Have you had your morning coffee yet Over the past decade, Taiwan has gradually formed a coffee drinking culture With the advancement of AI technology, autonomous coffee roasters can now rely on AI for precise location setting while also cultivating a loyal customer base Let's see how this is done According to the International Coffee Organization ICO, Taiwanese consume approximately 285 billion cups of coffee annually, with the coffee market in Taiwan estimated at 80 billion TWD, growing about 20 each year In recent years, the 'drinking coffee' culture in Taiwan has become synonymous with popularity, with coffee being the most frequently chosen daily beverage by 65 of the population Coffee enthusiasts, particularly the more avid ones, are willing to pay more for coffee beans that suit their tastes An increasing number of unmanned drink kiosks have also begun to appear in the Taiwanese beverage market Unmanned coffee beverage shops face difficulties in expanding quickly, primarily due to two major issues one is the appropriateness of customer flow and machine placement locations which still rely on manual analysis the second is penetrating the market of mid to high-end coffee lovers accurately AI resolves two major challenges for autonomous coffee roasters suitable placement and cultivating a loyal customer base To tackle these issues and help autonomous coffee roasters quickly break into the market, Raysharp Electronics intends to implement AI for people flow counting analysis and unfamiliar face recognition These technologies aim to calculate the crowd size at potential roaster locations and classify consumers by gender and age for more precise market analysis They also provide multiple choices for the roasting of raw coffee beans, offering a more customized service tailored to the needs and tastes of professional coffee aficionados with a pack of 'high-quality roasted beans' Since 2018, the rise of unmanned stores has been mainly due to owners wanting to reduce persistently rising rent and personnel costs However, the initial assessment of store locations still requires hourly labor expenses for manual estimation of customer flow, leading to possible miscalculations of both on-site consumers and passerby traffic These inaccuracies may prevent precise real-time analysis of customer flow, or even misguided estimations of operational efficacy after a trial run, thus missing the optimal timing for loss-preventing location retraction Raysharp Electronics introduces autonomous coffee roasters equipped with AI-based people counting analysis and facial recognition Raysharp Electronics combines AI people counting analysis and facial recognition with the coffee trend known as 'black gold', addressing the preferences of numerous coffee connoisseurs in Taiwan who enjoy personally selecting coffee beans at bulk stores and frequenting high-quality grinding cafes or chain coffee shops A new concept for the first autonomous coffee roaster offering choices based on the origin, variety, and roasting methods of coffee beans has emerged AI coffee roasters enhance customer loyalty and materials management efficiency by 20 For the advanced development of autonomous coffee roasters, Raysharp Electronics engineers have equipped the AI NVIDIA development platform on the basis of TCNNFacenet Through AI, tens of thousands of images related to gender and age are used for sample training, allowing even first-time coffee roasting customers to be easily classified using unfamiliar face recognition This gains consumer trust, enhances willingness to use, and allows for recording purchase information and future product recommendations, leading to consumer purchase behavior analysis This information helps owners tailor future material preparation based on consumer preferences for different coffee beans, reducing raw material transportation and storage issues, and improving material management efficiency by 20 Moreover, by placing these autonomous coffee roasters in high-traffic areas, owners can use cameras to capture the crowd and assess whether the machine location has an adequate customer base, quickly analyzing whether to reposition the machines, and more easily targeting the best locations for middle and high-end coffee lovers The unmanned coffee roaster features a professional roasting mode interface, providing options based on the origin and variety of coffee beans, their roasting methods light, medium, deep, and related temperature, wind speed, and timing settings If improvement needs arise during the process, engineers can adjust firmware parameters and also assist in integration with the owner's ordering system Staff members briefly describe the operation of the autonomous coffee roaster 'Black Gold' penetrates deeper into coffee shops, science parks, and commercial buildings through AI This autonomous coffee roaster targets coffee connoisseurs and can be placed in middle to high-end coffee shops to roast more customized coffee beans than those available in bulk stores Upon completing a batch of coffee beans, it immediately provides them to professional technicians within the coffee shops for grinding and manual brewing The remaining roasted beans can also be taken home for brewing and enjoyment It also adds value to coffee shops by better understanding consumer preferences for coffee beans and launching more customer-attracting drink promotions and appropriate inventory management In addition to coffee shops, the autonomous coffee roaster can also utilize AI-based people counting analysis to precisely set up near scientific parks and commercial buildings, offering high-quality coffee beans for office brewing to internal employees with high coffee consumption needs Furthermore, implementing a physical membership system can initiate coffee bean purchase promotions or periodic payment incentives, thus attracting new clients and cultivating existing customer loyalty and retention The operation interface of the smart autonomous coffee roaster「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

"The DNA of Magpie Life is not limited to vending machines We believe that vending machines combine technology, access, and humanities to bring us exciting results" This is a sentence on the official website of Magpie Life Let the vending machines bring To live a pleasant life and build a considerate, technological and sustainable future for the smartphone industry is also the original intention of Magpie Life Founded in 2018, Magpie Life launched Taiwan’s first private-brand mobile payment scan code sensor 4 months after its establishment, completing the consumption experience through screen touch The Magpie U1 smart vending machine manages the POS system and gathers data in the background, allowing consumers to synchronize with the world's new retail pace and experience a new retail consumption experience of purchasing convenience, checkout security, visual entertainment, and improved logistics replenishment efficiency Traditional vending machines lack information visibility and AI technology assists in information transparencyThis time, the Magpie smart vending machine is also equipped with AI technology to provide adjustable shelf space , a vending machine equipped with an industrial computer and a large-size touch display screen to achieve the purpose of a store-less store Magpie Life stated that the biggest problem with traditional vending machines is the lack of information visibility To check inventory, replenishment personnel must physically inspect each machine, which is time-consuming and costly When a machine breaks down, it will generally be unable to operate for a long time Most failures go unreported and are not discovered until the next restocking crew arrives to replenish supplies Then you have to wait for a service technician to be scheduled, which can take weeks Traditional vending machines lack real-time interactivity When consumers encounter problems after inserting coins, manufacturers cannot handle them immediately In addition, traditional vending machines are less flexible and cannot adapt to changes in consumer preferences Traditional vending machines have shortcomings such as limited change shopping, single payment tools, limited number of products, and few choices Affected by the COVID-19 epidemic, consumption habits have shifted to contactless methods, causing the unmanned store market to heat up Generally, vending machines can only place relatively simple products such as drinks, food, etc The properties available for sale are limited The patented vending machine developed by Magpie can adjust the shelf space and is equipped with a lifting cargo elevator, which is suitable for various types of goods In addition, the machine is equipped with an industrial computer and a large-size touch display screen, which can meet the needs of advertising support at the same time It is expected to move towards a storeless store According to Magpie Life Observation, the consumer market trend in the past two years is that consumers demand convenient life, food consumption patterns value dining experiencesimple and fast, and are equipped with mobile phone-connected ordering models, and hot drinks and Fresh food delivery is the focus of two major trends The location, items sold, consumption methods and multiple payment methods are the focus of market growth for smart vending machines In terms of convenience, Taiwanese consumers still prefer to purchase vending machine food near stations, airports, schools, and businesses in business districts Various payment methods are also gaining more support from consumers, indicating that in the future, automatic Vending machines can be developed in two directions diversified items and diversified payment methods AI sales forecast technology integrates back-end management to achieve precise marketing purposesDue to the wide variety of products, it is difficult to know the performance of products under different factors such as season, market conditions , promotional activities, etc, it is easy to cause out-of-stock or over-inventory situations Magpie Life has specially developed "AI sales forecasting technology" and integrated it into the back-end management system, hoping to lock in customer purchasing preferences and intentions through data analysis In order to achieve the purpose of precise marketing, make accurate business decisions and effectively allocate limited resources The introduction of AI systems can achieve the three major goals of precise marketing, inventory management and supply chain management This system is a replenishment decision-making aid designed specifically for supply chain managers It uses AI to predict future sales demand, helping companies effectively optimize production capacity, inventory and distribution strategies Its overall system architecture includes1 Data exploratory analysis function Provides automatic value filling, automatic coding and automatic feature screening functions for missing values in the data 2 Modeling function 1 Provides model training functions for two types of prediction problems regression Regression and time series Time Series Forecast nbsp2 Supports Auto ML automatic modeling, and the best model is recommended by the system Integrated models can also be established to improve model accuracy nbsp3 Supports multiple algorithm types Random Forest, XGBoost, GBM and other algorithms nbsp4 Supports a variety of time series models exponential smoothing, ARIMA, ARIMAX, intermittent demand, dynamic multiple regression and other models nbsp5 Supports a variety of model evaluation indicators R, MAE, MSE, RMSE, Deviance, AUC, Lift top 1, Misclassification and other indicators nbsp6 Supports automatic cutting of training data sets and Holdout verification data sets, and can manually adjust the ratio nbsp7 Supports automatic model ensemble learning Stacked Ensemble, balancing function learning Balancing Classes, and Early Stopping nbsp8 Supports the creation of multiple models at the same time The system will allocate resources according to modeling needs, so that modeling, prediction and other tasks have independent computing resources and do not affect each other In the overall server space With an upper limit, computing resources can be used efficiently nbsp9 It has in-memory computing function, which can use large-capacity and high-speed memory to perform calculations to avoid reading and writing a large number of files from the hard disk and improve computing performance 3 Data concatenation function Using API grafting and complete data concatenation automation, there is no need to manually import data, improving user experience 4 Chart analysis function Provides visual charts and basic statistical values for product sales AI data analysis solutions have two major advantages 1 Entrepreneurship machines can be rented and sold at low cost to open unmanned physical stores and cooperate with the chain retail industry Through smart machines, entrepreneurs can rent and sell them at a lower cost than the store rent Cost of running a retail business Two cooperation models, machine sales and leasing, are provided, and the choice is based on the evaluation of the industry 2 Various types of products are put on the shelves Products are sold anytime and anywhere 24 hours a day Up to 60 kinds of diversified products can be put on the shelves Large transparent windows enhance the visibility of products Regular replenishment and tracking of product sales status are available, and product types can be adjusted according to needs Recently, the line between the Internet and the physical world has blurred, the way customers interact has changed significantly, and consumer demand is changing and personalized The retail industry is facing unprecedented challenges and uncertainties, and mastering data has become key AI data analysis solutions can help the retail industry quickly activate large amounts of data, create seamless personalized experiences, optimize the operational value chain and improve efficiency, and strengthen the core competitiveness of enterprises 「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

The Kaohsiung-based Kha Shing Enterprise Co, Ltd was established over 40 years ago, and is Taiwan's largest customized yacht company with customers all over America, Europe, Asia, and Australia, earning Taiwan the reputation of the "Kingdom of Yachts" Current FRP hull inspection still relies on traditional methods, such as visual inspection and knocking sounds, which is time-consuming and labor-intensive Kha Shing has applied PAUT array ultrasonic inspection to hull FRP composite materials for the first time, and combined it with AI to interpret ultrasound images, develop complete intelligent solutions, and create emerging markets for inspection companies Kha Shing Enterprise Co, Ltd was formerly Kha Shing Wood Industry Co, Ltd, and was a factory specializing in wood import in Kaohsiung Linhai Industrial Park when it was first established It began to design, manufacture, and sell yachts in 1977 After the second-generation successor of the company, President Kung Chun-Hao entered the company, he made a breakthrough in the previous manufacturing model that relied mainly on the skills of master craftsmen, introduced digital manufacturing to accelerate shipbuilding, and began to make larger yachts, ranking in the top 20 manufacturers worldwide among manufacturers of large yachts over 24 feet It also set a record of delivering 94 yachts within one year, earning Taiwan the reputation of "Kingdom of Yachts" Defect detection ensures yacht quality, using AI to replace humans to achieve higher efficiency Defect detection is very important to ensuring yacht quality At present, the yacht industry still uses very traditional defect detection methods The hull structure is usually made by hand lay-up or the vacuum infusion process, using visual inspection or knocking and the frequency of the sound to determine defects It requires time-consuming manual inspection If there are any defects, they must be reworked and repaired, and a gel coat subsequently sprayed The hull must be constructed in sections to facilitate inspection For large yachts over 24 meters long, construction in sections is very time-consuming and labor-intensive To shorten the time of the yacht manufacturing process, Kha Shing Enterprise will first carry out the gel coating process for the hull, and then perform the hand lay-on process The hull manufacturing process has two types of composite material test specimen structures In terms of 54-foot yacht hulls, the hull contains gel coat, core material, fiber and resin, and the total thickness is about 32cmplusmn01cm, which is twice the total thickness of FRP hull without core material of about 16cmplusmn01cm Defects such as incomplete impregnation of glass fiber or residual air bubbles between glass fiber and resin occasionally occur during the manufacturing process The types of defects include insufficient resin, voids, and delamination Once defects occur, the supply of hull materials will be insufficient and yacht delivery will be delayed Schematic diagram of types of FRP hull In order to solve this problem, Kha Shing Enterprise has engaged in technical cooperated with the metal materials industry and the AI technology industry, combining the ultrasonic inspection expertise of the metal materials industry with AI technologies developed by the AI technology industry in recent years to help solve issues of Kha Shing Enterprise with defect detection The method uses PAUT on the composite material structure of yachts, conducts FRP ultrasonic evaluation to determine the thickness of the yacht hull and material properties, and evaluates the ultrasonic probe frequency applicable to the hull structure based on professional ultrasonic experience After testing, a frequency of 5MHz and a probe width of 45mm can successfully find the location and size of defects in the simulated defect test specimen The three parties jointly found defect detection solutions from array ultrasonic evaluation, AI technology model development, and actual application in yachts The image inspected is an ultrasound image The image displays different colors based on the ultrasonic feedback signal An AI model that automatically identifies defective parts is established through the YOLO algorithm If the amount of abnormal data collected is insufficient for training, the CNN-based Autoencoder algorithm is used to collect normal image data for training and construct an AI model for abnormality detection The object detection YOLO model is trained by inputting image data marked as having defects, while the abnormality detection model is trained by inputting image data without defects Simulated defective specimen corresponding to PAUT results Defect detection by and AI system can shorten the construction period by 15 months and speed up determination by 50 After the development of this AI system is completed, it will be validated on actual 54-foot yachts of Kha Shing Enterprise, and can effectively resolve issues with defects The application of AI technology in ultrasonic inspection for intelligent determination is expected to accelerate determination by approximately 50, and will also shortens the construction period by 15 months, effectively improving the speed and quality of the yacht manufacturing process As Taiwan develops larger and more refined yachts, it will create opportunities for industry optimization and transformation, as well as opportunities for the development of key technologies The application of an AI ultrasonic inspection solution for composite materials is the first of its kind in the yacht industry, and is expected to attract more yacht manufacturers with inspection needs The AI ultrasonic inspection solution for composite materials has three major competitive advantages 1 Professional inspection experience and digital database to facilitate process management and analysis 2 Automatic AI determination and identification quickly identifies defects and provides immediate feedback to process engineers 3 High-efficiency process inspection provides defect repair recommendations, reduces damage rate, and improves the strength and quality of composite materials The application of AI technology can optimize the yacht manufacturing process, reduce manual inspection, create added value through the application of AI in Taiwanrsquos yacht industry, increase international purchase orders, and allow Taiwan yachts to continue to enjoy a good reputation in the world Furthermore, this business model has also spread to fields of application related to composite materials, increasing cross-sector market usage It is estimated to contribute approximately NT14 to NT2 billion in economic benefits to Taiwan's equipment maintenance and non-destructive testing market

Taiwan is a maritime nation When you visit the Badozi Fishing Port or Tidal Park in Keelung, do you also explore the mysteries of the ocean world at the 48-hectare National Museum of Marine Science amp Technology To get more people closer to marine technology, Keelung's Marine Museum has introduced technological services, transforming the venue into a large technology playground that delights both children and adults, fully utilizing the 'learning through play' approach After a lengthy planning process, Northern Taiwan's largest marine science museum in Keelung opened in January 2014 The museum focuses on marine education and technology, boasting Taiwan's largest IMAX 3D ocean theater The unique themes and modern viewing facilities should make it a well-known landmark in Keelung However, the original exhibition planning was static and highly specialized, lacking sufficient interaction with the public Visitors who have attended the museum also reported that the exhibits were limited and quite boring, leading to poor overall consumer experience ratings The top three dissatisfactions with the museum were weak connections to surrounding attractions, unengaging display content, and lack of exhibit material According to statistics from the Marine Museum, the ratio of local to visiting guests is approximately 64, with most foreign visitors coming from the north transportation is primarily by car and bus common types of visits include family, parent-child, and friends and the stay duration is generally 1 to 2 hours Upon deeper investigation, the top three visitor complaints were weak linkages to surrounding attractions, unengaging display content, and insufficient number of exhibits The museum analyzed potential reasons, including some displays being too specialized, making it difficult for the public to understand, and a lack of interactive elements, making the exhibition boring and the visit hurriedly brief Analysis of visitor profiles revealed that since half of the museum's visitors are locals, and accessing the museum is not so easy for out-of-towners who must travel by car or public transport, the design of the venue and exhibitions must incorporate more interactivity and intrigue to encourage locals to return and extend the duration of visitors' stays while using technological services to highlight the museum's unique features Through a recommendation from the Information Software Association, part of the Ministry of Economic Affairs' Industrial Bureau AI team, the Marine Museum commissioned Jugu Technology to resolve the issue of uninspiring venue attractions Preliminary interviews by Jugu Technology revealed that many visitors were attracted by the architectural design of the museum, notices posted on nearby walls, flags, or events being held the most interesting feature for visitors was the 3D ocean theater, indicating that content presented through audio-video and physical scenic methods was more engaging Seven major AI technologies lead to a boost in regional tourism at the Marine Museum Through the introduction of technology services, Jugu Technology designed the 48-hectare site with seven major services AI voice tours, treasure hunt puzzle games, AI exhibit interactive revitalization, AI space exhibition interactive experience, AI crowd control, Face AI interactive experience, and AI voice customer service system By utilizing AIoT and cloud technology, they made the exhibition more interesting, not only solving the issue of boring static viewings for children but also doubling the learning efficiency and dramatically improving public perception of the Marine Museum, thus increasing visitor intent and boosting regional tourism The National Museum of Marine Science and Technology introduced seven major technological application services including AI voice guide Jugu Technology aimed to improve the space optimization of the Marine Museum, using the special exhibition of coastal birds in northern Taiwan as a prototype, integrating 'face', 'limb', 'crowd' as three main axes to enhance functionality and assist in improving the museum's application of AI Practically, the Marine Museum and Jugu Technology selected the on-site special exhibits to avoid any installation of water and electricity works or pipelines in active exhibits, thereby maintaining the quality of the viewing experience Instead, they selected exhibits that were not yet open to introduce a series of technological services tailored to the unique characteristics of the exhibits In the coastal bird special exhibition inside the Marine Museum, initial construction discussions with the curators utilized Bella X1 for a welcoming interactive introduction at the exhibition entrance This was followed by an AI-powered smart guide in both Chinese and English using X1 for narration, coupled with a fun treasure hunting stamp-collecting activity - APP X1, allowing visitors to participate in challenges Subsequently, bird species within the bird exhibition were brought to life interactively using X1, and AR scenarios X1 were introduced into the exhibition space to add elements of fun and entertainment Finally, Face AI was used to interactively test facial expressions and score smiles The gorgeously transformed Marine Museum will become the best travel destination for families with children ImageMarine Museum FB Page The AIoT services introduced by the Marine Museum could be extended to various exhibition-type museums and even static art galleries in the future, tailored to the unique characteristics of different venues They could also be promoted through government projects and related plans, aiding in rural revitalization, making visits more than just sightseeing in rural areas, and breaking free from stereotypes associated with different venues The applications of these services are broad「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

After incorporating AI technology, traditional logistics companies have seen significant improvements in transportation efficiency and reductions in transportation costs, especially in the transfer of medical materials which involves timely service and rights of hospitals and patients The implementation of intelligent logistics can save medical material businesses the cost of constructing GDP warehouses and other expenses up to millions A major domestic logistics leader, Hsinchu Transport HCT, owns a fleet of 3,500 vehicles and a storage area of 60,000 square meters, providing customized logistics solutions including logistics, commerce, finance, information, distribution, storage, and processing The company handles up to 580,000 parcels per day, with a maximum capacity reaching 900,000 parcels, making the enhancement of transshipment efficiency crucial for HCT Medical materials transportation at hospitals need optimization of current operational processes and enhancements in systematization and intelligence Especially the transportation of hospital medical materials, which encounters various challenges Medical materials suppliers need to cater to varying customer product demands, temperature requirements, and delivery times through multiple logistics providers This highly depends on the experience and careful control of operations staff Whether it is the product shipment or actual logistics process, each step must be interconnected Any human errors can impact the service timing and rights of the hospitals and patients Thus, all concerned businesses, along with the government and hospitals, are working to optimize current operational processes and elevate the level of systematization, automation, and intelligence to minimize service errors and cost losses HCT's distribution process prior to AI implementation Currently, with the government's push for standardized platform operations on the demand side of hospitals, supply-side businesses collaborate through data coordination to improve the accuracy and efficiency of product shipments, enhancing operational quality and management benefits at the demand side At the same time, some businesses are also investing in the standardization and systematization of internal operational processes, thus enhancing operational efficiency and quality In the freight logistics sector, logistics companies' warehouse staff need to expend labor to control different logistics shipment operations If they often receive emergency task notifications for shipments to medical facilities, they usually depend on small regional logistics providers to provide customized delivery services Although this improves delivery times, it does not allow for integrated informational services The new GDP regulations for medical materials require suppliers to undergo GDP compliance certification Therefore, Hsinchu Transport, assisted by the Ministry of Economic Affairs' AI coaching program, not only extends existing logistics services compliant with GDP regulations but will also use data integration and optimized AI technologies to help medical material businesses streamline and improve their logistics operations Complex logistics issues are solved using the Simulated Annealing SA algorithm To meet the 'Good Distribution Practices for Medical Devices,' Hsinchu Transport is not only actively introducing new logistics vehicles but will also implement artificial intelligence-based mathematical optimization technologies to assist in intelligent scheduling at nationwide business points and transshipment stations They aim to optimize the routing of medical materials between business points or regions thereby enhancing efficiency in the distribution process Currently, during the transshipment process of medical materials at Hsinchu Transport, detachable tractor heads and containers are used Each business point and transshipment station differ in location design and staffing, impacting the throughput per unit of time Furthermore, daily cargo conditions size, destination vary, and due to these fluctuating and distinct demands, the deployment of tractor heads and containers changes accordingly Under these circumstances, Hsinchu Transport relies on past experiences to schedule departures at each satellite depot and adjusts daily according to the cargo needs Due to the reliance on empirical scheduling, it is often difficult to consider all variables and considerations, leaving room for improvement in the current departure schedules The cargo delivery planning inherently constitutes an NP-Hard problem, difficult to solve with traditional analytical methods Hsinchu Transport, in collaboration with Singular Infinity, utilizes the Simulated Annealing SA algorithm to find solutions The new logistic service introduced by Hsinchu Transport is 'GDP Container Shift Planning' This planning involves estimating future volumes of medical materials between stations and scheduling container truck shifts accordingly, ensuring timely and quality delivery of medical materials while maximizing operational benefits and reducing travel distances Hsinchu Transport introduces AI-optimized shift planning, constructing the most efficient route from its origin to destination Hsinchu Transport introduces 'Optimized Shift Planning' service, reducing transportation costs by 5 The introduction method involves using cloud software services Hsinchu Transport regularly inputs 'Interchange Item Tables' from station to station into the 'Optimized Shift Planning' service After setting the algorithm parameters, a GDP container shift schedule is generated At the same time, developing a Hsinchu Transport medical material scheduling system allows Hsinchu Transport's medical transport units to compile suitable schedules through the Interchange Item Tables Under the same level of service, it's estimated that this can reduce transportation costs by 5, saving medical material businesses millions in construction costs for GDP warehouses and distribution Due to its requirements for sanitation, temperature, and its fragility, the transportation and transshipment of medical materials should be minimized to reduce exposure and risk However, logistics efficiency and costs must still be considered AI designs the most efficient route for each cargo from its origin to destination, effectively completing daily transportation tasks In response to the future high development demand of industrial logistics, distribution and transshipment AI optimization will be a key issue Through this project, a dedicated project promotion organization will be established, staffed with AI technology, IT, and process domain talents After accumulating implementation experience, the application of AI will gradually expand, comprehensively optimizing and transforming Hsinchu Transport's operational system, and partnering with AIOT and various AI domain partners to accelerate and expand the achievement of benefits「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

60-year-old Mr Huang was admitted to the hospital due to a stroke After lying in the intensive care unit for two weeks, his condition suddenly took a turn for the worse After rescue, he was lucky enough to survive In fact, with the assistance of AI critical illness early warning technology, hospitals can detect signs and take timely and accurate medical measures 6-8 hours before a patient's heart stops, which can greatly reduce the chance of death in the hospital The deterioration of the condition is a process that evolves over time, and its subtle changes are by no means without context Previous research reports show that about 60 to 70 of inpatients who experience unexpected in-hospital cardiac arrest had symptoms 6 to 8 hours before their cardiac arrest, but only a quarter of them were recognized by clinical staff Detection and discovery, therefore, there is a need for a risk warning tool or system that can be used earlier and continuously to monitor the condition, alert medical staff to pay attention to subtle changes in the patient's condition at any time, and take timely and accurate intervention measures before the condition progresses to effectively reduce adverse events or the risk of serious adverse events Unexpected deterioration cannot be detected early Acute and severe patients often undergo unpredictable changes, and timely detection or prediction of potential acute and severe patients is an important issue The currently commonly used clinical assessment method is Modified Early Warning Score MEWS, which uses simple physiological parameter assessment including heartbeat, respiratory rate, systolic blood pressure, body temperature, urine output and state of consciousness to screen out high-risk patients, and has been proven to be predictive Patient clinical prognosis MEWS is a scoring mechanism with a single time point and a standardized formula However, the AI crisis warning system developed by Boxin Medical Electronics - Hospital Emergency and Critical Care Early Warning Index System EWS is designed to predict patient status with immediate response , collect the physiological data of patients over time for deep learning, find the best prediction model, and improve the overall accuracy Boxin Medical Electronics uses a big data analysis model to build an early warning system EWS, IoT Internet of Things and 5G communication technology, allowing medical staff to remotely monitor the physiological status of patients through communication equipment, and monitor emergency and severe cases quickly The patient's condition changes and the golden rescue period of 6-8 hours before cardiac arrest can be grasped After Boxin Medical Electronics introduces AI visual interpretation, unmanned operation can greatly reduce medical manpower The AI technology developed by Boxin Medical Electronics is the Gradient Boosting Ensemble Learning System GBELS to build an early warning system It is a learning-based EWS prediction algorithm developed by the company, which is an integrated learning Ensemble Learning and is classified as supervised learning, providing the following three functions 1 Early warning risk notification is used to analyze representative data using GBELS to provide an early risk score so that medical staff can conduct immediate clinical assessment and provide appropriate medical treatment 2 Reduce medical manpower Collect continuous physiological monitoring data, such as heartbeat, respiration, blood pressure and blood oxygen concentration, etc, to reduce the time for medical staff to write cases 3 Combine IOT logistics network and 5G communication technology to quickly transmit medical data such as monitoring parameters and imaging data, and assist medical staff to monitor changes in patients' condition remotely through communication equipment AI critical illness system monitoring to master the golden treatment period Boxin Medical Electronics stated that assessing the severity of the disease in acute and severe patients is a complex task, and patients often experience unpredictable changes Clinical medical staff often judge the condition based on their own clinical experience or intuition, which lacks science and objectivity, resulting in the inability to correctly identify and timely detect potentially acute and severe patients, resulting in or misdiagnosis leading to increased in-hospital mortality of patients The introduction of an AI early critical illness warning system can assist emergency and critical care medical staff to correctly predict the patient's condition and allow patients to receive the care they need immediately This can reduce the manpower arrangement of the emergency and critical care ward at the same time and reduce labor costs In addition, the easy-to-carry design will help the system be introduced into ambulances, home care and other places in the future, so that emergency patients can receive appropriate care earlier Other departments within the hospital can also develop new applications around this system, which can effectively accelerate the development and promotion of smart medical technology With the COVID-19 epidemic still raging in many countries around the world, this system can also help hospitals in various places to operate more effectively Caring for and monitoring the condition of critically ill patients In addition to AI critical illness warning, Boxin Medical Electronics has also developed AI image interpretation - Medical Physiological Monitor Life Cycle Compliance Testing AVS, which uses AI image interpretation technology to develop automated quality inspection of life support medical equipment The instrument solves the time-consuming problem of medical instrument testing It can reduce testing time by 70, increase the number of tests by 3 times, and effectively reduce labor costs by 50 At the same time, it is 100 compliant with regulatory requirements, and gradually solves the shortage of manpower and medical resources in the medical field , medical work overload and other issues It has now taken root in mainland China and is actively preparing for its launch in Europe It will develop towards the Japanese and American markets in the future Boxin Medical Electronics develops AI image interpretation-medical physiological monitor life cycle compliance testing AVS to solve the time-consuming problem of medical instrument testing and can reduce testing by 70 time At this stage, Boxin Medical's smart medical technology has been introduced into medical hospitals including Hsinchu MacKay, Changkei, Dongyuan General Hospital, Kaohsiung University of Technology Affiliated Hospital, Zhenxin Hospital, Hsintai Hospital, Taipei Medical University Affiliated Hospital, etc GE HealthcareInc, an internationally renowned medical materials manufacturer, and Mindray Medical, China's largest medical materials manufacturer, are both representative customers of Boxin Medical Electronics 「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

As water resources deplete and environmental protection needs increase, wastewater treatment plants have increasingly adopted AI technology to assist in monitoring and warning systems Zhongxin行's integration of big data and AI technology has opened up new possibilities in the environmental industry In the future, besides boosting the technological momentum of the wastewater treatment industry, it can also be promoted to other industries to foster technological and economic development Founded in year 1980 as Zhongxin Engineering later renamed to Zhongxin行 Company Limited, it is one of the largest and most technically equipped environmental companies in the domestic operation and maintenance field Zhongxin行's achievements in the operation and maintenance of sewer systems span across Taiwan, including science parks, industrial zones, international airports, schools, collective housing, national parks, and factories Introduction of AI systems in wastewater plants Precisely reduces medication addition times and lowers the risk of penalties for water quality violations At the wastewater treatment plant in Hsinchu Science Park, Zhongxin行 introduced the 'AOMBR Carbon Source and Aeration Intelligent Enhancement Control System Development,' which accurately predicts air volume control and reduces medication times, thus lowering the risk of hefty fines Zhongxin行 points out that with the vigorous development of advanced industries and increasingly strict effluent standards, a slight misalignment in equipment control can lead to major discrepancies in water quality In recent years, many wastewater treatment facilities have incorporated automatic control functions, yet onsite conditions often deviate slightly from theoretical expectations, causing situations where good treatment technologies must continuously adapt and adjust to achieve effective effluent water quality control 'The better the quality of the effluent, the greater the pressure on the operators This is the biggest pain point for Zhongxin行,' said a senior manager candidly Regular water quality testing and equipment maintenance ensure that effluent water stays below legal standards This means that operators need to be on top of equipment and water quality conditions daily If there are sudden anomalies in influent water quality or equipment malfunctions, linked issues can lead to pollution Therefore, besides performing regular maintenance and testing, it is critical to constantly monitor the dashboard to ensure system stability, consuming both manpower and mental energy Zhongxin行's on-site operators work 24-hour shifts, constantly monitoring effluent water quality Combined with laboratory water testing and analysis, if the wastewater treatment values do not meet requirements, they face both administrative and contractual fines from environmental agencies and granting authorities, which also create significant psychological pressure on the employees Over the years, Zhongxin行 has built up a vast database of water quality information and invaluable experience passed down among employees, allowing a comprehensive understanding of the entire system's operational characteristics Moreover, by analyzing equipment or water quality data for key signals, problems in the treatment units can be pinpointed If AI technology could be adopted to replace manual inspections of wastewater sources and generate pre-warning signals for systematic assessment, it would significantly alleviate the pressure on staff Response time reduced from 8 hours to 4 hours, saving half the time By implementing 'AOMBR Carbon Source and Aeration Intelligent Enhancement Control System Development,' Zhongxin行 utilizes accumulated wastewater data along with verbal recounts of operator experiences on-site With the support of AI technology and environmental engineering principles, key parameters in the biological treatment unit such as carbon source dosages and aeration can be effectively controlled Through the AI transformation of wastewater treatment, a balance is achieved among pollutant removal, microbial growth, equipment energy conservation, and operation economization, achieving rationalized control parameters Carbon source and aeration parameter adjustment steps range from data collection, model training to prediction verification In the long run, incorporating historical data calculations, AI can operate within known boundary conditions, not only recording past water quality and equipment operational characteristics far more accurately, but also developing predictive models to find optimal solutions that offer the best results in terms of chemical use, energy saving, reduced greenhouse gas emissions, and pollutant removal According to Zhongxin行's estimates, originally due to human parameter adjustments leading to errors, controlling response time would take about 8 hours With the introduction of AI technology, not only can measurement errors be reduced, but also the control response time can be shortened to 4 hours, saving around half the time This enhancement increases the turnover rate of personnel and effectively reduces the risks of penalties due to operator errors and thus markedly reducing the pressure on employees Dashboard digital display panel illustration「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

How to integrate consumer data from various group companies to create advertising synergy and enhance the conversion rate of e-commerce guided orders is probably what every cross-industry business owner dreams of No problem, this can be achieved gradually through AI Eastern Home Shopping is affiliated with the Eastern International Group, which includes East International, Eastern News Cloud, Eastern Insurance Representatives, Eastern Natural Beauty, Eastern Global Marketing, Eastern Pet Cloud, HerEastern, Focus Media, Hong Kong Strawberry Net, and Bear Mom's Vegetable Market, among other companies With cross-industry and cross-domain relationships within the group, and independent operations of membership systems in each unit, consumer data could not be exchanged within the group, making it difficult to uphold Eastern Group's promise to 'place customers in a godly position' Eastern Group’s companies cover a wide range of industries, with large and scattered member databases The Eastern Group boasts significant member traffic and has applied AI news recommendation algorithms and other related technologies across various venues However, the independence of member systems in each unit of the Eastern Group prevents the exchange of consumer data within the group, lacking a comprehensive basis for consumer behavior analysis This results in the inability to enhance the precision of personalized services and marketing strategies When analyzing the challenges and trends of the current retail market, Eastern Group remarked that in response to changing consumer demands, non-traditional business models are emerging, leading to the fragmentation of retail Various emerging business models provide services or products catering to their niche markets, leading consumers to rely less on traditional retail models Retail fragmentation, becoming more apparent in emerging countries, rapidly develops new forms of retail such as high-growth flash sale eCommerce, which threatens traditional B2B2C eCommerce platforms These emerging business models quickly divide traditional retail spaces and could revolutionize existing market rules The retail market is expected to continue evolving towards segmentation The rapid integration of AI applications in the new retail industry to meet highly competitive markets Under the trend of merging physical and digital realms, the line between offline retailers and online e-commerce is increasingly blurred Offline retailers are setting up brand official websites and developing brand apps, investing in e-commerce platforms, while e-commerce operators are starting to established offline physical experience stores, enhancing touchpoints with customers Both are exploring consumer data profiles through offline-online integration, based on AI technologies like machine learning, deep learning, computer vision, language processing, mobility control, and decision-making technologies to actively integrate intelligent retail AI applications, shaping the new retail industry Additionally, Google Chrome claimed in 2021 that it would disable 3rd party cookie functionality within two years, causing retail companies to lose the ability to track personalization via Cookies and understand user behavior across different times, locations, and ads This will prevent cross-device, cross-platform tracking, forcing companies to transform and face big challenges in traffic advertising sales Therefore, the Eastern Group decided to implement the 'OneID AI Traffic Monetization Service Validation Plan', establishing an exclusive data alliance for the Eastern Group, using 'Unified ID' for cross-industry, cross-service data exchange Transforming from collecting personalized data of related companies to analyzing common behavioral characteristics of consumers across industries, segmenting them to obtain users with similar behaviors, and providing interesting content Additionally, utilizing first-party data and AI technologies to improve ad click-through rates, enhancing the advertising value and e-commerce guided order conversion rates This AI technology project is co-developed by Eastern and ASUS computers, encompassing major development tasks such as project planning, system architecture design, system environment setup, algorithm development, algorithm model validation, and system verification The employed technologies include a big data parallel processing framework, natural language processing, user recommendation embedding systems, similarity search, search engine indexing, and click rate prediction This project aims to develop a comprehensive data collection, processing, and integration platform 'Data Middleware', collecting various data sources, focusing on users as the basic unit, forming structured data tables, and calculating user tags for precise characterization of each user Subsequently, this data is utilized for precise AI advertisement placements Eastern Data Middleware structure diagram Eastern Home Shopping introduces OneID AI Traffic Monetization Service, predicting cost-effectiveness to be up to 2 times Eastern stated that this project primarily applies 'user behavior data' and 'AI technology', with user behavior data provided by the Eastern Group and AI technology being co-developed by company and ASUS teams, covering systems such as AD Serve, precise audience estimation system, AI automatic optimization system, advertising efficacy system, and user profiling system The customer data and traffic of AI technology co-developed with ASUS remain independent and not interconnected According to estimates, this development project's total cost-effectiveness could reach 200, expected to precisely capture the user's digital trajectories, behavior, and profiles, potentially resulting in significant growth in customer lifetime value LTV, effectively integrating Eastern's online and offline services, enhancing membership service content, and substantially increasing corporate value In the future, as the Eastern Group continues to expand into international markets, it currently targets Mainland China as the primary promotion market, extending the entire service module with Eastern Global’s operational model to the global Chinese market while ensuring compliance with GDPA, merging it with Strawberry Net to provide Eastern's new retail services with the advantages of big data and AI globally Eastern Group will expand its services and technology to the global market through Strawberry Net「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

Fisheries is an important industry in an island economy However, the fish farming industry has faced severe challenges in recent years, including climate change, labor shortage, and rising costs In particular, nearly 110,000 workers in agriculture will retire due to old age over the next 10 years For this reason, the need for aquaculture to move towards smart farming is becoming increasingly urgent Founded in 2014, Fongyu Corp Ltd has developed a unique eco-friendly farming model based on its own fish farming It uses AI knowledge-based fish farming to effectively increase aquatic product production by 10, and reduced labor cost by 15 The word "Fongyu" has a profound meaning "Fong" represents good mountains and "Yu" represents good water, and is the hope that companies will allow Taiwan to always have good mountains and good waterIt is also a homophone for "having a full figure," expressing the hope that products will give consumers a full and healthy body and mind The founder of the company, Liu Chien-Shen, has been through the difficult entrepreneurial journey of becoming an apprentice in fish farming, raising funds, renting fish farms, establishing a fish farming company, building a brand, and expanding sales Labor shortage and aging workers are hidden worries in the fish farming industry Currently, fish farms in Taiwan are still mainly traditional fish farms, and farming techniques are still passed down through word-of-mouth In addition, the labor shortage and average age of workers exceeding 60 years old has made it impossible to effectively stably improve productivity and yield This farming method makes it difficult to prevent and control diseases, and greatly increases the possibility of excessive use of drugs, environmental pollution, and water quality and ecological damage, creating a vicious cycle that lowers the quality of fish farming In addition, 651 of workers in Taiwan's fish farming industry are inadequately skilled With limited support from IoT sensors, traditional fish farmers still mainly rely on their own experience and knowledge for water quality management, feeding, and disease detection Fish farming management relies heavily on the ability of individual fishermen Once experienced workers retire, the industry will not only face the issue of succession, but also the difficult of stably supplying a certain amount of harvest that meets quality standards This may cause a dilemma for the entire industry from fish farming to sales In order to improve the pain point of inability to pass on experience in fish farming, and at the same time create a "digital" foundation for fish farming, the top priority must be to collect farming behavior data and develop AI services as an important starting point Fishery digital twin technology helps fishermen transition to smart farming With the assistance of the Institute for Information Technology III, Fongyu implemented the "fishery digital twin" technology to dynamically adjust the farming schedule In other words, the fish farming schedule is adjusted according to the species, habits, and variables of the fish The use of AI in fish farming not only effectively increase aquatic production by 10, but also reduced labor cost by 15 In terms of specific methods, we first digitalized the fish ponds, feed, and decision-making behavior for each species, such as sea bass and Taiwan tilapia, and recorded the seasonal temperature changes from releasing seedlings to harvesting, all of which were digitalized, gradually recording the experience and methods of experienced workers into a rich database Based on the recorded data, we analyzed the compound variables to find the best farming behavior and generate a dynamic farming schedule The records for each pool provide data on workers' experience However, fish farming behavior generally relies on rules of thumb Even experienced fish farmers cannot ensure that they will find the best solution Therefore, new methods are proposed to solve this issue That is, "to determine the best fish farming behavior by predicting the interaction with water quality and past data on feeding, and evaluating fish farming behavior based on water quality and fish farming," and provide fishermen with the most intuitive recommendations through daily schedules To continue optimizing the dynamic fish farming calendar on a rolling basis, iterations of the model will be developed through the three-step cycle 1 Input the current fish farming calendar into the model 2 The model predicts the future environment 3 Shortcomings of the fish farming calendar are corrected based on the future environment to obtain a new version of the fish farming calendar In the process, the experience of aquaculture experts is used to establish the causal relationship between fish farming behavior and the environment The establishment of a dynamic fish farming process and technology-based fish farming recommendation services provide a traceable and detailed fish farming process It is one of the few technologies that can digitalize fish farming Fishermen can quickly and easily record their daily behaviors to build knowledge without taking up too much time, but in the long run it can reduce labor cost by 15 and increase output and revenue by an average of 10 Smart fish farming has achieved outstanding results, reducing labor cost by 15 and increasing output by 10 At the same time, the fish farming calendar can also be extended to different aquatic species, such as white shrimp, milkfish, clams, and Taiwan tilapia, to produce fish farming schedules for ponds with different specifications, and the harvested aquatic species can be traced according to different specifications, establishing vertically integrated services for safe food products Fongyu's main products are divided into two categories One is aquaculture modules, including fry, feed, materials and probiotics, production planning and processes, and monitoring, which can be sold separately or exported as modules The high-quality aquatic products produced by Fongyu have repeatedly won awards Figure Fongyursquos official website The other category is high-quality aquatic products, including seabass fillets, seabass balls, oil-free seabass balls, seabass dumplings, and seabass soup The products have won various awards, including the top ten souvenirs in Pingtung in 2017, "Barramundi Fillet" won the 2017 Eatender of the Council of Agriculture COA, "Oil-Free Barramundi Fillet" won the 2018 Eatender Gold Food Award of the COA, and "Dumplings of Barramundi" and "Barramundi Broth" won the 2019 Eatender of the COA The consecutive awards represent that the "quality" of Fongyursquos aquatic products can be seen and eaten with peace of mind In addition, Fongyu has exclusive fingerlings that meet international needs, such as Pure seawater cultured tilapia fingerlings and seawater Taiwan tilapia fingerlings from selective breeding FY-01 are items that aquaculture companies in many countries are looking forward to The company also has aquaculture modules, disease monitoring tools, and feeding materials designed in accordance with the environment, in order to provide customers with more stable income