Solutions | AI HUB

Special Cases

【2020 Application Example】 Peeking into a Baozi to See How AI Reduces Scrap Rates by 50% and Boosts Production Efficiency by 60% for Frozen Foods

From production line to dining table, who oversees the hygiene management of what we eat In recent years, there has been a continuous stream of news reports concerning food safety, such as repackaging expired goods, and poisoning incidents at Hong Rui Zhen It's clear that people are increasingly concerned about the hygiene of their food However, due to various quality control methods in food processing, there are inherent risks The World Health Organization WHO has pointed out that unsafe food and water cause physical harm to 2 million people each year Hence, international markets demand that food processing companies must establish a traceability system for products This is why major domestic food processors also aim to set up a production traceability system to quickly trace back to problematic raw materials and initiate recall and destruction of problematic food Visible assurance, implementing production transparency A major domestic food manufacturer producing frozen food and instant meals has expanded its market presence to North America, New Zealand, Japan, etc They are also at the forefront in promoting food management domestically, having obtained certifications such as HACCP, ISO22000, ISO14001 Since food production is labor-intensive, it is prone to quality impacts caused by worker fatigue Additionally, the production lines often have unclear records of production quantities, processes, and timing This obscurity in traceability makes it difficult to track production information when defects occur, leading to food safety management gaps that result in the scrapping of entire batches To address this, the Production Development Center at National Sun Yat-sen University utilized its advisory resources to help the food manufacturer tackle food safety management challenges, planning the use of AI technology to collect production data and establish anti-fraud and traceability for food production Intelligent manufacturing boosts food safety Although the level of automation is not high in the processing of bakery products, the food plant in this case is keen to enhance the automation of its production lines and introduce smart manufacturing For businesses, a traceability system not only helps establish brand image and increase product and brand value, but also gives consumers peace of mind due to the transparency of production lines Therefore, the Production Development Center at National Sun Yat-sen University matched AI technology service providers, Hong Ge Technology, in the first phase to plan the introduction of data collection devices to link food work orders information, reducing human operational omissions and capturing real-time production information through dashboards to ensure the consistency of production stage information potentially affected by human factors Schematic for intelligent production line planning The second phase involves using deep learning during the dough fermentation stage to calculate size and volume, analyze the relationship between temperature, humidity, fermentation time, and product volume, and assess whether to introduce AOI foreign object detection after freezing as a second quality control step Schematic of AI-integrated quality control for finished products Food processing ID card, launching the AI-era of food safety tracing In Taiwan, the understanding and acceptance of production history by consumers is gradually improving From the supply of raw materials, processing, production, to distribution and sales, it is necessary to have complete control and provide transparent information Publicly disclosing the production history not only increases trust between enterprises and consumers, but also aligns Taiwan's food safety environment with international standards In 2020, the Production Development Center at National Sun Yat-sen University will assist enterprises with the adoption of advanced AI technology, documenting the entire data process from industry to dining table and supervising food production processes to successfully implement product tracing, prevention of adulteration, and the establishment of high standards for products, thus advancing food processing products to international standards「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

2020-03-12

【2022 Application Example】 Even the United Nations is on board! Yoyo Data Application captures global business opportunities with agricultural data

Nearly 2,000 days in the fields have made Yoyo Data Application a top player in Taiwan’s agricultural data sector Their comprehensive grasp of crop yields, production periods, and prices has enabled them to collaborate with the United Nations The service area for agricultural land skyrocketed from 24 hectares to over 6,000 hectares in less than three years—a 250-fold increase For Wu Junxiao, founder and CEO of Yoyo Data Application, aligning with global environmental trends and becoming a data company at the intersection of climate technology and the green economy to serve the global market is his ultimate entrepreneurial goal Wu Junxiao, originally an engineer, joined the Industrial Technology Research Institute in 2010, where he honed his profound technical and data science analytic skills 'At that time, I was working in data analysis engineering, and almost all data-related materials would be directed to me Additionally, I worked on indoor cultivation boxes, planting vegetables and mushrooms, hence planting the seed of entrepreneurship by integrating agriculture with data analysis,' Wu recalls Since 2016, Wu Junxiao has been frequently visiting farms to 'embed' himself among farmers and agricultural researchers, chatting and sharing information systematically, which quickly established his agricultural know-how Solid data analysis capabilities have even convinced the United Nations In 2017, he left the Institute to start his own business and founded Yoyo Data Application in 2019 Today, many agricultural businesses are his clients, with service areas rapidly climbing from 24 hectares to over 6,000 hectares, expected to surpass 7,000 hectares in 2022 His clientele includes markets in Japan, Central America, and even entities under the United Nations like the World Farmers Organization, which utilizes the 'Yoyo Crop Algorithm System' supported by Yoyo Data How exactly does Yoyo Data Application manage to impress even UN agencies The 'Yoyo Crop Algorithm System' developed by Yoyo Data Application accurately predicts the production period, yield, and prices Firstly, due to Wu Junxiao's precise mastery over agricultural data, Yoyo Data Application's clients don't necessarily need sensors or other hardware devices 'Sensors are expensive and if you buy cheap devices, you just collect a lot of noise or flawed data, which is useless,' Wu explains He continues, 'Collecting data doesn't necessarily require sensors our data solutions can solve problems more directly and effectively' For instance, one of Yoyo Data Application's products, the Yoyo Money Report Agri-price Linebot, developed in collaboration with LINE in 2020, gathers data on origin, wholesale, and terminal prices spanning over 10 years, driven by Yoyo Data’s proprietary AI algorithms This enables the system to autonomously learn about agricultural product trading prices, using big data and AI to perform price prediction analysis, thereby helping buyers reduce transaction risks and expanding the data application to the entire agricultural supply chain Regarding banana prices, the accuracy of price predictions increased from the original 70 to 998 Wu Junxiao notes that both buyers and farmers are very sensitive to prices Now, through the Yoyo Money Report service, both buyers and farmers can precisely understand the fluctuations in agricultural product prices Yoyo Data can also provide customers with optimal decision-making advice based on predictive models for crop growth, yield, and price estimations Currently, price predictions cover 28 types of crops Precise estimates of production periods and price fluctuations allow Yoyo Data to provide differentiated services based on data analysis The 'Yoyo Crop Algorithm System' provided by Yoyo Data Application incorporates a 'Parameter Bank', usually collecting 200-300 parameters, not just straightforward data like temperature and humidity, but also data divided according to the physiological characteristics of the crops Through effective dynamic data algorithms, it can accurately calculate when crops will flower and when they can be harvested, what the yield will be, and so forth For instance, the prediction accuracy of the broccoli production period is 0-4 days, with the flowering period predicted this year to be precisely 0 days, perfectly matching the actual flowering time in the field In these dynamic calculations, a 7-day range is considered reasonable, and the average error value of Yoyo Data's predictions typically ranges from 2-4 days, with most crop production period accuracies above 80 Through effective dynamic data algorithms, over 120 global crops can have their production periods and yields accurately estimated Using these effective dynamic data algorithms can set estimates for production quantities, helping adjust at the production end Yoyo Data Application's clientele primarily includes exporters of fruit crops like pineapples, bananas, guavas, mangos, pomelos, sugar apples, Taiwan's agricultural production is highly homogenized, often leading to a rush to plant the same crops and resulting in price crashes Yoyo Data Application helps clients differentiate their offerings Thus, Wu Junxiao positions his company as a boutique digital consultant, carefully selecting clients for quality over quantity He notes that Taiwanese agricultural clients focus on how to improve yield rates, even categorizing yield rates by quality, aiming for high-quality, specialized export markets whereas international clients prioritize maximizing per-unit yields, showing different operational approaches in domestic and international markets In addition to agricultural fruit, Yoyo Data Application has also extended its services to the fisheries sector, including species like milkfish, sea bass, and white shrimp, all using the same system to establish various parameters related to the growth of fish and shrimp, such as when to feed and when to harvest, and the anticipated yield, timing, and prices Yoyo Data Application harnesses the power of data to create miracles in smart agriculture In response to the company's rapid development, Yoyo Data Application introduced venture capital funds in 2021 to expand its staff and promote its business Wu Junxiao states that in response to the global trend towards net zero carbon emissions by 2050, he plans to help clients plant carbon in the soil, effectively retaining carbon in the land while also connecting clients to carbon trading platforms, creating environmental business opportunities together Wu Junxiao says that from the start of his entrepreneurial journey, he positioned the company as a global entity, thus continuous international collaborations are planned As a data company serving a global clientele and focused on climate technology and the green economy, this represents Wu’s expectations for himself and his company's long-term goals Yoyo Data Application founder and CEO Wu Junxiao「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

2022-03-14

【2020 Application Example】 "AI Color Recognition and Cost Optimization Control System" automatically recognizes colors, breaks through the traditional color grading model, significantly reduces costs, and improves yield!

Mixing new colors relies on the experience of master craftsmen The so-called "computer color matching" in the paint industry is simply the selection of "existing colors" for mixing, but there is actually no way to mix paint for a ldquonew colorrdquo and it all relies on the experience of master craftsmen Hence, it is necessary to start from scratch when a new color is encountered, which consumes a lot of manpower and time Moreover, due to the different color mixing habits of each master craftsman, the cost can be significantly different despite producing the same result The trilogy when paint factories face the crises of transformation I Lack of color mixing standards Generally, when traditional paint factories produce new colors, they will use a "spectrophotometer" to measure the LAB value of the sample color, and then the paint mixer will mix the paint of that color based on past experience After color mixing is completed, the instrument will be used to test the LAB value and C and H wavelength This process does not have a complete system and database records, and there are not standards for color mixing II Production costs are difficult to control Paint factories produce many pigments with different materials and functions, and the cost of paint will vary depending on the "color masterbatch material" used Even if the color number of the masterpiece is the same, the cost will be different if the ratio of the color masterbatch is different Paint mixers do not have a set of color mixing standards when mixing paint, making it difficult to control production costs III The color grading process is lengthy and personnel training is difficult As instruments cannot replace manual color mixing, the training of a paint mixer requires years of experience in paint mixing, familiarity with chromatology, as well as basic understanding of hue, saturation, and brightness If there is no basic reference color values when mixing paint, the paint mixer must spend a lot of time repeatedly mixing colors, resulting in a loss from time cost Developing an "AI Color Recognition and Cost Optimization Control System" The paint factory engaged in industry-academia collaboration with the Department of Computer Science amp Information Engineering of Chaoyang University of Technology through CDIT Information Co Ltd, and utilized the university's AI research capabilities to jointly develop the "AI Color Identification and Cost Optimization Control System" It established a database of "paint color numbers" and "color masterbatch material cost," and analyzes the optimal color mixing and optimal cost formula through data mining methods The paint mixer can refer to the formula analyzed by the system for color mixing, and then input the formula into the system after paint mixing is completed The formula is fed back to the basic database and an "artificial neural network model" is used by the system for deep learning, establishing a color grading standardization system for cost control and data collection, so as to solve the current difficulties faced by paint factories In the early stages of system development, CDIT planned the system requirements of the paint factory, established the system architecture and system database, and then worked with Chaoyang University of Technology on the implementation of model functions for the application of data mining and artificial neural network After the system is completed, CDIT will assist the paint factory in system testing and correction The system will be introduced after correction and testing are completed, and training on system use will be provided to ensure the correct use of the system System Screen Differences before and after using the system Expand new markets for the paint industry to see the paint industry thrive The "AI Color Recognition and Cost Optimization Control System" collects the color mixing formulas of paint mixers, establishes a paint color masterbatch formula database, and records the cost of each color number The system's deep learning function is then used with a spectrophotometer to analyze the optimal color mixing formula for each data entry, so that the paint factory can control the cost of paint mixing The optimal color mixing formula recommended by the system increases the speed of paint mixing and increases output value Future benefits include The improvement in product yield reduces customer complaints and improves customer satisfaction The breakthrough in the traditional color mixing model improves corporate image Improves the efficiency of paint mixing, and allows the remaining time to be invested in training to enhance the professional capabilities of personnel It will also allow the joint expansion of new markets with the paint industry and learning of new application technologies, and promote them to other paint companies, enhancing the industry's overall competitiveness to see the paint industry thrive

2020-08-11

【2021 Application Example】 Advancing to Smart Logistics 5.0: Hsinchu Logistics Delivers Medical Materials with Ultra-High Efficiency

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」

2021-10-14

Records of Solutions

【2020 Solutions】 Instantly Recommend the Right Products: Taimi Increases Your Customer Conversion and Retention Automatically

Have you ever had an experience where, while randomly browsing online stores, it seems like the website can read your mind, constantly recommending products you want to buy Recommending the right product to the right customer at the right time For example, when you see a piece of clothing you like, similar items or accessories that could match it immediately appear below, and before you know it your shopping cart gets fuller and fuller The reason the webpage understands you so well is primarily due to the implementation of an AI engine that can automatically analyze customer preferences and recommend the right product at the right moment, invisibly increasing the consumer's purchasing intent and stabilizing the platform's customer base This is the expertise of Taimi Rosettaai Taimi Rosettaai provides software services to e-commerce platforms aimed at increasing conversion rates and customer retention rates, by analyzing consumer preferences through various AI engines and recommending personalized products online and offline Taimi Rosettaai is an internet company specialized in creating one-stop customer conversion and retention services for e-commerce, analyzing consumer behavior through various AI engines, and recommending personalized products both online and offline Referring to the previous mention of online shopping, throughout the entire shopping journey, clever integration of different AI engines on various situational pages—home page, product page, category page, shopping cart, checkout page—these designed APIs tailored to consumer needs and shopping contexts further deepen the analysis of consumer preferences Through accurate sales forecasting, it elevates the consumer experience and conversion rates Throughout the entire shopping journey, Taimi Rosettaai is capable of installing different AI engines on various pages, instantly recommending the right products in the right context, thereby invisibly enhancing consumer's purchasing intentions Different AI engines analyze different situations to create consumer return flow and increase lift-to-cart rates For instance, if a consumer lingers on a page buying a coat, not only similar styles get recommended below, but there may also appear clothing or accessories that complement that coat, such as undergarments, pants, belts, bags, etc The system will also consider the consumer's past shopping habits and recommend items they might be interested in For instance, if the consumer has previously purchased a DSLR camera, the page might suggest camera bags, cleansing kits, etc, relevant products Through AI technology, cross-analyzing merchandise information with customer preferences achieves personalized promotions Besides targeting the e-commerce market, Taimi Rosettaai also actively expands overseas, collaborating with major domestic and international accelerators in recent years, and hopes to apply its capabilities in different industries to seek more collaboration opportunities Taimi Rosettaai offers a variety of instantly usable API modules and basic situational combinations, allowing users to choose according to the characteristics of their website, without the need for large investments in building an AI infrastructure This enables clear understanding of customer preferences, significant reduction in marketing costs, and even inventory forecasting, thus effectively increasing e-commerce revenue Besides focusing on the e-commerce market, Taimi Rosettaai is also actively expanding overseas, having been selected by well-known domestic and international accelerators such as AppWorks, Founder Institute, Orange Fab, Zerothai, etc, over the past two years It also hopes to apply its capabilities to different industries in the future, seeking more collaborative opportunities Taimi Rosettaai official website「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

【2019 Solutions】 Massive Digital Engineering: Smart Badminton Rackets Make Training More Fun!

For many professional team trainers, recording players' training conditions in the past often required manual effort However, by mounting sensors on sports equipment and combining them with corresponding AI devices, it's now possible to easily record training data Massive Digital Engineering has launched the napa smart badminton racket, digitizing the often abstract actions in sports, which assists athletes in finding the right training direction Introduction to Massive Digital Engineering Established in 2000, Massive Digital Engineering focuses on data analysis and mining in areas such as ERP, Industry 40, and financial big data It services manufacturing industries like chemicals, sports equipment, and automotive components, as well as various retail and distribution sectors by offering system development, customization, installation, and integration, helping companies enhance operational efficiency The company excels in cloud big data, using publicly traded financial databanks to design up to 92 financial assessment standards, which serve as benchmarks for businesses to improve their corporate structures Additionally, in response to Industry 40 and smart manufacturing trends, Massive Digital Engineering continues to develop innovative intelligent technologies aiming to boost production efficiency while reducing costs and pollution The napa smart badminton racket handle embeds high-performance sensors that automatically transmit the collected data for AI-driven analysis to an app Massive Digital Engineering showcased the napa smart badminton racket at the AI HUB Conference Recently at the AI HUB Conference, Massive Digital Engineering unveiled the extensively developed napa smart badminton racket, digitizing complex and hard-to-measure sports movements applicable in various competitive sports This tool helps coaches in training and assists athletes in finding the right direction For leisure and entertainment, the napa smart badminton racket can transform traditional courts into smart courts, complete with real-time data display boards on both sides of the court This not only displays scores during matches but also enables players to instantly access various swing data, vastly enhancing the fun and interactive aspect of the game With years of experience in data analysis and mining, one may wonder why Massive Digital Engineering ventured into the sports domain It turns out that there is a backstory involving long-term subcontracting work for the well-known sports brand WILSON, combined with the good reputation of its own Napa badminton rackets and familiarity with badminton-related products Hence, starting from the basic physical product of the racket, years of AI research were integrated into the development of the napa smart badminton racket project The sensors on the racket record all swinging actions including speed, posture, energy use, and striking force, and even 3D swing trajectories can be reviewed via the app But how does the napa smart badminton racket work Here's the principle sensors embedded in the racket handle automatically collect data, which, through AI algorithms, is linked to cloud big data When connected to a smartphone, various sports records can be viewed via an app The racket's sensors document every swing—its speed, energy consumption, posture, and power—and even 3D trajectories If used with a smart wristband on the same hand, it can also monitor heart rate and blood pressure, then through various big data applications, provide personalized scientific sports recommendations For instance, some players may swing too broadly with enough power but incorrect direction, or they may exert too much force during a swing but lack strength during impact These common training issues can be effectively addressed and improved through the napa smart badminton system Besides the napa smart badminton racket, the napa intelligent system can also be applied to baseball By installing sensors in the bat handle, swings can be recorded in real-time Smart sports application scenarios The primary target audience for napa smart badminton includes players and coaches, and it is also suitable for individuals who want to train independently Beyond badminton, the napa intelligent system can be applied to other sports like baseball The underlying principle is similar, hiding sensors in the bat handle to instantly record swing trajectories, enabling hitters to more precisely determine the impact position and power point Additionally, integrating more professional training, such as weightlifting—where Hsu Shu-ching won two Olympic gold medals—has gained more national attention Traditional training predominantly uses verbal instructions, such as directing athletes to apply a certain amount of force backward or forward, but these descriptions are abstract Integrating the napa intelligent system into weightlifting, for instance embedding miniature sensors in silicone gloves, would allow precise tracking of movement trajectories through app data, making adjustments more accurate with systematic data Massive Digital Engineering is actively collaborating with various badminton venues, aiming to upgrade traditional courts to smart courts using the napa smart badminton racket Massive Digital Engineering has recently started collaborating with various badminton venues to upgrade traditional courts to smart courts using the napa smart badminton racket They also continue promoting through sports communities, sports digitalization, experiential marketing, and other diverse applications to revolutionize the current sports industry「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

【2019 Solutions】 Aurora Information 'AU Care Recognition Service System' Aiming at a 15 Billion Business Opportunity by Enhancing Medical Completion Rates

As the population ages, home care has become a universal issue In the face of low medical staff ratios, whether in hospitals or external care facilities, medical personnel face the challenge of insufficient manpower Aurora Information has introduced the 'AU Care Recognition Service System', aiming to enhance medical completion rates through AI and 3D imaging technology Aurora Information introduces the 'AU Care Recognition Service System' using non-contact 3D imaging technology to instantly detect patient movements and physiological data from beds, significantly enhancing medical completion rates The 'AU Care Recognition Service System' incorporates Time-of-Flight ToF and mmWave Radar sensing technologies, coupled with point cloud and mmWave deep learning analysis AI algorithms, significantly strengthening computer vision and image processing capabilities Preserving Personal Privacy While Precisely Monitoring Patient Admission Status Aurora Information recently showcased the 'AU Care Recognition Service System' at the AI HUB conference With the use of Time-of-Flight ToF, mmWave Radar, and other sensing technologies, along with point cloud and mmWave deep learning analysis of AI algorithms, it greatly enhances computer vision and image processing capabilities Additionally, unlike traditional cameras that raise personal privacy concerns, this system uses non-contact 3D imaging technology for tracking bed exits and physiological data, providing instant notifications to users The system offers long-range, multi-target, high accuracy, continuity, and persistence advantages, all while maintaining patient privacy and precisely monitoring various admission statuses Through 3D imaging technology, when detecting potential danger actions like falls or tremors on the screen, it can immediately alert designated personnel or medical stations within 3 seconds, lowering the chances of sudden patient deaths The 'AU Care Recognition Service System' also measures heart rate, respiration, and other physiological data, using AI algorithms to predict the likelihood of sudden death 3D Imaging Technology for Immediate Reflection of Patient Emergency Situations How does it work in practice Suppose a patient falls out of bed when unattended, traditionally, they could only passively wait for help However, with the 'AU Care Recognition Service System' using 3D imaging technology to detect actions such as falls or tremors, it can immediately notify designated personnel or medical stations within 3 seconds, reducing the chances of sudden death by 20 it also measures heart rate, breathing, and other physiological data, using AI algorithms to assess the risk of sudden death, potentially reducing the death rate by over 40 Moreover, the system can simultaneously assess multiple patients, infants, and the elderly, enhancing timely care efficiency by more than 20, thereby significantly lightening the burden on medical staff Through the smart monitoring interface, medical personnel can clearly see real-time conditions in hospital wards or stairways, with intuitive icons helping them grasp the situation immediately Amidst the global challenges of aging and chronic diseases leading to high medical care costs, the 'AU Care Recognition Service System' effectively addresses the pain point of insufficient medical care According to the medical data released by the Ministry of Health and Welfare last year, if the 'AU Care Recognition Service System' were to be standardized, the market size for Taiwan's medical care institutions alone would be as high as 15 billion NTD Currently, Aurora Information is actively cooperating with the government, universities, and nonprofit organizations, hoping to contribute to medical care「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

【2019 Solutions】 Do products need 'AI Face Recognition' to qualify? The era of smart imaging has arrived, spearheaded by Juou Technology's interdisciplinary developments.

AI information technology can be utilized in very distinct industrial fieldsUnmanned factories, automated production lines, and robotic arms, etc To accelerate production lines to achieve economies of scale and simultaneously reduce costs, major production lines look forward to continuously optimizing in various aspects to reduce errors and increase yield rateIn the production line, quality control testing is a critical step that significantly impacts product quality Taiwan's Juou Technology Corporation stands out in its research and development efforts, not only addressing the management of Taiwan's resources and urban-rural development issues but also in its performance through innovative cross-disciplinary integrationWithin Juou's GEO IOT plan, two parts of the cross-disciplinary technology project are implementedPart oneWithin the AOI technology area, there is active investment in the technical development of big data, artificial intelligence, and data science It also involves the development of a high-speed, high-precision optical imaging inspection system in the production line quality management This technology utilizes machine vision with high focus and sensing to capture the surface images of products and automatically assess whether the products meet the quality standardsThis non-contact inspection tool not only speeds up the inspection process and identifies product defects but also automatically discriminates flawed products It is also applicable for the inspection of semi-finished products in the production line In enterprises that are major producers in Taiwan or those with a focus on quality, this optical combined with image processing system is necessaryPart twoBlood tests, crowd recognition, access control in danger areas construction sites, IVS, AIR vehicle controlBiometric recognition technology utilizes the characteristics of organisms for identification, including iris, retinal, and body shape recognition It also enables the monitoring of people flow within a specific space to quickly capture more information about crowd movements Beyond handling crowd recognition, Juou Technology also employs recognition technologies for control and monitoring of hazardous areas such as construction sites and production lines For instance, in spatial detection technology—if a construction worker forgets to wear a safety helmet or safety suit, the detection equipment will notify them upon entry to the site, thus reducing risks caused by human oversightCommitted to the innovation of the brand and the integration between sectors, it is believed that through digital technology and multi-disciplinary integration, the sustainable and innovative development of Taiwan will be driven「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

【2019 Solutions】 Chester SchoolBot Robot - Creating the Optimal Communication Platform for Parents and Teachers

For parents with young children, discussing matters with school teachers via the instant messaging app LINE is a good method Although LINE groups are convenient, if there are too many people talking at once, it can make what should be simple communication inefficient Starting from the service of campus smart vending machines, solving the pain points in parent-teacher communication In order to facilitate better communication between parents and schools, Chester International Co, Ltd and Zhonghua Lin Co, Ltd have collaborated to launch the SchoolBot service In fact, last year when Chester deployed the iMvending smart vending machine service at Taipei's Xingan Elementary School, they observed many communication pain points between parents and teachers This influenced the development of SchoolBot Utilizing the popular instant messaging app LINE as its platform, SchoolBot is essentially a robotic assistant for schools, incorporating LINE Bot and AI auto-response technology, and offering a pioneering one-on-one communication method that eliminates the clutter of traditional LINE groups SchoolBot incorporates LINE Bot and AI automatic response techniques, along with a pioneering one-on-one communication method in Taiwan, ensuring avoidance of the chaotic situation common in traditional LINE groups Automatic categorization makes it user-friendly, and privacy is secured Thanks to the adoption of AI technology, SchoolBot offers more applications than expected, providing a user-friendly and intuitive operation experience, as if chatting with a real person Whether helping children take leaves, sending messages to specific teachers, the system emphasizes categorization, allowing schools to identify and send messages to the appropriate recipients For parents, aside from basic inquiries, SchoolBot also supports categorization by child's student ID Upon the first use, when parents input their child's student ID, the system automatically categorizes it into the corresponding class, eliminating the need for manual selection and ensuring privacy security Whether helping children take leaves or sending messages to specific teachers, SchoolBot provides a smooth and intuitive operation experience, similar to chatting with a real person Additionally, SchoolBot caters to the common discussion scenarios faced by teachers and parents, integrating a practical online survey service This not only saves time and streamlines work processes for teachers but also supports the modern trend of going paperless Notably, the SchoolBot system automatically 'levels up' at the start of a new academic year, automatically advancing students to the next grade level, addressing the manual update problem that similar services face Chester has already collaborated with Xingan Elementary School, and hopes to expand the service into various community-based scenarios, creating a more convenient communication platform Besides schools, SchoolBot is also suitable for various scenarios like daycare centers, tutoring centers, and parent associations Chester has already partnered with Taipei's Xingan Elementary School and plans to continue expanding SchoolBot to other places, aiming to build a more convenient communication bridge for community-based scenarios「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

【2019 Solutions】 CyberLink FaceMe: Not Only Gender and Age, but Emotions Can Also Be Fully Detected

AI facial recognition has become an extremely popular topic in recent years and has been widely applied across various fields CyberLink's FaceMe facial recognition engine utilizes deep neural network learning algorithms, enabling comprehensive detection of not only gender and age but emotions as well CyberLink recently showcased the FaceMe facial recognition engine at the AI HUB conference, highlighting its capability to accurately pinpoint up to 106 facial feature points using deep neural network algorithms CyberLink presented the FaceMe facial recognition engine at the AI HUB conference CyberLink has devoted years to developing AI facial recognition and facial attribute technology, recently demonstrating the FaceMe facial recognition engine at the AI HUB conference Its standout feature is its precise localization of up to 106 facial feature points using deep neural network algorithms This makes it easier for developers to build dynamic 3D facial models and features a high accuracy recognition rate of 995 and a very low error rate, along with a software development kit SDK that enables system integrators and solution developers to incorporate high precision facial recognition technology into various products and services as needed The FaceMe facial recognition engine boasts a 995 accuracy rate How powerful is the FaceMe facial recognition engine It can detect not just basic attributes like gender and age, but also abstract ones like emotions At the recent AI HUB conference, CyberLink demonstrated this technology, showing that at the bustling venue, the FaceMe engine rapidly recognizes facial attributes such as age, gender, skin color, and head movements as soon as someone enters the camera's range and can even calculate emotional indices like surprise, happiness, anger, and sadness from slight facial changes The FaceMe facial recognition engine can detect subtle facial changes and calculate emotional indices such as surprise, happiness, anger, and sadness Applications of FaceMe facial recognition technology How can the FaceMe facial recognition technology be applied Imagine a scenario where police are tracking a criminal By focusing the search in a busy train station lobby using the FaceMe engine, every face can be detected and quickly matched with facial databases based on detected features, while also monitoring fluctuations in emotional indices to deduce potential suspects The FaceMe facial recognition engine provides various anti-spoofing mechanisms that can target the built-in camera lenses of mainstream mobile devices to prevent circumvention of access control systems using photos or videos of faces It's worth noting that the FaceMe AI facial recognition engine is compatible with mainstream platforms such as iOS, Linux, Windows, and Android It is suitable for a full range of devices from fully-equipped workstations to small, low-power devices Offering high precision and real-time advantages, the engine is suitable for scenarios like smart retail, smart finance, smart security, public safety, smart home, and more, making its potential applications in AIoT promising「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

【2019 Solutions】 NexCOBOT - Smart Self-Checkout System Makes Future Shopping Convenient

Imagine a future where all shops have no clerks, fully replaced by smart devices Simply placing items on the table and letting the intelligent self-checkout system handle the rest makes shopping convenient and easy This scenario is not far-fetched, as unmanned store projects have already emerged in Taiwan, such as the recent multi-million investment by FamilyMart to create their second tech-concept store Through human-machine collaboration and the latest technology, they aim to alleviate clerical work, and NexCOBOT hopes to bring this concept into unmanned stores to simplify the checkout process for consumers NexCOBOT introduces a smart self-checkout system, aiming to incorporate this technology into unmanned stores, simplifying the checkout experience for consumers Dedicated to smart retail solutions to enhance consumer technology experience NexCOBOT, a subsidiary of NEXCOM, specializes in the independent development of six-axis robots and smart retail solutions With the rise of the Internet of Things, the line between physical and virtual commerce has blurred NexCOBOT identifies three foundational elements of IoT commerce smart retail, smart logistics, and cloud-based real-time management systems Continually, NexCOBOT commits to smart retail solutions, addressing major pain points for business owners while considering enhanced technological experiences for consumers, hoping to pioneer unprecedented innovative applications When it's time to check out, simply place the items on the table, and a scanner will identify the products and display both the items and prices on the screen How does NexCOBOT's smart self-checkout system work When checking out, place the shopping cart's items on the table An overhead scanner performs image recognition, then the screen displays the types of products and the amounts Payment can then be made using cards, smartphones, or other payment devices It can even integrate with facial recognition systems, allowing customers to pay through face scanning, which saves the time previously spent scanning barcodes and queuing Additionally, the store can utilize backend analyses to track customer data and popular products Due to the need for precise image scanning, a detailed product database must be established beforehand The store can also analyze customer data and popular items through backend analytics Establishing a product database to gain control of product information Precise image scanning requires that all items have a previously established database Scanning could include detailed 3D images of merchandise like cookie boxes or drink cans The more detailed the database, the faster the checkout process and the more effective the backend analytics However, because of limited space on counters, scanning large volumes of merchandise could be problematic Initially, items easily recognizable like those in bakeries might be prioritized Additionally, NexCOBOT offers modular solutions such as smart shelves, smart self-order systems, smart self-checkouts, smart marketing dashboards, etc, all customizable as per the client's requirements Integration with existing systems such as Point of Sale POS, Enterprise Resource Planning ERP, Customer Relationship Management CRM, and Digital Signage is also feasible Besides using payment devices, it can even integrate with facial recognition systems, allowing customers to pay through facial scanning, eliminating the need for manual barcode scanning「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

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