A brilliant idea transforming AI facial recognition technology As artificial intelligence develops, more and more industries are embracing AI technology, even subtly entering into people's lives As most bakeries sell freshly made bread and pastries, which typically do not have barcodes, they rely on cashiers to visually identify each item and enter the type and price of the bread Thus, inspired by AI facial recognition technology, if such artificial intelligence could identify hundreds of types of bread, it could enhance checkout efficiency Diverse handmade breads delight customers but challenge clerks A local bakery has over 100 types of bread, regularly updating or adding new products, offering customers a variety of choices this poses a challenge for cashiers It takes two months to train a cashier, but even after they start, there's still a 5 to 10 error rate due to bread recognition mistakes each month, especially during peak checkout times after work, causing bottlenecks and further errors due to the stress on cashiers The difficulty in training cashiers and the lack of precision in the checkout process have long troubled businesses When baking meets artificial intelligence, it sparks a marvelous retail experience In typical bakeries, bread is sold 'naked' immediately after baking and then 'packaged' when it cools to room temperature Both methods require cashiers to recognize and remember the prices and undergo two months of training before they can work the cash register Even then, there is still a 5 to 10 error rate each month My Dee Bakery, with its extensive range of over 100 bread types, poses a significant challenge for cashiers Due to Yun Kui Technology Co, Ltd's expertise in developing iPad POS systems, which are designed to be simple, convenient, and easy to use, they allow businesses to check out efficiently and accurately Therefore, integrating the existing POS system with AI image recognition capabilities enables businesses to carry out transactions more efficiently and precisely AI bread recognition model operational schematic Image provided by Yun Kui Technology The execution can be simplified into eight steps, which include 1 Data collection Take bread image data at bakeries 2 Image annotation The image data is handed over to Mu Kesi Co, Ltd for manual annotation 3 AI modeling and training Managed by Mu Kesi, who adjusts AI models and training 4 iPad POS adjustment Simultaneous adjustments of the UI interface on the POS side and backend integration with the AI model 5 Start testing Once Mu Kesi reaches over 95 recognition accuracy with current data, formal integration testing begins 6 Real scene testing Move to the bakery to gather data and verify the correct recognition rates 7 Planning real scene application accessories When recognition accuracy exceeds 98, design accessories for on-site checkout, such as remote cameras and projection light sources 8 Official Application Integration with electronic receipts goes live POS machine AI bread recognition checkout process Start recognition - Recognition complete - Checkout - Confirm checkout, takes only 3 seconds Image provided by Yun Kui Technology AI bread recognition system, making multitasking easy After adding AI capabilities, not only can it save upfront training time and costs for bakery cashiers and reduce costs from recognition errors, but it can also speed up the checkout process and efficiency, increasing customer satisfaction This can later be promoted to various retail industries, expanding the new map of smart retail Before and after comparison chart of the bread checkout process with AI valuation Image provided by Yun Kui Technology「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

Best practices in AIIoT implementation As our country enters the first year of 5G commercialization this year, the integration of the Internet of Things with artificial intelligence to transmit data with zero delay will enable everyone to effectively manage all data Toilet 'odor monitoring' has become the best platform A certain chain supermarket in the country has 47 stores nationwide and in recent years, as competition in the supermarket industry intensifies, some stores plan seating areas and toilets for customer use Currently, the average number of customer complaints about toilet cleanliness in a certain store of the chain supermarket is about 10 times per month, which is notably higher than other stores, thus they hope to solve the problem of high complaint rates through artificial intelligence Customers frequently complain about dirty toilets The toilets of a certain store of the chain supermarket are inspected at 12 PM and 6 PM daily, and cleaned during the night shift Customer service staff often receive complaints about the dirty and smelly toilet environment, causing the need to constantly deploy manpower for toilet maintenance To achieve a 100 odor-free toilet, it would be necessary to employ a cleaning staff member permanently present in the toilet, however, this solution is too costly and wastes manpower Through a collaboration between Guo Xing Information Co, Ltd and the chain supermarket, the National Taichung University of Science and Technology AI team was commissioned to address this vexing issue using IoT and AI technologies IoT Monitoring x AI Manpower Dispatch Guo Xing Information equipped the toilet door locks with IoT sensory devices, and installed 'odor sensors' and 'air temperature and humidity sensors' outside the cubicles By monitoring the behavior, frequency, and timing of door usage, it predicts the cleanliness of the cubicle If a person opens the toilet door and closes it quickly, and if more than three consecutive people exhibit the same behavior, it predicts that the cubicle is dirty enough to require cleaning In terms of manpower dispatch, the system predicts staffing needs based on user frequency, holidays, and festive events, dynamically adjusts manpower reserves, and calculates the minimum staffing needed to maintain toilet comfort Service architecture of the Smart Toilet Quality Monitoring Platform This 'Smart Toilet Quality Monitoring Platform' is installed in the open-area toilets of business premises, collecting data such as usage frequency, time, odor intensity, air temperature, and humidity, and transmitting it to the platform for AI data analysis This enables management to understand the real-time usage, frequency, and dirtiness of the toilets, providing alerts to dispatch cleaning staff and take responsive actions It also assists managers in environmental quality monitoring and dirty conditions predictive dispatching Through historical data analysis, it suggests dynamic manpower deployment during different time intervals for effective human resource management and utilization Smart toilet detection, reducing cleaning labor costs After field tests of the Enhanced AI Smart Toilet Monitoring Platform, the retailer found the real-time monitoring and alert features extremely practical and is willing to continue using them Regarding 'reducing the number of complaints', a one-month data validation showed a significant effect, while 'dynamic manpower dispatch' is still under evaluation and validation After a month of data evaluation, a noticeable improvement was found in 'monitoring toilet usage' and 'reducing complaints' After trial use by the retailer, they are also willing to continue using the system In the future, notifications will be made according to 'usage time' to prevent accidents within the cubicles There will also be future deployments and promotions priced at low, mid, and high levels「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

The introduction of the 'AI Medical Imaging Identification System' assists radiologists to conveniently and quickly complete image identification tasks, reducing their workloadDifferent Non-Invasive OptionsMedical imaging recognition is an important task for radiologists, who must make professional judgments based on patient examination data When a tumor is discovered, it is necessary to determine whether it is cancerous The possible methods include non-invasive medical imaging and invasive biopsy Although the invasive biopsy has a high accuracy rate, it also causes significant physical and psychological stress to the patientCurrently, imaging recognition can only determine the presence of tumors, not yet able to detect the difference between benign and malignant tumors To distinguish benign and malignant breast tumors, Datong World Science Company has assisted the Imaging Department of Changhua Christian Hospital, the first hospital in Taiwan to introduce the 'AI Medical Imaging Identification System' This system has increased the accuracy rate of artificial intelligence mammography in distinguishing benign from malignant tumors to 85, allowing for a shift from the original binary approach to a probability expression of BI-RADS gradingAI Medical Imaging Identification System Enhances Breast Cancer Diagnosis Accuracy to 85The AI medical imaging recognition system can assist radiologists in making quick readings Initially, it will target mammography When a tumor is detected, determining whether it is cancerous requires a pathological biopsy or mammography Pathological biopsy is invasive and, although more accurate, carries higher tangible and intangible costsMoreover, it helps improve the efficiency and accuracy of mammography readings Furthermore, optimizing the mammography reading process will reduce the workload on radiologists and decrease the waiting time for patients for examination results Additionally, with the aid of artificial intelligence, it helps reduce differences in radiologists' subjective judgments and prevent human errors, helping the institution to establish common standards and enhance collaborative efficiency among doctors from different specializationsCNN Convolutional Neural Network ModelIn addition to assisting doctors in making quick readings, here are summarized benefits of introducing the AI Medical Imaging Identification System1 Provides AI-assisted BI-RADS grading for mammography, helping radiologists in interpretation2 Optimizes medical imaging recognition processes, enhancing the degree of automation of existing procedures3 Uses local medical images to retrain models4 Adopts superior CNN models to improve accuracy and stability of the system5 Defines the relationship between BI-RADS grading and AI's readings of benign and malignant tumors transitioning from a basic dichotomy to a probability representation in BI-RADS gradingThe prerequisite for deploying artificial intelligence in medical assistant decision-making is that the accuracy must exceed 85, providing a valuable reference for radiologists With the support of artificial intelligence, the time for radiologists to interpret a single x-ray mammography image and assign a BI-RADS grade has been reduced to 50 of the original time, from about 10 minutes to under 5 minutes, offering an efficient and accurate AI-assisted outcomeChairman Baiyan Shen of Datong World Technology Co, Ltd「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

The COVID-19 pandemic has spurred the popularity of delivery platforms such as Uber Eats and Foodpanda, creating an urgent need for smart dispatch systems Imagine if drivers could determine from their mobile phones or online platforms where there are no traffic jams, which roads have the fewest traffic lights AI could help plan the most suitable schedules, significantly improving logistics efficiency and reducing overwork With the flourishing of commercial activities, the logistics sector, which provides personnelgoods movement services, lacks smarter scheduling According to research by the international research organization Gartner, 97 of the global logistics industry does not use optimized software for effective planning Smart Scheduling Resolves Stakeholder Pain Points Let's first understand where the pain points lie among stakeholders in the logistics industry chain Employer's perspective In response to various types of delivery services, especially new types like food delivery, how to increase performance without expanding the fleet size Dispatcher's perspective Vehicle scheduling is very challenging, and the bosses demand increased efficiency, which is difficult to achieve without computers Driver's perspective Poor scheduling by the dispatcher leads to incomplete deliveries or traffic jams, often requiring overtime, or even accidentally running red lights, resulting in fines Addressing these issues, Zong Lan-Ken, founder and CEO of Singularity Infinite, states, 'All these problems are classical mathematical problems' Singularity Infinite's AIR Smart Dispatch Cloud Service is a cloud-based software service that resolves last-mile delivery scheduling and routing issues It addresses daily challenges faced by operators in managing goods, vehicles, and routes, enabling them to handle more orders with fewer vehicles Smart Scheduling System Schedule Zong Lan-Ken, who specializes in data science solutions for public needs and formerly served as an associate research professor at the Geographic Information Systems Research Center of Feng Chia University, founded Singularity Infinite in 2015 He aims to solve smart mobility issues using mathematics, statistics, and software technology The company's developed AIRouting optimization technique provides real-time traffic data and dynamic planning to assist operators in more efficient dispatching Singularity Infinite integrates real-time traffic and signal information and can handle high-frequency unconventional logistics models, such as gourmet delivery and electric scooter battery swap strategies For example, electric scooters must replace their batteries after every 50 kilometers If a scooter runs out of battery, the rider leaves it on the roadside The scooter operator must locate the depleted scooter and replace its battery To maintain effective operations, operators must keep the utilization rate of scooters between 80-90 For instance, in the Greater Taipei area with 10,000 scooters, maintaining more than 8,000 scooters on the roads at any time is crucial, yet without a smart scheduling system, high utilization rates cannot be maintained Following the system's introduction by WeMo in 2019, the utilization rate significantly improved by approximately 75 Effectiveness of AIR Smart Dispatch Cloud Service Introduction AIR Smart Dispatch Cloud Service has effectively increased the utilization rate by 75 Additionally, in the food ingredient delivery logistics, there have been notable results Traditional ingredient delivery companies need up to 25 trucks per day to transport fresh ingredients from produce markets, agricultural marketing companies, or seafood markets to restaurants After introducing the AIR Smart Dispatch Cloud Service, the number of trucks required per day was reduced to a maximum of 12, significantly cutting over half of the truck costs Singularity Infinite's team includes experts in mathematics, transportation, and AI technologies The traffic information used is from OpenStreetMap, supplemented with province-wide real-time traffic flow data to analyze congestion during different periods Additionally, future plans include using signal timing data to calculate which road segments have the fewest red lights and shortest red durations, to plan optimal routes, reducing the burden on logistics operators and drivers Singularity Infinite's team, the picture third from right is Zong Lan-Ken, founder and CEO of Singularity Infinite Besides logistics and transport, AIR Smart Dispatch Cloud Service can also be applied in container yard stacking, factory machine scheduling, project management, hospital bed allocation or operating room scheduling, and flight gate assignments among other areas Singularity Infinite employs two business models One involves customizing exclusive scheduling systems for clients, paid monthlyyearly on a pay-per-use basis the other involves system integration followed by revenue sharing with the client Fundamentally, Singularity Infinite provides APIs for integration, allowing operators to develop their own apps or provide services through websites In the entrepreneurial process, what are the most challenging aspects Zong Lan-Ken believes that entrepreneurship is a continuous series of multiple-choice questions, simplifying numerous questions into fewer choices, further simplifying each option to choose the correct answer Previously, it was mistakenly believed that 'technology can solve problems', but it was discovered that efficiency issues can not be solely resolved through mathematics, as the world does not operate this way In this ecosystem, 'who' will stop adoption due to 'whose opinion' For example, in the logistics industry, the most critical aspect of transporting goods is the driver, who needs rest If the system is introduced, and scheduling becomes completely transparent, drivers do not get time to rest The wrong introduction makes the system a tool for exploitation Hence, it is essential to consider human aspects, integrating rest times into the mathematical model to gain driver support Also, by knowing beforehand that a driver's home is near a train station, scheduling the last stop near the station lets the driver return home right after delivery These examples can significantly increase driver acceptance and greatly enhance the success rate of project adoption Zong Lan-Ken finally points out that data collection is crucial to the success of traditional industries' digital transformation in the future Without data, there is no data science, and no AI Singularity Infinite holds patents for automated data collection and recording, which can reduce data collection costs At the same time, the collected and stored data's high usability will serve as an important foundation for future intelligent logistics「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

In the era of "if you don't manage your money, money will not care about you", how to avoid the risks of the investment market and grasp investment returns has become the biggest hope of investors In order to overcome the human weaknesses of greed and fear, financial management robots developed through AI algorithms can help investors avoid disasters and enjoy fruitful profits in the treacherous and ever-changing financial market On March 17, 2020, affected by the global spread of the new coronavirus pneumonia COVID-19, also known as Wuhan pneumonia, the US stock market continued to plummet after opening, triggering the third circuit breaker in the US stock market, which was also the fourth in history After the circuit breaker, investors in the securities market were in distress and could not even escape for their lives Before that, the financial management robot had suggested adjusting the proportion of stocks and bonds, reducing the proportion of high-risk stocks, increasing the proportion of relatively safe bonds, and adding high risk aversion Gold and other combinations enable investors to effectively reduce investment risks and losses Robotic financial management has two service models B2B and B2C The robot financial management service provided by Leading Information Technology Company provides investors with a stable financial management tool Peng Hansheng, co-founder and CEO of Leading Information Technology, said that Leading Information Technology currently provides two service models The first is the Taiwan B2B model, which is to cooperate with domestic financial institutions to provide robot financial algorithm engines, Artificial intelligence market prediction engine, jointly launch robot financial management services the other is an American B2C model, aiming to serve Chinese American customers, self-developed intelligent financial management APP Growin, using AI and quantitative models to provide customized investment and financial management in ETFs and individual stocks Serve Among them, due to restrictions on regulations, the B2B financial management robot launched by Leading in Taiwan is cooperating with the domestic financial industry, including banks, insurance, etc Currently Leading's partners include an investment advisory and credit company, and a life insurance company The company and two banks provide customer financial management robots as a trading tool that consumers can rely on In addition, Taiwan's leader in the information service industry - Jingcheng Information provides diversified financial information services to financial institutions Liding also provides investors with investment portfolio recommendations for smart financial management by connecting APIs to the Jingcheng Information system Smart financial management APP Growin uses AI and quantitative models to provide customized investment and financial services in ETFs and individual stocks The financial regulations in the United States are relatively mature, allowing companies to set up online investment advisory companies Liding connects with the US brokerage system through APIs, and the partner is Interactive Brokers, the largest and No 1 company in the United States Broker, providing direct consumer services Interactive Brokers customers can place orders directly through the APP and enjoy the services of the financial management robot The iOS version is currently available for download The robot financial management platform charges a management fee of 05-1 of the investment amount every year There are 10 investment portfolios for consumers to choose from Stocks with high investment returns have higher management fees If you choose relatively stable ETFs, the fees will be Less expensive The services of Liding Financial Management Robot are mainly focused on medium and long-term investment Taking the United States as an example, the investment targets include 5,000 stocks and 2,000 ETFs in the US market Among them, the average investment return rate based on different risk investment portfolios is 45 -18 or so, and ETF is between 45 and 9 Introducing AI algorithms into investment and financial management can not only significantly reduce the impact of human emotions, but also enable disciplined execution of every investment decision, more effective prediction of the market, and immediate response to its trends Robotic financial management targets retired people and focuses on medium and long-term investment Take the global stock market crash triggered by the impact of the new coronavirus as an example The original investment portfolio of the financial management robot had a stock and bond ratio of 7 to 3 respectively Shortly after the global stock market crash, it automatically reversed and adjusted to 3 to 7, that is, to increase the bond ratio Proportion, reduce the proportion of stocks to avoid high investment risks Peng Hansheng said that the financial management robot uses AI technology models to gather 18 important global market indicators and economic trend forecasts for the next 1-3 months It can provide reversal suggestions when the market is about to fall sharply and avoid high investment risks Therefore, in The losses were relatively minor amid a sharp decline in global stock markets However, relatively speaking, when global stock markets rose sharply in April, the growth rate of financial management robots was relatively small, which is suitable for steady financial investors who pursue long-term performance Peng Hansheng said that investor financial management through AI algorithms can overcome the investment mistakes that ordinary investors are easily affected by emotions, news or irrational selling At the same time, in the form of a basket investment portfolio, It can also effectively diversify risks and reduce investment losses Integrated learning concepts can achieve dynamic asset allocation effects return on investment The so-called "ensemble learning" solves a single prediction problem by building a combination of several models Its working principle is to build multiple classifiersmodels on the data set, each independently learn and make predictions, and these predictions are finally combined into a single prediction The predictions are therefore better than those made by any single classifier In addition, using an "unsupervised" training and learning method, also known as "Hierarchical Clustering", the system will automatically classify the investment targets within the target range every month, allowing the machine to learn Financial report information, value investment, and then improve operational performance The choice of robot financial management as an entrepreneurial theme is mainly related to Peng Hansheng's financial engineering background He graduated from the Department of Finance at Tsinghua University and later went to Columbia University to study financial mathematics After graduation, he entered Wall Street to engage in quantitative trading 2-3 year time Three years ago, after witnessing the sudden ups and downs of the stock market and investors' irrational pursuit of highs and lows, resulting in investment failures, Peng Hansheng decided to contribute what he had learned to Taiwanese society and founded Liding Information Technology Company, specializing in robot financial services It is hoped that through the new smart financial management method driven by AI, it can help investors avoid bad luck and manage their finances steadily The most difficult thing about promoting AI financial management is that according to statistics, when financial management robots make investment portfolio recommendations, up to 40 of investors do not follow them, unable to overcome human weaknesses, and the final result is a losing position getting bigger In addition, in the B2B robot financial management market, the business logic of banks and insurance industries is different from that of financial management robots For example, banks specialize in wealth management, and high-end customers usually prefer direct service from financial specialists and do not like to interact with machines Therefore, promotion in the banking industry is difficult In the future, bank financial professionals or securities traders will be targeted, making the financial management robot an investment advice auxiliary tool for financial professionals and stock traders Peng Hansheng, co-founder and CEO of Liding Information Technology 「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

Farmers work hard in the fields to produce the freshest, nutritious and delicious crops Without a good cold chain transportation system, not only will farmers’ hard work go to waste, but agricultural enterprises will also suffer losses due to temperature loss and damage to refrigerated goods Loss has also become a major pain point The AI cold chain transportation chain break warning system can help reduce costs and improve the efficiency of fruit and vegetable transportation and preservation Zhongtian Technology, founded in 2017, is committed to using Internet of Things technology to develop smart agriculture In addition to winning many awards such as the Smart City Innovation Application Award, it has also assisted private institutions such as Xingnong Group and the Agricultural Experimental Institute in the construction of Smart agricultural software and hardware equipment Monitoring temperature throughout the cold chain must rely on AI technology to assist Chen Zhiming, chief consultant of Zhongtian Technology and a professor at the School of Information at Lingdong University of Science and Technology, said that Xingnong Group, which has more than 200 fertilizer supply centers across the country, and its Yumei Research Company have the most high-end greenhouses in Taiwan, and its products include crops such as beef tomatoes , supplying Formosa Steaks, McDonald's, COSTCO and five-star hotels, etc Yumei Research itself has 3 refrigerated trucks and 12 refrigerated rooms However, the transportation of vegetables, fruits, fresh food and other food needs to be kept in a low-temperature environment The ambient temperature, humidity, carbon dioxide, position, and opening and closing of the transportation box during transportation need to be monitored in real time for owners to ensure Understanding whether the quality of refrigerated food storage and transportation is affected by temperature changes cannot be done through human monitoring and must rely on the assistance of AI technology Agriculture 40 simple APP operation interface At present, the general practice of cold chain equipment manufacturers is to place wireless temperature recording devices in refrigerated goods and transport them together to record whether the quality is affected by temperature changes during the entire transport process A small number of refrigerated trucks also use 4G networks to transmit The temperature information of the refrigerated space in the vehicle provides monitoring of temperature changes in the cold chain during movement However, the above two methods can only know whether the quality of the product is affected by temperature changes at the final arrival time, and cannot provide analysis and early warning for various conditions that may occur during product storage and transportation to ensure refrigeration Quality assurance and instant feedback of information during product delivery information Schematic diagram of cooperation between ICTIoT technology in agriculture Once the cargo status is abnormal or is about to occur, the AI system can immediately execute warning notifications, which can reduce the loss of broken links caused by environmental changes The overall cold chain monitoring scope extends from logistics and transportation to unloading, transshipment and storage, thereby building a complete cold chain monitoring system AI technology is introduced into the cold chain system, reducing product damage rate by 75 Chen Zhiming said that after the system is established, the proportion of refrigerated goods that are damaged due to temperature changes can be reduced by 75 At the same time, through AI intelligent judgment and statistical analysis algorithms, real-time information on each storage space, delivery vehicle and even pallets can be provided Usage status, it can provide intelligent scheduling and data analysis to increase the utilization rate of the overall cold chain system by 20, which is a good result Taiwan Fengkang Supermarket, owned by Yumei Research Company, has 48 stores north of Hsinchu in the province, with a wide range of products and 100 refrigerated trucks It is currently being planned by Guoxing Information, hoping to break the AI cold chain transportation chain The early warning system has been introduced into Fengkang supermarkets across the province, allowing consumers in metropolitan areas to enjoy better quality refrigerated fresh fruits, vegetables and food In addition to the AI cold chain transportation chain breakage warning system that solves the problem of freshness throughout the entire process "from the production area to the supermarket", agricultural enterprises also have a pain point In order to save electricity during the transportation process, outsourcing manufacturers may turn off the air conditioners on the vehicles In other words, during the 2-4 hour transportation process, the air conditioner may be turned on in the first half hour and the second half hour, and may be without air conditioning at other times In this situation, a Bluetooth data collector can also be installed in the pallet Temperature data is collected every five minutes to ensure that the goods are kept fresh throughout the transportation process Changes in refrigerated temperature trends Greenhouse temperature and humidity change trend chart Chen Zhiming said that Xingnong Group is Taiwan's leading agricultural enterprise Its subsidiary Guoxing Information can build a powerful AI expert system through knowledge in the agricultural field From greenhouses, logistics vehicles, warehouses, sub-warehouses to supermarkets, it can collect and collect data throughout the entire process Get refrigerated truck information For ordinary small farmers, resources are not abundant In the future, Zhongtian Technology will cooperate with Chunghwa Telecom to provide mobile APP promotion for a monthly fee to assist farmers in real-time monitoring of the environmental temperature, humidity, and wind speed required for planting Information such as direction, sunshine and rainfall can be used to facilitate farmers to respond early, and multiple fields can be controlled at the same time, which will greatly reduce the need for manpower and achieve the purpose of smart planting Chen Zhiming, Chief Consultant of Zhongtian Technology 「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

Fu-Shan Technology, specializing in deep learning, dynamic facial recognition, and image tracking and analysis, provided critical AI temperature screening technology during the government's fight against COVID-19, playing a key role as a valuable tool in pandemic prevention With the pandemic escalating, it's mandatory to wear masks and check temperatures in public transport systems However, in places with thousands of people, like factory areas or Taiwan Railways, it's challenging to measure temperatures individually without shortcomings AI thermal imaging a comprehensive temperature screening system In response to rapid outbreaks of COVID-19 and influenza, Fu-Shan Technology has integrated AI facial recognition with thermal imaging technology to launch an AI-based smart temperature screening and RTC self-health management system, achieving automated screening and real-time abnormal temperature alerting This also ties with AI facial recognition to provide employee temperature tracking and records in an electronic system, significantly reducing the burden of manual monitoring and queuing times Fu-Shan Technology’s CEO, Hong Kun-Yu, stated that existing thermal imagers can only identify the highest temperature source in the area and lack image recognition capabilities, rendering them as industrial thermal detectors For instance, in train stations, thermal imagers detecting items like coffee or lunchboxes exceeding the temperature limit would trigger false alarms Crowded places also fail to identify individual images for timely detection of febrile individuals Visual design makes it clear by displaying the temperature values on people Using dynamic facial recognition, the system can read the relative position of a person's face while targeting the forehead area for automated forehead temperature measurement This not only solves the issue of false alarms but also collects long-term, stable data to manage health Importantly, it captures images of individuals with abnormal temperatures and correlates them with temperature data, date, and time to trace their contact history, effectively preventing epidemic outbreaks Potential false alarms with thermal imagers Currently, Fu-Shan Technology has installed multipoint-thermal imaging systems for temperature screening in 21 train stations along Taiwan Railways’ western line, from north to south The system allows non-contact temperature measurement for over 2,000 people with good results, as evidenced by Transport Minister Lin Chia-lung who personally experienced the system on-site Transport Minister Lin Chia-lung experiencing the AI-based smart temperature screening system Aside from the camera, the AI thermal imaging temperature screening system comprises two software systems RTC rapid temperature check to digitalize and visualize the obtained temperature data, improving the response to false positives and abnormal temperature alerts and PTM personnel temperature management, which, in crowded places, utilizes facial recognition data to confirm identities and temperature changes Upon detecting abnormalities, it can trace contact history and infection sources to swiftly control the pandemic Collecting and managing public temperature measurement data Fu-Shan Safety Monitoring Solutions Broad Application As COVID-19 becomes more endemic like the flu, managing employee body temperatures becomes increasingly important CEO Hong Kun-Yu mentioned that even after the pandemic subsides, the personnel temperature management system PTM can integrate with the company’s attendance management system, automating temperature management for employees to proactively prevent problems Indeed, Fu-Shan has been deeply involved in developing human form and behavior analysis technology based on AI deep learning for 2-3 years The solutions include safety recognition for construction site personnel like hats and protective goggles, perimeter intrusion detection able to determine unauthorized entry, abnormal lingering, or abandoned objects within restricted areas, and excludes interference from leaves, animals, light, rain, etc Also, fire and smoke detection employs AI to overcome misreports from red and yellow colors, and foggy weather Fu-Shan’s core technology in dynamic facial recognition, using CNN convolutional neural network and powered by GPU, achieves facial recognition in just 0025 seconds It covers wide angles up to 75 degrees on the sides and 45 degrees vertically, overcoming issues from lighting, posture, and expressions, significantly enhancing recognition accuracy to 9951 It is applicable for factory perimeter safety, bank access management, facial recognition payment, license plate recognition, reaching pre-alert and real-time dealing in smart image monitoring Fu-Shan Technology’s CEO Hong Kun-Yu「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

"Why does the music industry need AI What problems can AI solve" These are the questions Zeng Zhizhong, the founder and CEO of Anpu Artificial Intelligence Co, Ltd, continuously asks himself Since founding the company in 2018, Zeng Zhizhong has understood market positioning and customer needs clearly Anpu uses AI composition to seize the global environmental music broadcasting market With the system online for over a month, AI has created more than 10,000 pieces of music, serving clients across cafes, car showrooms, restaurants, and hair salons with a "legal, free" broadcasting solution, becoming the first choice for stores Zeng Zhizhong is a serial entrepreneur with a background in both the internet and music He has served as the general manager of Taihe Music Group, director of music services for Microsoft and Nokia in Asia Pacific, founded AR company Emitia Technologies and streaming company Tianlida Technology, and currently operates a company called Ouster Music specializing in film and television soundtracks With a dual background in technology and music, Zeng Zhizhong navigates AI music to solve copyright dilemmas With his sharp senses in technology and music, particularly amidst the ongoing AI boom, Zeng Zhizhong constantly contemplates how to turn AI composition into a profitable business He analyzes examples such as Spotify with 100 million paid subscribers in the USA, 1 million in Taiwan's KK BOX, and the mainland China's IPO-listed QQ Music, all operating at a loss The primary issue lies with these platforms not owning the copyrights to the music they provide, despite offering membership subscriptions They must also pay royalties to record companies and creators, leading to 'the bigger they are, the more they lose' Zeng Zhizhong, with his tech and music background, hopes to carve a niche for AI-generated music In the music industry, there are two main domains ambient music background music, BGM and pop music Pop music involves a lengthy production chain including lyric writing, composition, arrangement, singing, harmonizing, mixing, and finalization, entailing high costs and investment risks Meanwhile, ambient music, used in malls, department stores, cafes, and restaurants, traditionally sees copyrights held by music industry associations in various countries, making acquisitions costly and time-consuming However, producing music in-house circumvents copyright issues Thus, composing with AI and retaining copyrights internally becomes a key to success According to the International Federation of the Phonographic Industry IFPI report, global music market revenues in 2018 grew by 97 to 191 billion, up from 174 billion in 2017 Streaming music revenue alone reached 89 billion, accounting for 47 of the global total, nearly half Publicly broadcasted music accounted for 10-15, marking a significant portion of the market Recognizing the immense potential of the market, Zeng Zhizhong then assessed the technical capabilities of AI music, candidly stating, "AI is not a cure-all" For concert performances or chart-topping pop music, human lyricists and composers are necessary to achieve desired effects, while AI composition typically handles simple, uncomplicated melodies Assembling a large music database coupled with proprietary AI algorithms for rapid music production Anpu Music's AI composition system utilizes algorithms that include Markov chains, neural networks, deep learning methods, and combines the company's proprietary algorithm MDN Music Deeplearning Network, which conforms to unique musical algorithmic theories, thus breaking through traditional pop music structures and styles to create more market-aligned music compositions The database aggregates a large amount of sheet music data from top charted tracks and renowned songs globally, initially analyzing and summarizing the characteristics and melodies of popular quality music, then employing deep learning for efficient and excellent outcomes in AI composition BGMRADIO公播平台上集結上萬首AI音樂 Anpu provides a clear AI solution for the complex music copyright environment, with a material library owning a vast amount of clear-cut copyrights over 10,000 music tracks in 50 different styles, allowing users to freely choose suitable music to enjoy Anpu's current business model is twofold one provides a web-based platform offering 10,000 free AI-generated music tracks for online listening, and the other involves custom music services for a fee Additionally, responding to the promotional needs of the record industry and artists, it also charges for advertisement playbacks Another revenue model involves renting music players to users, charging an annual rental fee BGMRADIO公播平台與其他公播平台之比較 Zeng Zhizhong states, "Music knows no borders good music doesn't distinguish between being created by humans or AI" With current AI algorithms and related technology being quite mature, using AI to produce music is not a difficult task The key is identifying market pain points for business opportunities Anpu's market spans Taiwan, Japan, Korea, Singapore, and it aims to continue expanding into China's largest market Having founded startups for 20 years in mainland China, Zeng Zhizhong's primary reason for starting a business back home is Taiwan's rich talent pool, especially the interdisciplinary talents Unlike typical AI or music companies, Anpu requires a large number of amphibious talents capable of both programming and music The company comprises two main departments the RampD department, mostly formed from graduates from NTHU and NCTU in electrical engineering, electronic engineering, and applied music, and the music production department, where after quick AI algorithmic composition in the RampD department, highly musically educated producers refine these AI compositions into high-quality music experiences 安譜團隊大多是科技與音樂兼具的跨域人才「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

A stamp-sized flexible temperature patch became an essential tool for fever monitoring amid the ongoing COVID-19 pandemic, with orders soaring to over 500,000 units in just two months, proving useful for home isolation and medical quarantine iWEECARE, established just five years ago, has created the world's smallest connected smart thermometer, Temp Pal, which offers remote continuous temperature monitoring and alerts iWEECARE has integrated a temperature sensor into a 3-gram, stamp-sized flexible patch, which is stuck under the arm's skin and can continuously monitor temperature between 36 to 48 hours without interruption, transferring temperature data via Bluetooth to a mobile app and cloud backend, displaying real-time temperature changes and setting fever alerts In this epidemic response effort, the rejuvenated hospital, equipped with negative pressure isolation wards, installed a temperature monitoring system Unlike the common forehead or infrared temperature monitoring methods, the hospital uses Temp Pal smart temperature patches developed by iWEECARE, which are only stamp-sized 33 cm, stuck under the patient's skin under the arm, combined with a low-power Bluetooth receiver, allowing continuous monitoring of the patient's temperature, recording every 5 minutes If a case of fever is detected, the system will notify medical staff proactively, enabling them to accurately monitor the patient's condition and handle it promptly, thereby enhancing patient safety care 像郵票一樣大小的體溫貼片 醫院設置即時體溫貼片監控系統 節省超過6萬件防護衣耗損 振興醫院表示，引進監控體溫的即時體溫貼片監控系統，對隔離患者進行24小時體溫監測，醫護人員可以在不進入隔離病房的前提下，事先擷取到病患重要的生理數據，在提昇照護品質同時，醫護人員進出隔離病房的頻率可以減半，1個月即可節省約6萬5千多件防護衣的損耗。 The Temp Pal smart thermometer is not just small and capable of continuous temperature monitoring its biggest feature is the ability to 'actively and continuously monitor multiple people's temperatures,' ideal for group quarantine and mass isolation in hospitals, achieving efficient and thorough results Kang Ying-Cen, the marketing director of iWEECARE, mentioned that initially, the 'Temp Pal wearable smart thermometer' was mainly used in maternity centers or by new parents to continuously measure a baby's temperature, monitoring the temperature trends of newborns and early prevention of potential harm Unlike standard thermometers that measure at singular moments and require manual adjustment every 4-6 hours, the smart thermometer, with its personal and soft design, does not cause any discomfort to the baby and monitors temperature continuously If the temperature deviates from normal values, the mobile app will also sound an alarm to prevent scenarios where the fever could lead to grave consequences 將體溫貼片貼於腋下，36小時監控寶寶的體溫 精準掌握基礎體溫 備孕效果佳 由於連網智慧體溫計蒐集了使用者的體溫趨勢的數據，未來透過AI演算法的導入，對於婦女的排卵期有精準的掌握，一般而言，適孕婦女的「基礎體溫」是指在較長時間的睡眠（約6～8小時）後，尚未進行任何活動前（含起身下床）所測得的體溫，且每天需於相同的時間進行，此為人在一天當中最低的體溫點。在健康的身體狀態之下，溫度曲線會隨著週期間的排卵而產生升高溫的現象，也就是說，即基礎體溫在排卵日當天會升溫，想要懷孕的女性可以藉此作為受孕及避孕的基礎。 現階段除了台灣外，連網智慧體溫計也銷售至東南亞、新加坡、加拿大及歐洲等地區，其中，位於泰國，屬東南亞最大的私人醫院集團在2019年底也開始採用 Temp Pal Group System（添寶群體監測體溫系統），該醫院目前在泰國各城市有 40 家分院。以往體溫正常者平均每 4 小時護理人員要量測病患體溫一次，體溫異常者則每 1 小時需量測一次，而採用 Temp Pal 群體監測體溫系統後，智能體溫貼片每次充電可使用長達 36 小時，每日最高可減少 23 次的體溫量測頻次，估計可節省每日每單位護理人員 25 小時以上的時間。 體溫貼片以藍芽傳輸，透過手機APP傳輸溫度變化 愛微科兩位創辦人為有電池設計專長的曾軍皓及擅長韌體開發的張和逸，一開始對於穿戴式智慧體溫貼片在台灣屬於第二類醫療器材的規定認知有誤，第二類醫材要上市，不光是要取得政府核發許可證，還得通過臨床前測試，而在歐美要通過認證，至少要花一年的時間，日本市場則需要投入兩到三年通過認證，難度更高。未來1-3年內，愛微科仍將持續研發新型的態體溫貼片，以提供更多元服務。 愛微科兩位創辦人「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

What is the next consumer electronics product that will spark a market frenzy after smartphones and tablets Recently on a crowdfunding platform, a 'smart projector' raised more than NT10 million in just half a month, becoming a hot market focus Formed just over a year ago, Drip-Drop Technology's 'smart touch ultra-short-throw projector' is smaller than a tablet and weighs less than one kilogram It uses ultra-short-throw optical projection to project an 80-inch image from just 50 cm away from the wall Most importantly, the projector features virtual finger touch control This means that inside the lens, an AI algorithm is utilized, allowing the camera to actively learn to recognize fingers and the environment through machine learning When the image is projected onto a table or wall, no remote control is needed operations can be directly controlled by touching with fingers The Drip-Drop Technology team currently has 4 members, focusing on research and development The founders have over 10 years of experience in projector development and mass production, including co-founders Wang Shouzheng, You Xianglin, and Chen Zhengfang, who participated in the development of the first laser TV ultra-short-throw laser projector launched by Hisense Group in China In collaboration with Lin Zuoxian, a part-time lecturer at Ming Chuan University who also joined the team in 2019 as the general manager, handling IP, crowdfunding, and business operations management, the rest of the team concentrates on developing interactive projection technology and products to build the smart touch projector General Manager of Drip-Drop Technology, Lin Zuoxian Smart Touch Projector, a Key Player in the Future Smart Home At the end of 2018, Wang Shouzheng met Gao Yuan, a professor in the Marketing and Distribution Management Department of the Business and Management College at Gao Yuan University of Science and Technology, specializing in artificial intelligence, multimedia interaction Unity, and smart interaction devices APP They hit it off immediately, with Gao Yuan not only becoming the director of RampD but also becoming a shareholder of Drip-Drop Technology last year Wang Shouzheng explained that unlike traditional projectors, the smart touch projector can not only be controlled by touching the screen with fingers but also by hand gestures, such as swiping left or right to adjust the volume or the screen brightness It can also be used to control household appliances in the future Despite the technical challenges of projecting on tabletops and controlling by touch, continuous optimization of recognition technology through AI algorithms has been crucial Within the first half-month of its crowdfunding campaign in February 2020, it raised over ten million dollars, with an expected delivery of 400 units Wang Shouzheng believes the greatest challenge in developing the projector was dealing with AI algorithms The projection might encounter different materials such as glass, wood, or plastic, compounded by lights, angles, background, and interference such as coffee cups, creating varying parameters The projector sensors must automatically adjust to the surrounding environment to avoid false touches The projector lens processes 200 finger position frames per minute, and through continuous machine learning, the recognition accuracy has significantly increased Comparison between Smart Touch Projector and Traditional Projector AI algorithms significantly enhance precision, sensitivity, and recognition in finger touch control The Smart Touch Projector will be used in education, entertainment, and business sectors Wang Shouzheng mentioned that originally, the smart touch projector was designed for home entertainment, such as providing a larger interactive projection surface to replace traditional smartphones and tablets for family interactions However, its potential for multiple uses was soon discovered, like in smart kitchens where chefs can interact directly with the projection, avoiding issues when hands are dirty during cooking It also provides ease of use for the elderly because of larger controls and reducing eye strain Playing mobile games with a Smart Touch Projector offers a unique experience In business settings, it can be used to establish interactive projection-based ordering systems, allowing customers to directly interact and order, while businesses can integrate other digital media content to provide diverse services This includes real estate agents and insurance agents who need to attract business outside the office, as they can achieve better results through the smart touch projector Low blue light and diffuse reflection are among the technologies that help protect eye health, making the smart touch projector a significant upgrade from tablets Drip-Drop aims to secure four patents by the end of 2020 and plans to expand to mainland China within 1-2 years through crowdfunding, allowing more industries to choose smarter options Drip-Drop Technology Team「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

Amid the global rampage of the novel coronavirus, countries have implemented lockdown policies, leading to emerging food shortages as many countries halt exports By integrating technology with agriculture, productivity can be increased while also addressing issues like soil acidification and labor shortages in farming Dr Chen Wenliang, an associate professor at the College of Biotechnology of National Chiao Tung University, along with students, established Agritech Translation Technology They integrated biotechnology, Internet of Things, big data analysis, and artificial intelligence to develop the 'AgriTalk Management Platform', a pesticide-free agricultural pest and fertilizer monitoring system Utilizing big data analysis and AI learning from environmental data collected by various sensors, the platform can precisely adjust and control six major production factors disease, pests, soil fertility, moisturehumidity, temperature, and light CEO of Agritech Translation Technology Chen Wenliang 'Growing up, my father planted peanuts, watermelons, and sweet potatoes in Yunlin, which gave me a special affection for agriculture and a desire to contribute what I've learned' Born into a farming family in Yunlin, Chen Wenliang utilized his expertise in biotechnology, along with the AI team led by Lin Yiping, Vice President and Professor of Computer Science at National Chiao Tung University They received NT68 million over two years from the Ministry of Science and Technology's Innovative Technology Agriculture System project, setting a benchmark for 'professor entrepreneurship' Two Major Rural Dilemmas - Soil Acidification and Labor Shortage in Farming Chen Wenliang stated that the current rural dilemmas include severe problems of soil acidification and labor shortage on farms Long-term pesticide abuse has led to soil acidification, reducing soil fertility and decreasing crop values Therefore, prior to the company's establishment, his research team isolated and developed a biological insecticidal agent from over 5,000 types of spider neurotoxic proteins, which can kill specific pests but is harmless to humans and bees After the sensors collect all data on soil, it is combined with an environmental control system Once the environment reaches specific parameters, various actions such as watering, fertilizing, and lighting are initiated to maintain optimal growing conditions Additionally, this data is uploaded to the cloud, stored as big data, and analyzed by the AgriTalk platform's AI algorithm to predict future pest outbreaks and adjust the cultivation environment accordingly, thus preventing pest issues from the source Agricultural Control Module Controls Various Machines Agritech Translation Technology selected turmeric as a crop because it is entirely edible, has few pests, a short growth period, and high economic value Currently, Agritech Translation Technology has four demonstration sites in Taiwan located at altitudes of 1,200 meters in Wufeng, Nanzhuang, Baoshan, and areas around Qionglin and Zhubei They use sensors to collect data and AI to automatically adjust soil nitrogen, phosphorus, potassium content, control moisture, and soil pH Before introducing AI, the maximum turmeric plant height was 140cm After introducing the AI management system, plants could grow to 158cm in a week, and up to 170cm overall, achieving a curcumin concentration of up to 55000mg100g 4-5 times higher than usual From Seeding to Producing High-Quality Final Crops AgriTalk Management Platform Prioritizes High Economic Value Crops for Introduction Following the successful introduction of turmeric, Agritech Translation Technology's next phase will introduce the cultivation of dan-shen using the AgriTalk Management Platform, continuing to prioritize the cultivation of high economic value crops in the future Chen Wenliang indicated that he once saw an 80-year-old farmer still working bent over in the fields in Nanzhuang, highlighting the severe labor shortage Also, traditional farming knowledge is gradually being lost Agritech Translation Technology aims to attract young farmers back to agriculture and preserve the older generation’s planting expertise through an AI algorithm, establishing an expert system Generally, with a single master's guidance, all data is captured, allowing even novice farmers to quickly cultivate crops with the aid of the expert system Agritech Translation Technology adopts a one-stop service approach for farmers, from sensor integration to monitoring and management platform implementation, even buying the produce at double the price, to attract enterprises and agricultural product channels to invest, creating a guaranteed contract farming business model, thereby finding a sustainable and profitable model for the entire rural area and Taiwanese agriculture This will attract more young people to return to rural areas, and solve the labor shortage problem Besides its own sites, the company adopts a flexible partnership model to promote its products, offering complete solutions, using single products, or even just AI services With complete solutions and significant results, Agritech Translation Technology's system not only became a focal point of Taiwanese agriculture but also has partnerships in Japan, the Philippines, the USA, and even Armenia in West Asia, introducing the system to crops like bananas, grapes, and olives Chen Wenliang noted that the AgriTalk Management Platform elevates agriculture from semi-automated or manual processes to automated and AI-enhanced, creating a win-win situation for both the economy and agricultural environmental protection「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

Taiwan is known as the 'Kingdom of Shrimp Farming' However, due to drastic weather changes and the inability to pass on farming experience, the risks for farmers are increasing Through AIoT Artificial Intelligence combined with IoT, Kuanwei Technology has started a trend in smart aquaculture, innovating the traditional aquaculture value According to the statistics from the Council of Agriculture, the total fishery production value in Taiwan is around NT100 billion, of which NT60 billion is contributed by offshore fisheries through exports, and NT40 billion is from coastal and aquaculture fisheries The aquaculture industry, which spans 40,000 hectares, has been a strong support in Taiwan's progress from the 'Kingdom of Eels', 'Kingdom of Shrimp', 'Kingdom of Ornamental Fish' to the 'Kingdom of Tilapia' However, affected by drastic changes in weather, the winters of 2018 and 2019 were notably warm, averaging the highest temperatures in 72 years, disrupting the breeding cycle of fisheries and severely impacting production AI Fish Farming Reduces Costs by 30 and Increases Production Capacity by 30 Although fishermen also 'depend on the weather for food', they can minimize risks with the aid of artificial intelligence Located in Hsinchu, Kuanwei Technology focuses on the development of IoT systems and AI algorithms for the aquaculture industry, developing the 'Water Jewel Smart Aquaculture Monitoring System' and the 'Smart Device Control System' These assist operators in obtaining real-time data such as temperature, dissolved oxygen DO, pH value, redox potential ORP, and salinity With the smart device control system installed, users can start water wheels and set automatic feeding depending on dissolved oxygen in the water Fishers only need to use a mobile app to keep track at any time, allowing for early prevention and reducing losses By adopting technology in aquaculture, costs are effectively reduced, creating endless business opportunities Fishermen can accurately monitor and control the water quality and growth process of aquatic products, hence providing safer food to consumers Kuanwei Technology's CEO, Tsai Cheng-hsun, indicated that traditional fishing methods involve measuring water quality twice daily and feeding based on experience, which not only is time-consuming but could also negatively affect water quality due to environments' drastic changes or overfeeding The 'Water Jewel Smart Aquaculture Monitoring System' continuously collects data every five minutes, gathering up to 1,000 data points per day if any abnormality occurs, such as overfeeding causing turbid water pollution, or abnormal water temperatures, it communicates these problems to the fishers via the app, allowing immediate remediation AI Monitors Water Quality Changes Kuanwei Technology's CEO Tsai Cheng-hsun Tsai Cheng-hsun stated that by monitoring data and keeping it within normal ranges, they can avoid unnecessary water stirring or feeding, thus maintaining water quality stability and reducing costs Typically, half of the farm costs are feed and electricity accounts for 15-20 According to research by Dr Luo Yong-zhong from the National Cheng Kung University 'Microalgae Biotech and Engineering Lab', after implementing the 'Water Jewel Smart Aquaculture Monitoring System', electricity costs can be reduced by nearly 60, and with reduced feed input, the overall farming costs can be reduced by 30 300 Pools Across Taiwan Adopting Water Jewel Smart Aquaculture Monitoring System A study by the Ocean University also pointed out that technological equipment, along with basic infrastructure such as waste pipes, should increase the aquaculture output by 30 For fishers, smart aquaculture truly helps in increasing profits significantly Aquaculture expert Huang Guo-liang in Tainan's Jiangjun area is the third generation cultivating milkfish, utilizing ecological balance and friendly farming methods through smart monitoring systems for problem detection and optimizes productivity while reducing costs Tsai Cheng-hsun stated that the Water Jewel leverages solar power, reports fish pond water data every 5 minutes, and for the Giant Grouper, for example, which needs at least three years to grow and weigh about 20 kg to be marketable With temperature alerts set at 16 degrees Celsius, if a cold snap occurs and temperatures drop below 10 degrees Celsius, Giant Grouper could freeze to death By monitoring such instances, preventive actions can reduce losses Kuanwei Technology currently has introduced its system to 300 farming pools across Taiwan, including in Hsinchu, Fangliao, Hualien, and Taitung, employing Water Jewel's remote water quality and environmental monitoring, smart energy-saving, automatic feeding, and automated production traceability features This allows every farmer to record their farming data and process according to their own habits They can choose to manually control or use AI assistance for real-time alerts and also monitor sites through remote video links to make the Water Jewel aquatic farming IoT system more accessible Water Quality Monitoring Equipment Fishermen, reliant on the weather, can now monitor aquaculture pond water quality through the AI monitoring system Tsai Cheng-hsun, currently the first term manager of the Taiwan Artificial Intelligence School Hsinchu branch and the vice president of the Taiwan Artificial Intelligence School Alumni Association, is deeply committed to AI research In the future, Kuanwei Technology will continue to optimize data, proposing more applications, and has received recognition from Intel for IoT solutions maturity in Taiwan By utilizing cloud, big data IoT, and AI technologies and equipment with scientific data management, along with continuous data logging and AI algorithms, it can quickly uncover potential risks, effectively preventing and reducing aquaculture losses At the Kuanwei Technology exhibition, vice presidential candidate Lai Ching-te second from the left also attended to show support「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」