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Special Cases

20
2020.3
【2020 Application Example】 Intelligent Prescription Recognition: A Helpful Tool for Community Pharmacy Pharmacists

AI is thriving in healthcare services, where pharmacists in community pharmacies are essential for providing drug knowledge and pharmaceutical services However, these pharmacists often spend much time manually processing prescription entries into systems, which takes away from the time they could spend on drug education, medication effectiveness tracking, and other professional services How can AI help community pharmacies to support pharmacists Tedious, time-consuming, and repetitive tasks, and AI solutions Pharmacy operations are under threat from new market dynamics and limited profit-making modes, making digital upgrades challenging for single-pharmacist community pharmacies Pharmacists, taking on multiple roles to understand the health levels of community residents, face tedious, time-consuming, and highly repetitive tasks that hinder the quality of service and make it difficult to respond to customers non-stop all year round Smart Pharmacist Assistant Service Platform Enabled by Jiankangli Technology's smart pharmacist assistant service platform's system architecture, paired with the mobile application 'Smart Good Doctor' and the backend system 'Smart Good Pharmacist', along with the integration of external development feature resources 'OCR Prescription Recognition' and 'RPA Process Automation Training Module RPA library' Primarily applied in clinics and pharmacies at the primary healthcare level, this aims to solve various operational challenges and pain points It includes using digital technology to improve work efficiency, bridging the gap between the public and medical institutions, enhancing the medical relationship, achieving better operational and manpower benefits Additionally, it enhances medication safety for the public and improves their knowledge on medications, while also reducing the daily burden on pharmacists in pharmaceutical services Smart Pharmacist Assistant Project In the current stage, the Institute for Information Industry's team is guiding the integration of pharmacy information system vendors with AI startups, focusing on the development of intelligent prescription image recognition technologies, along with drug image recognition and smart drug scheduling reminder technologies as key research areas This has led to the implementation of practical deployments in 12 community pharmacies in Greater Taipei With the help of the Taiwan Young Pharmacists Association in promoting these technologies, over 100 community pharmacy proprietors have expressed interest in adopting such technologies Once the integration of these service platform systems is complete, it will become a model for promoting AI services in Taiwan's community pharmacy pharmaceutical services「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

2020-03-20
【2021 Application Example】 Optical industry AOI imports AI Great Leap Forward to completely solve the pain points of lens defect detection

The stay-at-home economy such as smartphones and remote working is booming, and the information and communication industry is booming, driving the optical industry to flourish However, the defect detection of optical lenses is mostly carried out by human eyes, which is not only time-consuming and labor-intensive, but also limited by the fact that human eyes are prone to fatigue The misjudgment rate is also a lingering pain point for the optical industry Benefiting from the evolution of AI technology, Shangyang Optics introduced diffraction optical technology for shooting, used the images captured by the system as the data source, introduced AI model training, and integrated the camera system and image recognition into a production line workstation, greatly improving defect identification The rate is as high as over 90 Taiwan’s optical production value accounts for 10 of the world’s, and the application range of precision optics is expanding day by day The optical industry is a mainstream product in consumer electronics Even though Taiwan was affected by the Sino-US trade dispute in 2019, the output value of optoelectronics still reached US463 billion, accounting for 10 of the world's total Among them, the "precision optics" segment accounts for NT87 billion approximately US29 billion in output value In view of the increase in the number of smartphone lenses, precision optics still maintains a sustained growth of 4 compared to the decline in other fields Since Sharp launched the world's first camera phone equipped with a rear 110,000-pixel lens in 2000, end consumers' requirements for smartphone camera performance have continued to increase, and with the wave of 5G high-speed Internet The advent of the technology has led to the activation of application markets such as augmented reality AR or virtual reality VR The innovation and application of its technology have added a lot of momentum to the optical industry, and the application fields have extended from smartphones to popularization to the mass consumer markets such as automobiles and home entertainment Optical lenses are inseparable from the economic development of "precision optics" As semiconductor technology continues to mature and network speeds continue to increase, optical lenses are used not only in smartphones, tablets, traditional cameras, projectors, In the field of people's livelihood vehicles, the demand for engineering visual inspection and security applications in high-precision manufacturing processes continues to grow rapidly Optical lens defect detection is mostly done manually "Optical lenses" are essential components of the overall optical-mechanical system The lens finish inspection after incoming materials and before shipment not only affects the overall production line efficiency development, but also has an impact on the quality commitment of end customers that cannot be underestimated For a long time, the optical industry has mostly used human eye detection for defect inspection As production volume continues to increase, not only labor costs continue to rise As inspectors age, their eyesight gradually declines, and the misjudgment rate increases every year In addition, manpower recruitment has been difficult in recent years Even if they are lucky enough to be recruited, it is not easy to develop the inspection technology, and the training time is lengthy, making it impossible to respond to the production line manpower needs in a timely manner Introducing diffraction optical technology and AI training model to improve defect recognition rate to more than 90 The current market is flooded with a large number of automated optical inspection systems, and there are many substantial cases of lens defects However, after years of market exploration and evaluation by Shangyang Optics, this system still cannot solve the current manual inspection problem The main reason is that the appearance of the optical lens is curved and transparent, and it is not easy to photograph various defects, and once the defects are around There is interference from other stray lights, making judgment more difficult Moreover, different types of lenses need to be individually rotated and lit and adjusted according to the defect status before entering the judgment stage The labor consumption ratio is still high, which is not in line with the efficiency and cost Through this, through the matchmaking of the AI project execution team of the Industrial Bureau of the Ministry of Economic Affairs, Xiaoma Optics assisted Shangyang Optoelectronics in establishing an effective defect photography system Pony Optics provides guidance on precision diffraction optics Based on the characteristics of "light" fluctuations, lens defects can be obtained through a unified lens shooting method Current photography systems on the market mostly use geometric optics Geometric optics uses linear light and is not easy to capture defects such as missing coatings, tiny scratches, and liquid dirt The cooperation plan introduces diffraction optical technology for shooting Through precise imaging from all angles, it can achieve higher contrast and better noise reduction than ordinary geometric optical elements, so as to obtain the necessary defective images Schematic diagram of optical lens scratches and defects In order to improve the more detailed defect detection and recognition rate in this case, Shangyang Optics used the image captured by the system as the data source, imported AI model training, and integrated the camera system and image recognition into a production line workstation, which not only improved the defect recognition rate Reaching more than 90, it is more conducive to the subsequent development of automated production lines The AI model training for this cooperation project is provided by Yirui Technology Currently, most manufacturers have introduced AOI systems for production line defect inspection Most of them use OCR optical character recognition, which refers to the analysis and recognition processing of image files of text data , the process of obtaining text and layout information technology needs to be 100 accurate, and there is no room for error, resulting in accidental killings often occurring After adding the AI training model, the optical lens defect recognition rate is greatly improved AIAOI solves the two major pain points of insufficient manpower and high misjudgment rate This time, Yirui Technology and Xiaoma Optics cooperated to install Yirui's AI system in the optical inspection instruments developed by Xiaoma Optics, adding AI algorithms to the optical detection of defects, and training based on the data and needs provided by customers AI model identification can greatly improve the accuracy of identification of defects, improve yield rate, and increase production line efficiency Through the tripartite cooperation between Shangyang Optics, Xiaoma Optics and Yirui Technology, the optical industry AOI is introduced into AI, hoping to completely solve the pain points of industrial lens defect detection Since setting up the production line in 2019, Shangyang Optics hopes to introduce a smart production model In view of the continuous growth of the company's operations and the continuous improvement of production volume, through the introduction and expansion of this achievement, the demand for manpower will be significantly reduced, and the impact of production scheduling can be reduced due to the high accuracy of the discrimination rate index, thereby improving production efficiency Shangyang Optics stated that as the development results are implemented, it will lead the technology to be promoted to upstream and downstream players in the optical industry, such as upstream optical lens raw material suppliers to downstream finished product applications, including immersive gaming equipment and related curved glass products , people's livelihood vehicle and security camera devices, etc 「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

2021-09-23
【2020 Application Example】 Dynamic License Plate Recognition System: Time-Saving and Convenient for Management

Jiude Songyi Company, with 40 years in motor-related equipment manufacturing, introduced a dynamic license plate recognition system with an accuracy rate of 989 to effectively monitor vehicles entering and exiting the factory area The system uses AI technology, making vehicle management both time-efficient and effortless License plate recognition systems are a fundamental application of intelligent image analysis Using cameras to capture images of license plates, the system then analyzes and processes these images to recognize the plates Kangqiao Technology, established in 2008 by a team of LED developers and software engineers, specializes in LED product applications, developed license plate recognition and Etag integrated systems, primarily for domestic and international public works projects Recently, the III AI Team collaborated with the Taiwan Energy Technology Service Industry Development Association to explore real-world applications of license plate recognition technology They identified three major issues faced by Jiude Songyi Company at this stage 1 Currently, the company gate has no barrier machine or other control equipment Vehicle entry and exit rely entirely on manual control and recording If no personnel are present, vehicle movements cannot be controlled 2 When issues arise, the existing surveillance system has to slowly search for data to locate the problematic vehicle, which is very time-consuming and inconvenient 3 When the footage is found, it is often difficult to clearly identify the license plate, and even if found, it is not possible to verify the vehicle owner Solving Three Major Problems, Providing Four Major Functions After understanding the actual needs of the enterprise, according to the license plate recognition system architecture established by Kangqiao Technology, real-world validation was conducted on-site, with monitoring computers set up in the control room Kangqiao Technology License Plate Recognition System Architecture After installation, the main functionalities of the license plate recognition system are as follows 1 When vehicles enter or exit, high-resolution smart cameras can identify license plates and capture images, recording the license number and vehicle status 2 When file retrieval is needed, vehicle data can be searched by time or license plate information, allowing quick access to the required video files, saving considerable time 3 The use of high-resolution smart cameras significantly improves image quality, which helps in clear identification in case of incidents 4 With registered license plate data, a blacklist and whitelist database can be set up, facilitating the management by security personnel The advantage of license plate recognition is that it fully automates vehicle entry and exit control, reducing labor costs The software helps to prevent misuse of license plates and eliminates the issues of remote control, induction buckle loss, and borrowing by unauthorized persons Vehicles can enter and exit without using a remote control or rolling down the window The long-distance license plate recognition allows gates to open while the vehicle is still moving, eliminating the waiting time for parking Kangqiao Technology License Plate Recognition System Setup in the Management Room The III AI Team states continually collaborating with relevant associations, from identifying corporate needs, setting topics, linking teams, introducing real-world validations, to systematically assisting enterprises in need to adopt AI technology and solve industrial problems, aiming for the AI transformation of industries In the future, it will continue to help enterprises harness technology tools to overcome business challenges「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

2020-03-19
【2021 Application Example】 AI Complements the Disruption of Traditional Industry Experience: Production Forecast Analysis in Plastic Recycling Process

As the number of veteran craftsmen in traditional industries diminishes In Taiwan, SMEs have always played a central role in Taiwan's industry, accompanying Taiwan through various 'economic miracles' periods But as time progresses, the old masters gradually became elderly craftsmen Coupled with the phenomenon of fewer children and changes in the overall industrial structure, fewer and fewer of the new generation are willing to enter traditional industries Now, it can be observed that the main combination on most SMEs' operational fields is formed by 'elder craftsmen' together with 'foreign workers' These experienced craftsmen, who act as living dictionaries of field experience, suffer from a lack of successors to continue the tradition, leading to a growing difficulty in sustaining on-site experience transfer in traditional industries The limits of traditional hands-on process optimization are in sight Located in Tainan Baoan Industrial District, 'Tangxian Company' was established in 1972, initially manufacturing high-quality weaving equipment It possesses the capability to manufacture machinery, and in recent years it has actively developed environmentally friendly plastic recycling equipment in response to international green energy, recycling, and environmental protection demands Ultimately, they have successfully developed low energy consumption, low waste, high purity, and high output recycling granulators with a sleek and efficient machine design supplemented by advanced intelligent control technology Tangxian Company's self-developed plastic recycling granulator equipment However, in the production process of plastic recycling, when faced with hundreds of material types and dozens of process temperatures, speed settings, what is faced is thousands of possible parameter combinations Previously, the adjustment of various production process conditions was reliant on the on-site staff the experience of the craftsmen Thus, during the transition of production of different incoming materials such as PET, PP, PE, a significant amount of raw materials would be wasted during the trial phase The professional information gap in traditional industries Tangxian Company recognizes the importance of data In the past, although process parameters were recorded, due to a lack of data capabilities at the time, it was primarily in paper form, manually written down by the operating staff, accumulating a large amount of paper data However, this also meant a lack of scientifically accurate and detailed information available for real-time reference and adjustment Process parameters logbook, records the state of about a dozen machines and production figures hourly In quality control as well, due to a lack of control over the quality of output and monitoring and feedback mechanisms for unit time production, it becomes difficult to predict the profit conditions of each batch Production management can only estimate and average cost and productivity changes over the process from the outcomes, without being able to objectively and timely restore the production conditions to reasonableness or make clearer adjustments when facing quality abnormalities Site reality left image shows recycled scraps right image shows pellet production Taiwanese manufacturers possess strong machinery manufacturing capabilities, and many modern machines now have data capabilities, recording real-time status and information via IoT But is the infrastructure of the factory's on-site and information systems ready yet When the Old Master Meets AI With government referral, Tangxian Company partnered with a Taiwanese data science company, working together to integrate AI services and optimize internal processes using AI They started with a medium-sized plastic recycling production line within the factory as a trial field After establishing a successful benchmark, this model was expanded to larger plastic recycling machinery within the factory to continue verification and application Initially, both parties converted the past handwritten paper data into digital format using OCR supplemented by manual correction Tangxian Company also worked with the supplier of the human-machine interface of the machinery to integrate the control panel and parameter data into the factory's database, allowing real-time monitoring of machine status and eliminating the complexities and potential errors of manual transcription Panel of plastic recycling granulation machine, showing current process temperatures, speeds, and power usage Meanwhile, the Taiwanese data science company further modeled dozens of parameter data through AI, conducting scenario analysis to simulate various production possibilities under environmental parameters and material inputs, identifying key characteristic parameters and providing parameter adjustment recommendations to decrease costs during the trial phase Applying data analysis to traditional industry machinery processes After the old master receives the raw materials, they only need to enter the relevant material characteristic parameters, and the system automatically generates recommended process parameters After small adjustments by the old master, they proceed with the trial production of the material, effectively reducing the waste of materials, water, electricity, and manpower caused by incorrect attempts Moreover, Tangxian Company has proactively deployed the concept of 'production pedigree' in the plastic recycling process, allowing the batch's raw materials and process parameters to be accessed by scanning a QRCode Production and sales pedigree of plastic recycling pelletizing Taiwan's SMEs have strong machinery capabilities, just waiting for the 'east wind' of data From industrial revolutions 20 to 30, even 40, many Taiwanese SMEs face challenges in transitions not just in upgrading machinery, but after investing in modern equipment and generating data, they do not know how to utilize it effectively It is impractical for these manufacturers to develop a specialized data analysis department on their own meanwhile, Taiwan also has many innovative teams with strong software capabilities in AI and data analysis, possessing the technology but lacking the field and data Therefore, if the traditional industries of Taiwan could be fully integrated with the innovative teams in AI and data analysis, it would not only address the current challenges of manpower and experience transfer faced by traditional industries but also advance Taiwan's development and application of AI significantly「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

2021-01-21

Records of Application Example

【導入案例】智慧農漁業數位分身：一個高效率、永續經營的農漁業升級解決方案。養殖漁業如何靠著稱為「數位分身」的AI 技術達成三倍產量
【2019 Application Example】 Smart agriculture and fisheries digital twin: A highly efficient and sustainable agriculture and fisheries upgrade solution. How did the AI technology called "digital twin" triple the output of aquaculture?

Relying on nine types of sensors to detect water quality, while monitoring the growth of the farmed species and fishermen's behavioral decisions, the artificial intelligence AI solution "Smart Agriculture and Fisheries Digital Twin" can significantly increase production by 300 The ldquoHappy Harvestrdquo - style high-tech integrated solution allows novices to get started quickly It significantly reduces the reliance of agriculture and fisheries on experience, and makes it more appealing for young people to return to their hometowns to work in agriculture and fisheries There was a time when Facebook games were just starting to become popular, and everyone could be called a farmer due to the popular game ldquoHappy Harvestrdquo Office workers took out their mobile phones one by one during their lunch breaks and started living the life of a happy farmer life on their mobile phones Some people were naughty, secretly went on Facebook during work hours to steal the harvest from their colleagues The game was so therapeutic that some people actually went into the fields to become farmers during the holidays If I said that "Happy Harvest" really exists, would you believe me THE "Digital Twin" -"Smart Greenhouse" and "Smart Farm" solutions developed by the Innovative DigiTech-Enabled Applications amp Service Institute IDEAS Institute for Information Technology III are "Happy Harvest" and "Happy Fish Dream Aquarium" in real life Here, nine sensors based on IoT will continuously monitor the "facility factors" of the cropaquaculture growth environment, such as water quality, and upload them to the cloud through the control box The AI robot in the cloud will continue to simulate a digital twin in the system, receiving "facility factors" such as water temperature and dissolved oxygen, and continuously collecting "growth factors" for the growth status of cropsfarmed species A simulated "digital twin" of the fisherman is created in the cloud system, and the AI robot will also calculate appropriate "behavioral decisions" based on the successful strategies of past fishermen When the oxygen content is low and the water temperature exceeds the standard, AI will suggest you to make behavioral decisions, such as turning on the water wheel, turning on the aerator, or using medication Fishermen use their own experience or knowledge to decide whether to follow the suggestion Afterwards, the system will compare the results of the decision, and fishermen can also judge based on the results whether the decision made by a real person is better than the behavioral decision made by the ldquodigital twinrdquoIn addition, the digital twin AI of smart agriculture operates in the background around the clock, silently recording and analyzing the corresponding "behavioral decisions" of fishermen in response to various "facility factors" and "growth factors" in smart farms Decision-making", slowly establishing the best solution model for the farming strategies Slowly, AI silently learns these "tacit knowledge" from fishermen like a little apprentice at their side, so that this knowledge will not be lost when the fishermen retireMoreover, this technology can not only be used to "farm fish," but also "farm vegetables" These optimized farming models can become a precious database Even novices who have just entered the industry can skip the process of exploration and directly become a master The greatest challenges currently faced are insufficient manpower, aging population, loss of experience, and high cost of new technologies Taiwan is famous for its agricultural technologies and farming technologies However, small farmers generally have a shortage of manpower and aging workers Digital transformation is imperative The cost of new technologies is too high for 80 of small farmers and fishermen Since there are too many uncertainties in environmental factors, such as climate change, and water quality changes, they are all highly dependent on experience Therefore, the most severe challenge comes from farmers and fishermen retiring before young farmers and fishermen can take over, and many years of experience are lost because they cannot be passed on Smart agriculture and fisheries digital twin allow continuous optimization without downtime "Digital twin" is an emerging technology that combines AI and HI craftsman wisdom, and was rated by Gartner as one of the top ten key technologies for the future for three consecutive years The Department of Industrial Technology, Ministry of Economic Affairs began to engage in RampD of digital twin in 2016 It believes that in addition to automation efficiency, industries also need to digitally preserve experience and skills to develop optimal human-machine collaboration technologies through AI and HI interactive learning In the field of aquaculture, the "digital twin" of AIoT Artificial Internet of Things for "fishery and electricity symbiosis fish farms" digitalizes the tacit knowledge of fishermen Using the analysis of "facility factors" constructed from different types of water quality data and ldquogrowth factorsrdquo such as fish and shrimp images and disease symptom images, as well as the "behavioral decisions" of fishermen, to train AI can produce optimized models for water quality management, aquatic product growth management, and aquatic disease managementThe "digital twin" of AIoT for "fishery and electricity symbiosis fish farms" digitalizes the tacit knowledge of fishermen These AI management models are combined to create a smart farming solution with high survival rate and high feed conversion rate The entire farming process has digital monitoring data and quality that can be analyzed Traceability can reach the initial stage of farming, greatly improving the quality, value, and output of aquatic products Despite promising prospects, there are still many challenges The III IDEAS first become involved in ldquodigital twinrdquo due to a forward-looking technology project supported by the Department of Industrial Technology, Ministry of Economic Affairs in 2018 At that time, the Department of Industrial Technology believed that in addition to automation efficiency, industries also need to digitally preserve experience and skills to develop optimal human-machine collaboration technologies through AI and HI interactive learning Taiwan Agricultural Research Institute, Council of Agriculture, Executive Yuan subsequently supported the application of "digital twin" in smart agriculture "The application of digital twin technology in agriculture helps small farmers digitally accumulate experience, and improves their agricultural skills through the interaction of group experience and AI, resolving the greatest challenge of intelligent agriculturerdquo Intelligent agriculture digital twin technology is expected to increase production efficiency by 30 after commercialization and is quite promising Team leader Qiu Jingming "The behavioral decisions made by powerful fishermen are three times better than those of ordinary fishermen in terms of results" nbsp Digital Twin Aqua-Solution After working with technology-based aquaculture companies and gaining support from an industry project of the Industrial Development Bureau, Ministry of Economic Affairs, III IDEAS applied digital twin technology in the field of "smart fish farms" The field application team responsible for aquaculture pointed out ldquoIn fish farms, fishermen often make different behavioral decisions when facing various environmental changes The behavioral decisions made by experienced fishermen are three times better than ordinary fishermen in terms of results For example, the survival rate of white shrimps is generally about 10, but some fishermen can achieve a yield of up to 30 This reduced production costs and tripled profitsDigital twin technology can pass on the tacit knowledge of these experts and ultimately upgrade the entire industry" The "digital twin" is composed of 9 sensors, fish images, and fishermen's behavioral decisions 9 sensors, constantly monitoring "facility factors" such as water quality IDEAS uses nine sensors to monitor water quality, nbspincluding dissolved oxygen, water temperature, pH, salinity, turbidity, ammonia nitrogen, nitrate, chlorophyll a, and ORP Oxidation-Reduction Potential, in order to obtain the environmental data of various farms These factors are also known as ldquofacility factorsrdquo In addition, fishermen will regularly take fish and shrimp out of the pond, or use submersible cameras to take pictures of farmed species underwater This is used to determine the current size of the farmed species and its growth condition, which is also called "growth factor" "Facility factors," "growth factors" plus "behavioral decisions" made by fishermen in different situations can create a "digital twin" in the cloud server Source of diagram Taiwan Salt Green Energy Co, Ltd commissioned Sanyi Design Consultants Co, Ltd to designnbsp With these two factors plus "behavioral decisions" made by fishermen in different situations, a "digital twin" can be created in the cloud server In this game-like "digital twin," we can simulate as much as we want to find the best "behavioral decision" under different "facility factors" and obtain the optimal "growth factorrdquo To put it in a way that is easier to understand, readers can try to imagine that we have a game called "Happy Fish Farm" The environmental parameters of the fish farm are all recorded from actual situations We also record the behavioral decisions made by each "Happy Fish Farm" player under different environmental parameters and the final results When the number of recorded data sets is sufficient, a digital twin of the fish farm can be obtained from machine learning, and then real-time data is simulated to obtain optimal combinations This simulated world is the "digital twin" of "Happy Fish Farm" How is the issue of sensors easily being damaged resolved However, there will always be challenges in the RampD process For example, underwater sensors such as water temperature and dissolved oxygen sensors are often damaged due to algae growth Underwater cameras that record the size of fish are often blurred and unrecognizable due to sediment or algae pollution on the bottom of the pond There are two solutions for overcoming the issue with sensor damage One is to regularly scoop water out from the pond and pass it through the sensor for detection The other is to make the sensor into a box and put it into the pond every day to detect the water quality As for the growth condition of fish and shrimp, fishermen only need to fish them out of the pond every day to take pictures and measure them Low cost and effective Team leader Chiu said "We are currently developing a 9-in-1 water quality detection box After successful integration, we can prepare for mass production and start commercial operation by selling the box plus a monthly connection fee" Team leader Chiu of IDEAS of the III said "The issue with sensor damage is the cost Even though it provides great benefits, it would be meaningless if fishermen are not willing to use it due to high cost We are currently developing a 9-in-1 water quality detection box After successful integration, we can prepare for mass production and start commercial operation by selling the box plus a monthly connection fee We are now very close to completing the integration, and welcome companies to discuss cooperationrdquo Difficulties in recording fishermenrsquos behavioral decisions Another challenge comes from fishermen Some fishermen will consciously record the water quality and environmental indicators they observe every day, and record their own operating strategies and results However, not every fisherman will do this This is why it is necessary to use GAN generative adversarial network technology, which is very important in AI GAN will generate possible strategies of fishermen based on past data, ie, it "guesses" the fishermen's decisions to supplement the behavioral decisions that the fishermen do not input If it is completed by fishermen afterwards, it will not affect the training data set After the award-winning technology is put into mass production, 300 production efficiency will no longer be out of reach Current applications of "digital twin" technology worldwide are mostly in aerospace and manufacturing Taiwan and the Netherlands are the first to engage in the RampD of digital twin in intelligent agriculture Therefore,the "Intelligent Agriculture Digital Twin" winning the US RampD 100 Awards is proof of Taiwanrsquos technological leadership We are currently completing the integrated water quality monitoring box and total solution, and the product is expected to increase production efficiency by 300 In the future, "digital twin" technology will not only be used in agriculture and fisheries, but can also be extended to industries that originally relied on "tacit knowledge", such as tea making, fisheries, etc Due to the digitization of the entire process, quality no longer relies on experience and the weather This can upgrade farmers' technology for "AI monitoring" and "precision production" In addition to improving the productivity of traditional agriculture and fisheries, it also has a good chance of achieving sustainable operations, upgrading the entire industry, and making it more appealing for young people to return to their hometowns to work in agriculture and fisheries Reference materials A key piece of the puzzle of smart manufacturing Innovative sensing technology that accelerates the realization of "digital twin" - Digital era

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Rows：73, 9 pages