun to show concrete results Take Viscovery's AI image recognition checkout system as an example This system is a type of AI copilot model that helps store clerks speed up checkout or assists consumers in simplifying the self-service 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effectively shortened Even for products with barcodes, AI can quickly identify multiple items in one second, which is more efficient than scanning barcodes one by one The self-checkout system "assisted" by AI image recognition allows consumers to successfully complete shopping without the help of store clerks, eliminating the trouble of swiping barcodes or searching for items on the screen, which improves the shopping experience In a time when store clerks are hard to hire due to labor shortage, this also helps stores reduce operating costs AI quickly identifies multiple checkout items in just one second Source of image Viscovery Recently, startups dedicated to developing AI image recognition checkout solutions have emerged in various countries The most lightweight solution currently known is in Taiwan It can be immediately used by installing a Viscovery lens and a tablet installed with Viscovery AI image recognition software at the checkout counter to connect to the store's existing POS checkout system There are various integration methods, including plug-and-play and API solutions integrated with the store's POS system Viscovery AI image recognition system can be painlessly integrated with the store's existing POS system Source of image Viscovery Example of AI image recognition checkout Currently, the Viscovery AI image recognition system is being used in bakery chains in Taiwan, Chinese noodle shops in Singapore, micromarkets in department stores in Sendai, Japan, and Japanese bakeries and cake shops Over 7 million transactions were completed through this AI system, which identified more than 40 million items These use cases demonstrate the extensive application of the Viscovery AI image recognition system in the retail industry In the future, the company will continue to explore the various possibilities of using Vision AI in retail and catering nbsp The Viscovery AI image recognition system is already being used in bakeries, cake shops, restaurants, and convenience stores in Japan, Singapore, and Taiwan Source of image Viscovery

【解決方案】小柿智檢 以「AOIAI」雙劍合璧,軟加硬體千錘百鍊 打通外觀瑕疵檢測任督二脈
Xiaoshi Intelligent Inspection uses the two swords of "AOI + AI" to combine software and hardware to open up the two channels of appearance defect detection and supervision.

Quality inspection, like a double-edged sword, has always been a favorite and painful subject for Taiwanese manufacturers When AI deep learning enters the industrial visual inspection of traditional manufacturing industries, it can not only save inspection manpower investment, solve the problem of inconsistent manual visual standards, overcome the limited visual recognition and defect detection blind spots of traditional automatic optical inspection AOI, and also enable real-time traceability Causes of quality problems The overall AIAOI visual inspection solution developed by Xiaoshi Intelligent Inspection integrates software and hardware to create efficient appearance defect detection capabilities, helping electronics OEM customers create high-efficiency products with a miss detection rate of less than 1 and an overkill rate of less than 3 Check the level Xiaoshi Intelligent Inspection was established in 2020 Although it is a new venture two years ago, it did not start from scratch Founder and CEO Hong Peijun and the core team have been deeply involved in Foxconn factories for many years and participated in countless smart factory-related solutions and process improvements , has profound AI deep learning development capabilities, and accumulated rich experience in world-class AI application implementation Seeing that AI industrial inspection must be the last mile for the manufacturing industry to move towards Industry 40, Hong Peijun resolutely decided to implement AI deep learning technology in the field of smart manufacturing with high output value, and specialized in the development of AI industrial visual inspection For the manufacturing industry, product inspection is the most important part of all quality control, but traditional industrial inspection faces two major pain points 1 Manual visual inspection Today, more than 95 of the entire manufacturing industry still relies on manual visual inspection Inspection makes it difficult for manual visual quality inspection standards to be consistent, and visual inspection of fine objects, such as passive components or highly reflective components, will cause long-term vision damage 2 Traditional AOI automatic optical inspection The product has limited visual recognition capabilities and blind spots in defect detection Among them, the detection of appearance defects such as scratches, oil stains, dirt or hair and other unexpected subtle defects has always been a problem in AOI applications Insurmountable difficulties AIAOI visual inspection overall solution is a great boon for appearance defect detection When designing the product roadmap of Xiaoshi Zhikan, customer group positioning and strengthening customer product services and value were important indicators Moreover, appearance defect detection has always been an unresolved pain in the manufacturing industry, Hong Peijun said With industrial quality inspection AI software as the core, Xiaoshi Intelligent Inspection provides an overall solution for AIAOI visual inspection It mainly promotes three major products, including "QVI-T AI deep learning inspection modeling platform software" and "AI six-sided defect inspection and screening machine" ” and “AI Industrial Quality Inspection Platform” The main customer groups served are semiconductor packaging and testing, EMS electronics foundry, small metal parts processing and other industries with high production capacity and high gross profit margin In response to customer needs, Xiaoshi Intelligent Inspection provides corresponding software and hardware services, combining self-developed AI deep learning software and hardware quality inspection equipment to reduce the manual visual burden on the production line and effectively improve the production quality of the factory In order to help equipment manufacturers and technical engineers with development capabilities accurately grasp product appearance defect detection, Xiaoshi Intelligent Inspection independently developed QVI-T deep learning detection software, which can provide customers with defect location, defect classification, defect segmentation, anomaly detection and text recognition Key functions such as this are different from the fixed detection methods of traditional software Algorithms can be refined based on different industrial detection methods and different APIs can be developed to connect devices with different lenses The software design of this platform is very lightweight It is a SaaS software built on public cloudprivate cloud It mainly involves simple image uploading, labeling, training modeling, and verification testing After completion, users can download models, SDKs, APIs, and reports Effectively help customers achieve AI inference functions Currently, most of the industrial inspection services on the market are traditional AOI software industrial inspection machines, which can only measure product contours such as the head and length of fasteners, etc, and cannot truly provide detection of subtle product surface defects such as screw head cracks and tooth damage There is a lack of such high-precision defect detection companies in the market, Hong Peijun observed Xiaoshi Intelligent Inspection developed and independently built the "AI six-sided defect detection and screening machine" from customized services in the past to providing standardized services for customers at the current stage It provides standardized testing services for fasteners in measurement and surface defects, as well as passive components High-speed surface defect detection of similar products This professional machine uses the AI deep learning AOI composite algorithm technology independently developed by Xiaoshi Intelligent Inspection Through parallel computing technology, it can achieve model inference up to 3 milliseconds per picture, and realize multiple complex defect detection on the electrodes and body of passive components This professional machine is mainly used for the inspection of fasteners, small metal parts and passive components In terms of competitiveness in the industry, the software hardware integration provided by the AI six-sided defect inspection and screening professional machine is an important core competitive advantage of Xiaoshi Intelligent Inspection It is not as simple as it sounds Hong Peijun said with emotion that this special machine is very important in the industrial inspection industry Commonly known as the highly integrated integration of optical mechanisms, electronic controls, software and algorithms, the process requires continuous optimization and iteration, and requires multiple client verifications and modifications After a long period of hard work, the technical threshold has also been raised The AI six-sided defect detection and screening professional machine will be the main product promotion direction of Xiaoshi Intelligent Inspection in the next 3-5 years It is believed that AI combined with measurement technology and surface 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the introduction of AI visual inspection software and hardware integrated solutions, we have effectively helped customers maintain an overkill rate of less than 3 in the past two years, and achieved high-efficiency performance with a missed detection rate of less than 1 In addition, this solution allows practitioners who do not understand AI to quickly operate modeling By installing the modeling tool on the device, when the customer has a new product number and needs to create a model, he only needs to provide 10 pictures of good products to scan under the device It only takes 15 minutes to quickly train the model In terms of product core strategic layout, compared with market competitors who rely solely on general software services to seize all manufacturing markets, it is not feasible to apply it to industrial inspection Hong Peijun has observed over the past 10 years and believes that only software hardware can With technical thresholds and focusing on one industry and field, only 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more standardized and sell them to overseas markets, the company will conduct a fundraising plan at this stage, hoping to use legal persons such as the Capital Strategy Council to assist in more business connections and fundraising channels For the medium and long-term goals, Xiaoshi Intelligent Inspection will lay out the global market including mainland China and Southeast Asian countries At the same time, it will follow the international footsteps of major OEMs in global layout Under the target inspection project, it will continue to develop specialty products and spread towards the international field 「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.
AI Smart Health Prevention Plan

Herji Ltd held an interactive teaching session with AI storybooks at the 'Taiwan Early Childhood Development and Remedial Association Taitung Office', allowing children, teachers, and parents to engage in immersive educational experiences AI-generated children's educational storybook materials AI Learning Platform In recent years, changes in the social structure of Taiwan, combined with experiences in hospital emergency departments, have often led us to overlook the depressive symptoms exhibited by adolescents, resulting in tragic incidents of self-harm or even suicide among children A significant part of children's depression stems from their academic performance, with parents worrying about their children's future competitiveness, thus placing a lot of pressure on children who perform poorly academically In a family with two children with the same genetic background and provided with the same resources for growth, we often find that the second child's academic performance is not up 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accumulates a lot of negative emotions in children during their developmental process, which in turn affects various factors impacting their health In reality, the main reasons behind a child's poor academic performance, inability to learn, lack of interest in learning new things, or even developing health-impacting psychological conditions, actually stem from accumulated learning delays during early childhood The period before the age of six is considered the golden window for treating learning delays If these can be identified and addressed during this time, there is a chance that the child's learning abilities can be greatly improved10The industry's current pain points are as follows 1Lack of methodologies for assessing learning abilitiesLack of databases for sample comparisons in the market 2Traditional parental misconceptionsFear of labeling and treatment delays for mild to moderate cases 3Lack of therapeutic materials and toolsShortage of therapeutic storybooks and series courses This project will develop a national talent development support system, utilizing AI Technological development of a system for assessing children's learning abilities that supports parents in safeguarding their children's health from the start of learning ability testing, offering early detection and treatment In the future, all Taiwanese children, regardless of background, will be able to establish a healthy foundation in early childhood, growing up to become valuable assets for national development 2、 As proposed in this planAIApplications and explanations 'Child Language Ability'AI'Analysis Model' This model quantitatively analyzes 'the condition of children's use of Mandarin' when 'expressing an event' Scenario Preschool teachers guide children in narrating storybook contentAITools analyze the sentences used by children to describe storybook content, applying statistical algorithms for quantitative analysis Analysis indicators include 'sentence type' and 'lexical items' Analysis 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abilities 4、 Expected Industrial Benefits Economic Benefit and Future Spread and Impetus By supporting children with delayed learning abilities, enhancing their learning prowess through this project, these children serve as the future of our nation and can thus significantly contribute to national talent development Furthermore, the purpose of establishing a learning ability development base is to help reunite children with their parents, increasing their interaction time, allowing the children to move beyond mere one-dimensional interactions 3C This facilitates two-way interactions between the child and parents, potentially impacting children who may have been otherwise delayed in developing their capabilities due to environmental factors 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-11-15」