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

AI information technology can be utilized in very distinct industrial fields.

Unmanned factories, automated production lines, and robotic arms, etc. To accelerate production lines to achieve economies of scale and simultaneously reduce costs, major production lines look forward to continuously optimizing in various aspects to reduce errors and increase yield rate.

In the production line, quality control testing is a critical step that significantly impacts product quality. Taiwan's Juou Technology Corporation stands out in its research and development efforts, not only addressing the management of Taiwan's resources and urban-rural development issues but also in its performance through innovative cross-disciplinary integration.

Within Juou's GEO IOT plan, two parts of the cross-disciplinary technology project are implemented:

Part one

Within the AOI technology area, there is active investment in the technical development of big data, artificial intelligence, and data science. It also involves the development of a high-speed, high-precision optical imaging inspection system in the production line quality management. This technology utilizes machine vision with high focus and sensing to capture the surface images of products and automatically assess whether the products meet the quality standards.

This non-contact inspection tool not only speeds up the inspection process and identifies product defects but also automatically discriminates flawed products. It is also applicable for the inspection of semi-finished products in the production line. In enterprises that are major producers in Taiwan or those with a focus on quality, this optical combined with image processing system is necessary.

Part two

Blood tests, crowd recognition, access control in danger areas (construction sites), IVS, AIR vehicle control

Biometric recognition technology utilizes the characteristics of organisms for identification, including iris, retinal, and body shape recognition. It also enables the monitoring of people flow within a specific space to quickly capture more information about crowd movements. Beyond handling crowd recognition, Juou Technology also employs recognition technologies for control and monitoring of hazardous areas such as construction sites and production lines. For instance, in spatial detection technology—if a construction worker forgets to wear a safety helmet or safety suit, the detection equipment will notify them upon entry to the site, thus reducing risks caused by human oversight.

Committed to the innovation of the brand and the integration between sectors, it is believed that through digital technology and multi-disciplinary integration, the sustainable and innovative development of Taiwan will be driven.

「Translated content is generated by ChatGPT and is for reference only. Translation date:2024-05-19」

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【解決方案】滴水不漏的智慧工安巡檢 鑫蘊林科Linker Vision的影像分析AI平台 創造巡檢時間從100分鐘降至3秒新紀錄
Watertight smart industrial safety inspection Linker Vision’s image analysis AI platform sets a new record of inspection time reduced from 100 minutes to 3 seconds

With the rise of smart manufacturing, there is a demand for industrial safety inspections in high-risk industries such as chemical, energy, and electrical industries Take pipeline inspection in the chemical industry as an example It relies heavily on manual regular inspection and monitoring, and lacks intelligent monitoring by a professional AI team This is not only time-consuming and labor-intensive, but may also cause accidental risks to employees in various industrial safety environments The image analysis AI platform developed by Xinyun Linke not only improves employee personal safety and reduces risk factors, but also significantly reduces the time for human visual inspection of pipeline abnormalities from an average of 100 minutes to 3 seconds Paul Shieh, founder and chairman of Linker Vision Co, Ltd Linker Vision, said, "The overall technological development and progress in the United States comes from entrepreneurship Linker Vision's original intention to start a business in Taiwan has been I hope that through my past experience in entrepreneurship in the United States, I can introduce the American entrepreneurial spirit and culture to Taiwan's budding entrepreneurial fertile ground and truly implement it "American entrepreneurial culture encourages employees to value ownership and emphasizes that employees regard themselves as owners of the company Be a part of the company, with a work attitude and spirit that would be better than mine The company's achievements are your own achievements, breaking the original employer-employee relationship The company will reward outstanding employees with stocks, share the glory together, and establish a partnership with employees Partnership On the other hand, Taiwan still has room for efforts in entrepreneurial culture and management, and it retains the traditional thinking of employers and employees It is expected that Xinyun Linke's establishment of American entrepreneurial culture and values in Taiwan will serve as a starting point to drive more domestic new companies to follow suit, and then Only by upgrading the business constitution of new software AI entrepreneurs can they break out of the cocoon and go global Facing the market, most international players focus on developing AI models and algorithms They are less willing to invest in data-centered Data-Centric AI services They think that processing large amounts of 2D or 3D data is quite time-consuming It’s also energy-consuming Seeing the gap in AI technology and encouraged by Microsoft, Xinyunlinke decided to fully invest in Data-Centric's AI technology layout and deep roots many years ago, and specialize in technical energy in data processing, filtering and accuracy Therefore, Become an important partnership with Microsoft for AI technology supply In addition, due to the gap in industrial demand, domestic large factories, whose strength is chemical manufacturing, still rely heavily on manpower for inspection of pipelines in the factory, which is time-consuming and labor-intensive However, in order to cater to the AI industry, the owner reorganized the IT department originally engaged in database management and control into an AI team However, due to the owner's lack of professional experience in AI software technology, AI models and related domain know-how, the owner introduced AI implementation Industrial safety monitoring in the chemical industry is even more challenging The world's first AI automatic labeling technology surpasses manual labeling and can visually identify objects with an accuracy of over 95 In terms of AI technology power, Xinyunlinke has launched the world's first dual-core innovative technology of automatic labeling Auto-labeling and automatic machine learning to create an efficient and stable image analysis AI platform to provide customers with the best Advanced and complete AI solutions In terms of automatic annotation, this AI technology can overcome the most difficult challenge in deep learning, which is to provide customers with the highest quality training data Taking self-driving cars as an example, how to enable one self-driving car to effectively identify another car is the importance of labeling In the past labeling methods, we first needed to collect digital images of millions of vehicles, roads, signs, and pedestrians, and spent a lot of manpower Manually labeling one image at a time was time-consuming, labor-intensive, high in labor cost, and inefficient Through automatic labeling AI technology, combined with automatic machine learning to automatically label digital images, AI can exclude human error labeling and then throw the correct data into the vehicle's brain for vehicle identification Compared with manual labeling accuracy of only 60, the accuracy of automatically labeling and identifying objects with AI can be as high as over 95 It can also reduce manual labeling time by more than 80 and save at least 80 of labor costs AI automatically marks AI behavior recognition for high-altitude operations In the automatic machine learning part, Xinyunlinke established an AI visual model with continuous learning capabilities to adapt to data changes By optimizing the overall development process, from AI data ingestion and filtering Data Selection to AI labeling AI Labeling , model training and verification, deployment and monitoring, so that AI computer vision can continue to learn more quickly and easily Automatic machine learning can currently be applied to different business cases such as object identification and counting, personnel entry and exit security detection, product defect detection, people flow identification, product shortages on shelves, etc Looking at domestic companies such as TSMC, Formosa Plastics and Hon Hai towards intelligent AI management and purchasing a large number of cameras to meet the image recognition needs of industrial safety surveillance, coupled with the introduction caused by the unfamiliarity of existing customer organizations with AI applications Thresholds and preliminary preparations for image recognition include complicated workflows such as data screening and annotation To this end, Xinyunlinke has been committed to accelerating the development of AI computer vision applications in recent years, providing client-to-end services, and can flexibly deploy according to customer needs Complete automated AI solution services in the cloud, on-premises, or cloud on-premises Xie Yuanbao said that the AI automation technology process provides data selection Data Selection AI technology through domain-type pictures given by customers, helping customers automatically filter out precise such as 10,000 transactions from a large amount of data such as 1 million transactions Data, and by using the AI algorithm technology of Auto-Labeling to replace manual labeling, it can effectively save customers a lot of labor costs and achieve efficient data labeling processing In addition, the AI technology of automated machine learning can help clients customize automatic AI model training or repeated training when the factory environment changes, providing more accurate AI models and allowing customers to operate autonomously Through the above-mentioned key features and advantages of the automated AI technology provided by Xinyunlinke, we believe that it can definitely meet the needs of customers for an automated end-to-end AI independent learning platform, and at the same time, it can significantly save customers the cost of AI team establishment In terms of technological competitiveness, in addition to providing the chemical industry with AI image analysis applications in smart industrial safety, Xie Yuanbao said that Xinyunlinke can also extend the process application of automatic annotation and automated machine learning to different industrial landing services, such as Various fields such as self-driving cars, smart warehousing self-propelled robots and self-driving buses in future smart cities are all in line with the spirit of automated mobility of Mobility as a Service We look forward to the role played by Xinyunlinke The process of image annotation in different industries accelerates the efficiency of developing image recognition services in different fields We believe that by providing client-to-end AI solutions and a complete set of automated AI image analysis pre-operation processes from Data Selection AI technology, Auto-Labeling AI technology, and automated machine learning AI technology, we can greatly satisfy our customers The demand for AI autonomous learning platform Image analysis AI platform sets a new record for smart industrial safety inspections from 100 minutes to 3 seconds Seeing the high demand for industrial safety supervision in high-risk industries such as the chemical industry in recent years, Xinyunlinke launched the "Vision AI Platform", which uses AI image recognition technology Its main functions include real-time AI streaming It has four major functions detection, event notification, defining customer-specific AI models and continuous learning In the real-time AI stream detection part, the Vision AI system can use the customer's factory camera combined with the AI module to perform real-time stream detection of AI image events It can help customers manage various operations and factory environments and keep track of them anytime and anywhere Various work situations in terms of event notification, the Vision AI platform can provide a web version or APP or LINE instant messaging software to provide customers with video records of the events at that time, so that the team does not miss any events, maintains daily production capacity and reduces accidents in defining customers In terms of exclusive AI models, a variety of basic AI models are available, including 8 detection scenarios electronic fences, personal safety equipment, construction safety equipment, construction operations, personnel counting, screen availability, smoke detection, pipeline corrosion and damage , illegal stacking for use in different industries, customers can build exclusive AI models without spending time writing programs in the continuous learning part, the Vision AI system can provide customers with the performance and accuracy of AI models, and have the ability to adapt as the environment changes Continuous learning ability Vision AI has a simple user interface and intuitive operation For cross-field industries, this platform has automated and flexible AI capabilities Customers can build self-defined AI models without spending time writing programs, and Vision AI gives AI models the ability to continuously learn and improve, allowing customers to save the labor cost of building an AI team In addition, the platform can significantly reduce the manpower allocation for routine inspections required for operational safety management, improve employee safety in the working environment, and reduce on-site accidentsrisk factors at various work sites In the platform operation mode, customers can reduce the risk of manual monitoring operations through remote operations, ensuring normal work operations and uninterrupted production operations They can also review high-risk operating situations and collect data to assist in the planning and correction of operating processes In addition, in order to ensure that customers comply with government regulations, Vision AI can help customers control the equipment and safety regulations required in different workplaces at any time through the platform's event notification and management detection The image analysis AI platform is used in cross-field AI image recognition technology Generally, for industrial safety inspections in the chemical industry, most rely on the naked eye of personnel to regularly inspect pipeline abnormalities It takes an average of 100 minutes to scan an area each time, which is time-consuming and laborious, and the pipeline location is difficult to visually observe, which may cause Employees are exposed to accidental risks in various work safety environments In order to reduce the pain points of industrial safety inspections in the chemical industry, Xinyunlinke assists well-known domestic chemical industry players by using an automated image analysis AI platform, combined with customized virtual electronic fences, and using in-plant cameras to configure AI pipeline leakage modules , the AI automatic inspection method can effectively reduce the abnormal detection time to less than 3 seconds In addition, cameras deployed in the factory can automatically record inspection schedules to achieve full-time monitoring, allowing customers to instantly discover and fully control pipelines, minimizing risks In addition, the automated image analysis AI platform can help customers apply fire warnings in factories It is conservatively estimated that the return on investment can be less than 9 months to pay back the investment The longer the platform is used, the higher the cost-effectiveness Build an automatic learning image analysis AI platform for Mobility as a Service in various fields Xie Yuanbao observed that the biggest challenge facing the entrepreneurial culture of software companies in Taiwan is that young new entrepreneurs or employees in Taiwan do not understand the entrepreneurial model and lack the awareness to regard themselves as part of the company owners This has caused It is a pity that your future is unclear or you have a past-experience mentality that prevents you from staying competent in a new start-up company for a long time I believe that the essence of true entrepreneurship lies in every employee rolling up their sleeves and working hard, so that they can truly enjoy the fruits of entrepreneurial profits Otherwise, for young entrepreneurs or employees who often change tracks, it will be like a rolling stone that gathers no moss , I am unable to take a deep root on the road of entrepreneurship, and I lose my ability to solidly accumulate financial independence Regarding the business promotion challenges of Xinyun Linke, Xie Yuanbao said with emotion that because the Taiwan market does not have a deep understanding of AI software applications, it relies more on open source AI visual analysis or machine learning and other resources on the market, but in fact These AI technology resources are limited in their ability to support customers' AI model needs, resulting in uneven quality of AI visual analysis software in the market Therefore, the impact is more indirect on Xinyunlinke's ability to truly provide customers with professional and data-centric AI image analysis services, and it also reduces the company's original business value in customer reference In terms of technical research and development challenges, the visual analysis AI platform cannot rely solely on AI model experts It must gather talents in various fields such as cloud, machine learning, data science, front-end and back-end and other professional team combinations to make the platform operate successfully Xie Yuanbao said that he believes that only through the automatic learning of the visual analysis AI platform, automatic fast and accurate data processing capabilities, and providing customers with complete AI solution services in the cloud, cloud ground Hybrid to pure ground, can we truly Convince customers and stand out from the competition Looking to the future, Xie Yuanbao hopes that Xinyunlin Technology can build an image analysis AI platform for Mobility as a Service to automatically learn in various fields such as self-driving cars, smart warehousing robots, and unmanned buses in smart cities At the same time, I am also grateful to the support of the Industrial Bureau of the Ministry of Economic Affairs for the smooth landing of Xinyunlin Technology in Taiwan and the opportunity to recruit talents from all walks of life to work together In the short-term layout, the company will actively cooperate with domestic players such as Hon Hai and TSMC to implement image analysis AI technology in fields such as self-driving cars, smart industrial safety, and smart warehousing robots In the medium to long term, Xinyunlinke will target the United States, Europe, Japan and other countries as its global market layout, establish investment and cooperation partnerships with major international companies such as Microsoft, and replicate its successful experience and promote it internationally Xinyunlinke official website Xie Yuanbao, founder and chairman of Xinyunlinke 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】AI智慧眼鏡 雄欣科技鎖定智慧照護市場 讓老者住得安心安全
AI + Smart Glasses: Hsiung-Hsin Technology Targets Smart Care Market, Ensuring Safety and Security for the Elderly

In the small care room, Mr Wang, who is over eighty, is coughing intensely The nurse gently uses a suction device to help him, hoping to make him more comfortable Meanwhile, a sharp-eyed family member notices that the nurse is wearing smart glasses At the other end, the doctor organizes medical records while simultaneously monitoring Mr Wang's condition on a screen With the advent of precision care, it will soon be a blessing for the care market for doctors to remotely monitor crucial physiological information of the cared-for in real time In fact, Hsiung-Hsin Technology, established in 2020, uses smart glasses combined with AI algorithms to launch smart care services as an AI startup Through AI multiple sensors to achieve effective smart care In 2021, Hsiung-Hsin Technology participated in the Ministry of Economic Affairs Industrial Bureau AI Emerging Selection event, cooperating with smart glasses leader Jozhen Technology Jozhen provided millimeter-wave radar and smart glasses, combined with Hsiung-Hsin Technology's AI algorithms, to launch 'AI Care Recognition Service System' and a life-saving 'Fall Prevention System' The 'AI Care Recognition Service System' uses radar millimeter waves and Time-of-Flight ToF among various sensor technologies combined with point cloud and mmWave deep learning analysis in AI algorithms While protecting personal privacy, it can detect patients' physiological data upon hospital admission as well as detect falls and bed exits during bed care The 'life-saving fall prevention system', on the other hand, utilizes artificial intelligence and 3D technology, combined with radar sensing devices, while protecting personal data through 'de-identification' technology, detecting falls in real-time in the environment Building the AI Care Recognition Service System, Hsiung-Hsin Technology is aiming at the smart care market Lee Jia-Hsin, founder and chairman of Hsiung-Hsin Technology, who has worked for IBM Taiwan for 14 years, states that after placing millimeter-wave radar in the medical test field, combined with AI algorithms, they can obtain physiological signals such as the patient's breath and heartbeat Moreover, when paired with Jozhen's smart glasses, during a doctor's consultation, the physician can immediately see the patient's heartbeat and breathing data through the glasses, enhancing efficiency Additionally, Jozhen has also developed a management platform where physicians and nursing staff can view the patient's physiological data at a glance After integrating the 'AI Care Recognition Service System' and 'Life-Saving Fall Prevention System', they were launched and commercialized in June 2021, and officially introduced into Kaohsiung Municipal Triumph Hospital by the end of November last year It not only helps medical staff understand the residents' physiological conditions, monitoring elders' physiological data continuously, but also reduces the burden on medical institutions while preventing accidents and enabling quick action in emergencies to provide optimal medical care Aside from medical institutions, another major target customer group for Hsiung-Hsin Technology's products are long-term care institutions, with ongoing product implementation plans in Tainan and Eastern Taiwan On-demand lightweight design, easy to use and reasonably priced Lee Jia-Hsin mentions that the company's productsservices are developed in-house, designed to be lightweight Depending on the needs of the institution where they are implemented, they may choose between CPU computing or edge computing for flexible configuration, which is very convenient and also comparatively cost-effective In the future, through Jozhen smart glasses, diagnoses can be made more immediately and quickly The method allows nursing or care staff to wear smart glasses when visiting patients or residents The images seen by the nursing staff's eyes are transmitted in real-time to the backend, allowing doctors to make immediate diagnoses based on real-time images and take appropriate care measures, effectively assessing the patient's condition on time Hsiung-Hsin Technology's smart care services have been listed on the Startup Common Supply Contract Platform Last year, Hsiung-Hsin Technology's productsservices were also listed on the Ministry of Economic Affairs, Small and Medium Enterprise Administration's Startup Common Supply Contract Procurement Platform, available for government agencies, public medical institutions, and long-term care facilities to purchase for lease In the future, they hope to expand to private medical institutions and care centers, enabling more care facilities to utilize technology for transformation and reducing the talent shortage in the care market Furthermore, with more than 300,000 elderly people living alone in Taiwan, Lee Jia-Hsin believes that as the aging society approaches, the health and safety issues of solitary elderly individuals are increasingly receiving attention If technological care medical solutions can be incorporated into the subsidy scope for assistive devices, it can also help reduce the burden on local government institutions for solitary elderly care, effectively lowering societal costs Extended application Smart campuses enhance management safety and efficiency Lee Jia-Hsin points out that the company's core values are making life safer and improving living quality The company has developed its own software and hardware solutions for big data, artificial intelligence, and the Internet of Things Using a hybrid cloud development approach, it addresses various types of medical care pain points, enhances medical management efficiency, and improves residents' safety, thus significantly enhancing overall services by medical institutions Hsiung-Hsin Technology's partners include SI businesses, medical care institutions, large chain restaurants, and major venues In the future, there are plans to develop into an AI SaaS company, extending services to Japan, Southeast Asia, and other overseas markets Additionally, Lee Jia-Hsin, who teaches at Tunghai University in Taichung, is also actively promoting the smart campus initiative Currently, Hsiung-Hsin Technology has established a 'smart campus' at Tunghai University, utilizing up to 700 cameras throughout the campus to build a miniature AI SaaS platform for monitoring This not only allows for mask, human traffic, restricted area, and license plate recognition within the campus but also enables automatic records of the campus's flora and fauna, greatly aiding in the efficiency of campus safety management As the population gradually ages, home care becomes a universal challenge With a low doctor-to-patient ratio, both inside and outside hospitals, including extended to care institutions, medical professionals face a scarcity of manpower Using AI technology to assist the elderly care market presents itself as the best solution Besides smart elderly care and smart campuses, Hsiung-Hsin Technology also applies its image recognition technology in places like factory safety and parking lot license plate recognition, and future applications will continue to expand boundlessly Hsiung-Hsin Technology's founder and chairman, Lee Jia-Hsin「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】2秒鐘完成結帳動作 Viscovery AI影像辨識助攻智慧零售
Complete checkout in 1 second, Viscovery AI image recognition assists smart retail

Artificial intelligence AI has gradually changed the way various industries operate in recent years However, most of the work is still done by humans, with AI playing a supporting role This has led to emergence of the term "AI Copilot," which stands for "AI-driven tools or assistants" that aim to assist users in completing various tasks and improve productivity and efficiency The concept of AI Copilot comes from the role of "co-pilot" During flight, the co-pilot assists the main pilot in completing various tasks to ensure flight safety and efficiency In fact, there have been signs of various "machines" beginning to play the role of "copilot" in different fields since the Industrial Revolution, assisting humans in completing heavy physical and repetitive tasks, greatly improving factory production efficiency, and driving rapid economic development Following the advancement of computing equipment and breakthroughs in machine learning, deep learning, and image recognition technologies, the concept of AI Copilot has gradually taken shape The development of AI Copilot marks the transition from "machine-assisted to AI-assisted" Early robots could only complete preset repetitive tasks, but today's AI copilot can learn and adapt to new environments and tasks, and continuously optimize its performance in practical applications This transformation not only changes human-machine interactions, but also has a profound impact on various industries The application scope of AI copilot covers various industries, including finance, healthcare, manufacturing, education, retail, etc, and are everywhere to be seen Application of AI copilot in the retail industry AI image recognition checkout In the retail industry, the application of AI copilot has begun to show concrete results Take Viscovery's AI image recognition checkout system as an example This system is a type of AI copilot model that helps store clerks speed up checkout or assists consumers in simplifying the self-service checkout process The store clerk needs to scan the product barcodes one by one in the regular checkout method If a product does not have a barcode, such as bread and meals, the clerk needs to first visually confirm the items, and then input them into the POS checkout system one by one Based on actual measurements at a chain bakery, it takes 22 seconds for an experienced clerk from "visual recognition" to "entering product information of a plate of 6 items into the checkout system" New clerks may need even more time In addition, according to a Japanese bakery operator, it takes 1 to 2 months to train employees to become familiar with products Now with AI image recognition technology, store clerks let AI handle the "product recognition" step, and AI will play the role of copilot, quickly identifying items within 1 second, speeding up checkout to save 50 of checkout time, and optimizing customers'shopping experience The time cost of training employees to identify bread can also be effectively shortened Even for products with barcodes, AI can quickly identify multiple items in one second, which is more efficient than scanning barcodes one by one The self-checkout system "assisted" by AI image recognition allows consumers to successfully complete shopping without the help of store clerks, eliminating the trouble of swiping barcodes or searching for items on the screen, which improves the shopping experience In a time when store clerks are hard to hire due to labor shortage, this also helps stores reduce operating costs AI quickly identifies multiple checkout items in just one second Source of image Viscovery Recently, startups dedicated to developing AI image recognition checkout solutions have emerged in various countries The most lightweight solution currently known is in Taiwan It can be immediately used by installing a Viscovery lens and a tablet installed with Viscovery AI image recognition software at the checkout counter to connect to the store's existing POS checkout system There are various integration methods, including plug-and-play and API solutions integrated with the store's POS system Viscovery AI image recognition system can be painlessly integrated with the store's existing POS system Source of image Viscovery Example of AI image recognition checkout Currently, the Viscovery AI image recognition system is being used in bakery chains in Taiwan, Chinese noodle shops in Singapore, micromarkets in department stores in Sendai, Japan, and Japanese bakeries and cake shops Over 7 million transactions were completed through this AI system, which identified more than 40 million items These use cases demonstrate the extensive application of the Viscovery AI image recognition system in the retail industry In the future, the company will continue to explore the various possibilities of using Vision AI in retail and catering nbsp The Viscovery AI image recognition system is already being used in bakeries, cake shops, restaurants, and convenience stores in Japan, Singapore, and Taiwan Source of image Viscovery