In the era of AI, whether it's smart manufacturing or smart retail industry applications, the most important first step is data collection, especially on factory machines where thousands of information streams exist It's crucial to define what information is useful and what constitutes useless digital junk from the onset If there is simple, lightweight, and low-cost software, it could help enterprises collect data from machines and analyze and predict to achieve traditional enterprises' digital transformation goals AI Commercialization Insufficient, Main Consideration for Enterprises is Cost-Benefit Located in Xindian, New Taipei City, the headquarters of Beier Electronics Asia Pacific is a technology company committed to industrial automation and high-standard data communication Its main products include Industrial IoT Gateways devices linking two different network systems, transmitting data to other networks with similar functionalities but different structures, War Room Visualization software, HMI, with core technologies being controller communication drivers and visualization software Lee Li-Wei, the deputy director of product management and support at Beier Electronics, who has worked at Advantech and Xinchang Company, and familiar with Industry 40 operations, stated that when assessing whether to introduce AI, the most important consideration is cost and benefit From his observations over the years, the level of AI commercialization is still very insufficient because AI is often customized, not mass-reproducible, hence naturally expensive Only if AI moves to vertical applications and standardizes products, like using AOI for defect inspection or predictive diagnostics for motors or tools, can such AI possibly be commercialized and cost-effective X2 pro提供各種高性能工業用人機介面 At this stage, digital transformation challenges faced by factories include 1 Data collection difficulties 2 Factory equipment needing updates, which consumes time 3 High costs For large enterprises, sufficient funds and human resources allow them to introduce AI and undergo digital transformation projects As for SMEs, limited by resources, the key factor is cost-benefit, determining whether to introduce AI Existing software that assists in data collection and provides decision-making visualization software may meet current practical needs Once business owners see tangible benefits, they can further consider the need and incentives for adopting AI As a professional manufacturer of human-machine interfaces in Europe and America, Beier Electronics provides visualization software that fetches controller data on production lines and machine tools, as well as IT data integration services Using AI technology optimized for productivity and quality management can solve data fetching and integration issues For example, the factory war room displays the day's factory data and even real-time financial reports on a large screen wall Factory decision-makers can then use the integrated information and war analysis converted by visualization software to make decisions about production, marketing, inventory management, and procurement preparations Three major advantages of the war room low cost, easy maintenance, and mass reproducibility Compared to a typical factory war room, Beier Electronics' war room service has three major advantages it offers a low-cost, packaged visualization software it doesn't depend on engineers for maintenance and the war room can be easily commercialized and mass produced, which also accommodates future expansions from automation to IoT devices Lee further explains that AI primarily retrieves data for assessment, unlike automation, which demands real-time reaction It can tolerate a slower data fetching speed, still within milliseconds Human-machine communication doesn't need a special interface, so it can be decoupled from existing controllers without program changes, directly interfacing with existing hardware on the production line to fetch data, using existing software for data reading and analysis, aiding in decision management, and carrying out factory digitization upgrades As for whether Beier Electronics will introduce AI algorithm technology to provide users not only with data collection but also analysis and prediction services Lee stated that Beier Electronics considers three aspects Firstly, data collection is absolutely crucial when introducing AI At the same time, it must be done without increasing costs or changing site equipment for high customer acceptance Secondly, what problems AI aims to solve must be clearly defined Beier Electronics' clientele includes PLC programmable logic controller vendors, including Delta Electronics, Yonghong, Alliance Automation, Shilin Electric, and international giants such as Siemens, Rock weld, and MITSUBISHI However, the ultimate customers are PLC users, covering industries beyond semiconductors, including petrochemicals, 3C manufacturing, automotive manufacturing, power generation, and risk control The domain knowledge covered is extensive Given limited resources, whether to extend services to AI is still under consideration However, if professional specialization can be implemented, Beier Electronics plans to arrange an industrial ecosystem, introducing strategic partners to assist customers toward AIoT goals Deputy Director Lee Li-Wei, Product Management and Support Department at Beier Electronics「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

A tiny chip capable of driving AI algorithm speeds by nearly a hundredfold, Fansi Data's team is dedicated to software and hardware integration, providing industries including finance, smart healthcare, and smart manufacturing with a cost-effective, high-efficiency way of introducing AI and rapidly undergoing digital transformation In recent years, artificial intelligence has been highly prominent however, practical applications have been limited by high costs The enhancement of 'computing power' is crucial for breaking through the bottlenecks in AI applications Fansi Data's customized chip design and solutions can increase processing performance and effectively reduce costs, making AI applications in finance, healthcare, and manufacturing easy and feasible The company's core service is the high-performance hardware acceleration platform FPGA Fansi Data was founded in October 2018 by a founding team from National Tsing Hua University, National Chiao Tung University, and National Taipei University The company currently has 11 employees, including the chip design director Liu Wenkai from the IC design company Huirong Technology, who leads a 5-person IC design team They spent over a year developing the high-performance hardware acceleration platform FPGA, which became the company's core service Fansi Data integrates software and hardware to develop a high-performance hardware acceleration platform FPGA 'To bring AI to practical implementation, the challenges are cost and real processing situations Purchasing a standard set of NIDIA GPUs is expensive If we can adjust the hardware through customization, producing a setup tailored for use, the costs can be significantly reduced' Said Liao Yanchin, General Manager of Fansi Data, who additionally pointed out that most AI startups currently only have software engineers and lack hardware engineers Fansi Data excels in data handling and softwarehardware integration, has an excellent team, and can efficiently solve data issues while developing softwarehardware solutions tailored to customer needs Financial markets are notoriously fickle, as evidenced by the recent COVID-19 pandemic, which triggered a global stock market crash and was reinforced by program trading, leading to the unprecedented implementation of four trading halts in US stock exchanges within a decade This has significantly raised investors' risk awareness Zheng Zongyi, co-founder of Fansi Data, experienced in financial trading, points out that in financial markets such as stocks, futures, and warrants, 'speed' is often the key to victory Typically, the traditional stock trading process involves financial trading data flowing from the network to the mainframe, processed through combination software, measured in milliseconds ms, 10-3 seconds, with an average transaction completed in 20 ms System transaction processing speed, however, is at the nanosecond level ns, 10-9 seconds, and through the high-performance hardware acceleration platform FPGA, each financial matching transaction can be completed in microseconds, a significant difference that can lead to billions in trading gains or losses, and is a major competitive edge for proprietary traders Financial services in the domain of securities firms' proprietary sections, new types of financial product trading departments, and high-frequency traders or major retail traders In the securities market, market volatility is the result of a tremendous amount of data If the system operates at nanosecond speed, allowing you to see transaction information instantaneously, ahead by 01 seconds, you can make trading decisions before others even see the market data Service areas focus on financial technology and smart manufacturing The risk control systems of bank credit cards can also utilize AI integration acceleration, similar to regulatory technology domains Establishing an AI model can effectively identify risky credit card transactions and provide responses in a very short time, enhancing the security and smoothness of online transactions In the AI credit card risk control system, AI acceleration is also used through software integration Transactions are prevalent, and fraud is common, similar to regulatory technology domains By establishing an AI model, risky credit card transactions can be effectively identified, and responses given in a very short time, enhancing the security and smoothness of online transactions This includes financial transactions and credit card risk identification, all through chip-based transaction data analysis and risk management system direct acceleration calculations Financial transaction information acceleration solution Currently, many financial companies have their own IT departments, including data scientists, big data analysts, and AI algorithm engineers What is Fansi Data's advantage in the financial sector Zheng Zongyi points out that the IT departments in the financial industry are more 'users' of IT, not 'developers' of IT Moreover, understanding IC design involves high costs, and the financial industry does not need to maintain their IC design team The specialization is very clear, as Fansi simply develops models for the financial industry to adopt Considering personal privacy and data security, financial data is sensitive and often not easily accessible Fansi Data, by joining the financial technology innovation park FinTechSpace and with the assistance of the Institute for Information Industry, applies for the real-time transaction data and corporate annual financial statements, historical trading data provided by the digital sandbox, using it to group data, analyze, model, backtest, and propose AI risk warnings and other solutions for abnormal transactions and risk management Besides financial technology, Fansi Data also focuses on AI applications in smart manufacturing, such as developing smart image meter reading through image recognition methods, which can help businesses reduce equipment replacement costs and achieve higher accuracy In the process of customized chip design, data analysis, and softwarehardware integration, Fansi Data encounters difficulties in data and talent acquisition At this stage, through interfacing with the digital sandbox and utilizing resources provided by the financial technology innovation park, AI models are built regarding talent, a lean core team is established, continuously accumulating experience and building a robust entrepreneurial culture to face the ever-growing market demands From left to right Co-founder Zheng Zongyi, General Manager Liao Yanchin, and Chip Design Director Liu Wenkai「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」