Factory machines operate 24 hours a day and will cause heavy losses if they are shut down due to failure If the usage status can be monitored by machine and abnormalities immediately determined, it will help the industry maintain product yields, machine stability, reduce maintenance costs, and shorten maintenance time At present, mainstream AI mostly uses big data gathered in advance or already on hand for training and characterization However, despite the a wide variety of machinery and equipment in factories and the marketrsquos emphasis on predictive maintenance and monitoring in recent years, the amount of data accumulated is very limited How can we quickly meet the needs of factories Provides immediate diagnosis and shortens the troubleshooting process Good Tech Instruments has accumulated a huge database and can quickly help manufacturers protect machinery, equipment, and product quality Wen-Tze Hsu, founder and technical manager of Good Tech Instruments, said that the main feature of machine learning AI monitoring system products is that it quickly learns from the experience of practitioners in the original field, and then uses pre-built mathematical models to classify and manage human experience based on physical and mathematical calculations, accumulating a large amount of data through repetitive production actions At the same time, the previously learned experience data is overlapped with data accumulated over a long period of time and deviation conditions for optimization, in order to achieve the goal of optimizing the monitoring model The time series charts generated by the system are subsequently used to define the predictive maintenance time for various industries and equipment The implementation of instant diagnosis can increase production by 40 working days per year Good Tech Instruments has accumulated a huge database and can quickly help manufacturers protect machinery, equipment, and product quality Wen-Tze Hsu also pointed out that factories have a lot of data, but collecting data does not mean that the data will be useful, and collecting data for deep learning will not necessarily solve the problem of predictive monitoring Good Tech Instrument's monitoring program uses existing or learned rules for monitoring when it is first installed, in order to protect machinery and product quality In the monitoring process, the underlying algorithm will continue to collect and classify data Users can perform labeling actions in the process or use the collected and classified data groups for deep learning AI technology is mainly applied in equipment monitoring and predictive maintenance processes The VMSreg-ML Intelligent Machine Learning Monitoring System can achieve three benefits IAvoid business losses due to production line shutdowns caused by unexpected damage to equipment and molds By preventing unexpected shutdowns and time waiting for materials, production can be increased by 40 working days per year, and quality assurance manpower can be reduced by one third IIOnline monitoring of production processes serves as a defense mechanism against defective products, which can reduce customer complaints and rejected goods IIIMonitor the health status of machinery and equipment, avoid delayed maintenance or excessive maintenance, improve management of industrial production risks, and reduce waste of operating costs The target market of Good Tech Instruments is monitoring applications for stamping, such as the health of motors, crankshafts, punch rods, and springs It can also be applied to smartphone casings, automobile manufacturing body parts, 5G equipment casings, and metal fasteners, and its customer base is mainly in the semiconductor industry Wen-Tze Hsu also said that AI has been the most important trend in the manufacturing industry in recent years, and equipment monitoring is now regarded by most companies as the first step in implementing smart manufacturing systems

Facial recognition software applying deep learning and edge computing model compression technologies significantly reduces costs compared to cloud computing and has increased efficiency by more than ten times The technology has been introduced to law enforcement agencies for suspect identification and will be used in more access control systems, membership systems, and provide diverse AI services in the futureBy integrating edge computing, facial recognition time is saved by more than ten timesAs end-user demand for AI increases, most current AI applications involve sending files to the cloud, where they are processed and analyzed by high-end processors like CPUs and GPUs Future devices such as tablets, smartphones, surveillance cameras, and smart doorbells will feature AI applications, addressing issues of insufficient computing resources and decreased performance with edge computing and efficient deep learning algorithmsApex Intelligence developed AiBo facial recognition software applying deep learning and edge computing model compression technology that allows IPCams to automatically recognize every smile of children aged 0-12 through local device computation, emotion detection accuracy exceeds 98, significantly saving more than ten times the photography and recognition time compared to cloud services Photos can also be uploaded to the cloud to create smart albums using facial classification technology, allowing users to share albums with friends and familyUsing edge computing reduces expenditures by 4 million annuallyWith edge computing, there's no need to spend time sending all images back to the cloud for recognition and classification This saves more storage space and costs, and can expand services to remote areas or locations with unstable internet This technology has already been partnered with major domestic manufacturers, significantly reducing the average annual cloud storage, computer processing, and service costs by 4 million The application also utilizes facial recognition for real authentication, adding an extra layer of protection for online transactions, while physical retail stores can use security system image analysis to quickly identify customers, providing more precise service qualityApex Intelligence's product technology can perform facial detection, identification, classification, object detection, and gaze detection The main focus of its AI deep learning technology is on image processing, with existing products including facial unlock and smart photo albums For example, in collaboration with UMC, it is determined whether personnel wearing safety gear enter within safety cones This technology can be further applied in homes, family restaurants, kindergartens, and more, enhancing applications in access control systems and membership systems to provide diverse AI servicesZhongwei Chen, founder and CEO of Apex Intelligence, also pointed out that images occupy a significant proportion in the data types of the Internet of Things AI can extend the value of images, inspiring different creativity and generating enormous business opportunities in the future「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

Hangte developed AI Cam, offering smart innovative services The development of monitoring products has undergone breakthrough development due to the advent of artificial intelligence technology traditional network cameras IP Cam have been upgraded to AI network cameras with smart image automatic analysis and response capabilities AI Cam not only meets the high-resolution demands of various platforms with image quality but also continuously expands its capabilities based on its smart application properties, thereby creating innovative services in smart imaging applications that keep evolving and being suitably applied in various environments and scenarios For example, in the use of human detection applications, this smart monitoring feature can separately identify each person in the surveillance video and delineate a specific range as a basis for monitoring decisions, conducting systematic analysis and management users can calculate the dwell time, count people traffic, and also issue immediate alerts when a designated person enters the monitored range as shown in the diagram below Smart monitoring features can individually categorize each person in the surveillance video In the aging society with a shortage of manpower, smart long-term care efficiently enhances care quality According to statistics from the Ministry of Interior, Taiwan has entered the 'aging society' structure Since 1993, the population of elderly people aged 65 and above has steadily increased from 1,491,000 to 3,312,000 by the end of March 2018 according to estimates by the National Development Council, the elderly population is expected to exceed 20 by 2026, making Taiwan parallel with Japan, South Korea, Singapore, and some European countries as a 'super-aged society' In other words, in the future, Taiwan's society may become a structure where one in every five people is elderly, significantly increasing the need for long-term care facilities and retirement centers Given the trend toward an aging population, the manpower resources for caring for the elderly will inevitably diminish over time The solution to the aforementioned shortage of manpower for long-term care needs is to optimize the operation of long-term care institutions using artificial intelligence technology, particularly by utilizing AI network cameras with smart image auto-analysis and instant response capabilities, combined with the Internet of Things IoT automatic connection features to promptly identify problems and handle them effectively, embodying a high-efficiency smart service application In the smart operation system of long-term care institutions, we can set up a people counting function to calculate the daily traffic, using this data as a reference for observing the dynamics of personnel entering and exiting a designated detection area, useful for calculating attendance or foreign visitor flow, and adjusting door threshold times or work schedules accordingly additionally, the electronic fence feature can define and secure specific areas, immediately alerting the management if an unauthorized visitor breaches the area, coupled with fall detection to set up designated areas for the care recipients prone to falls, immediately notifying the caregiver if an incident occurs within the detection range as shown in the diagram below Using AI surveillance cameras in long-term care facilities reduces the workload and enhances care quality Edge computing smart imaging, cloud IoT innovative services The application of artificial intelligence combined with the Internet of Things in monitoring scenarios is not limited to potential suspects or dangerous individuals in retirement and long-term care environments, AI surveillance can also enhance monitoring and integrated management of resources Hangte Electronics, leveraging over thirty years of industry experience and RampD capability in monitoring imaging technology, successfully combines Internet of Things technology IoT and Artificial Intelligence AI, not only making good use of cloud computing to reduce installation and management costs of surveillance environments but also greatly enhancing the overall monitoring effectiveness of security systems by utilizing edge computing to provide image preprocessing capabilities and coupling it with AI smart image analysis technology for various image recognition and instant analysis of monitored subjects' behavior, automatically linking response mechanisms to correspond to triggering events, fully dedicated to crafting innovative service solutions for smart surveillance 20 for clients Fully dedicated to crafting innovative service solutions for smart surveillance 20 for clients 「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

When consumers don't know what to buy or are specifically interested in certain types of products, their first thought might be to shop online Why Because it's fast, convenient, offers 24-hour delivery, and they don't have a preference for specific brands, allowing them to find products from various sellers on a single platform While browsing online, you've surely seen product recommendation features like 'You may also like' or 'Others also viewed' These not only help you find the products you need more quickly but also allow for fast comparison of similar items in terms of specs and price It's a very useful feature for consumers For merchants, this data helps understand customers' habits and preferences 'Recommendation systems' basically ineffective Amazon and the globally known streaming platform Netflix see significant revenue boosts from their recommendation systems Coupled with articles teaching how to increase conversion rates, e-commerce business owners might have quietly thought, 'I've tried using similar recommendation systems, but they haven't shown significant results' Perhaps, aside from focusing on targeted marketing, we should consider each consumer as an individual with unique preferences, behaviors, and needs, creating a personalized shopping experience just for them Traditional methods, like recommending more fans after one buys a fan, no longer meet the current users' needs Modern networks use AI algorithms to dynamically calculate user behavior and update website merchandise, promptly adjusting the recommendations on sites and e-commerce platforms, such as recommended content and the content viewed, to better align with what users are seeking Why not analyze consumer profiles, allowing customers to have their 'personalized website' Data shows that e-commerce worldwide spends a lot on advertising to drive traffic, yet the actual conversion rates average only 2 - 3 Why is this Rosettaai has learned from over five years of e-commerce experience that two main factors affect customer conversion and retention Inability to grasp customer purchase preferences, motivations, and situations, including personal factors E-commerce often involves wearing many hats with insufficient resources and budget to adopt innovative technology Thus, Rosettaai has always focused on two critical business factors 'Customer Acquisition' and 'Customer Retention', emphasizing integration of all touchpoints throughout the consumer's online and offline journey, rather than just being an online recommendation tool Its personalized recommendation system suggests products that best suit each customer's taste, analyzing preferences to help brands more accurately understand their consumer profiles and recommend styles to potential customers Rosettaai also designs recommendation systems to suit different pages and KPI stages based on consumer shopping processes Users can select scenarios based on their website's needs the system also provides real-time feedback and automated engines Now, with over 30 unified API-ready free modules and 14 basic scenario combinations, your e-commerce site will no longer be just another site With AI and deep learning, the concept of homepage will be redefined, tailoring product recommendations and homepage design to meet individual consumer demands From another angle, creating a precision recommendation service for e-commerce, allowing the use of a personalized recommendation system, not only prevents customer churn and increases average order value but also enhances turnover and provides a novel shopping experience for modern consumers, resulting in a mutually beneficial cycle 「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

The development of AI voice assistants has become increasingly mature, but there is a lack of applications specifically for the hotel industry Therefore, the AI voice assistant developed by Aiello can complete room service, equipment introduction, check-out, and stay extension, making it a considerate AI butler The introduction of AI voice assistants into the hotel industry will help improve the experience of guests Google Assistant, Apple's Siri, and Amazon's Alexa are known as the world's three major voice assistants The applications of voice assistants are becoming growingly diverse, but they are mostly used in handheld devices, personal applications and home applications Some hotel operators are optimistic about demand in the hotel industry, and have introduced AI voice assistants into hotel industry applications, leading to the rise of smart hotels Aiello was founded in October 2018 and launched the Aiello Voice Assistant that supports Chinese and English The Aiello butler, which looks like an alarm clock, can assist with room service, equipment introduction, check-out, and stay extension after receiving voice commands from hotel guests Hotel voice assistant For example, if a hotel guest needs drinking water or newspapers, he only needs to say to the Aiello Voice Assistant "Please send a bottle of mineral water to my room" or "Please send a newspaper to my room" After the Aiello butler receives the guest's voice command, the customer service manager will directly send someone to deliver mineral water or newspaper This prevents poor service or even customer complaints because counter staff missed a call In addition to receiving instructions from guests, Aiello Voice Assistant can also combine the functions of a phone and an alarm clock, and has a built-in Bluetooth speaker, so that it can automatically play online streaming music with a single command, providing guests with a better service experience Deepening service scenarios and expanding practical applications Aiello Voice Assistant uses natural language processing NLP and semantic analysis to recognize customers' voice commands and complete multiple room services, reducing unnecessary communication time and potential human error Among them, semantic analysis is used to replace the rule-based model and the exhaustive method of linguistics It can understand at least three questions at a time, which is more in line with people's conversation habits and more adaptable to different situations, thereby deepening the service scenario Hsien-Hsien Liao, co-founder of Aiello, also believes that deepening the service scenario is the only way for consumer experience reach a certain level BERT proposed by Google also uses image analysis to replace the rule-based model and the exhaustive method of linguistics This technology has gradually become mainstream in the market The introduction of AI voice assistants into the hotel industry to provide services will effectively replace manpower to optimize and improve the quality and efficiency of room service The current version of Aiello is already online and will initially target the Chinese market The company is currently negotiating with hotel groups and system service providers in first-tier cities, and has two models monthly rental and buyout In the future, more services will be integrated to expand the business model, including calling taxis, purchasing tickets for entertainment, and booking travel packages In the future, the company will further design a new type of in-room service system specifically for hotels It transforms the in-room voice portal and the hotel's SaaS platform into a new retail channel to maximize benefits for hotel operators The current challenge is that it is difficult to find news and music content providers in Taiwan who are willing to cooperate in providing services However, as the system becomes more mature and the products continue to be promoted towards the hotel industry, more content manufacturers will be attracted to work with the company