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【2020 Solutions】 Anomaly Detection Solves the Problem of Insufficient Defect Images

E-Hui Technology collaborates with the Institute for Information Industry to create an anomaly detection system

In closed production lines where anomaly data is hard to collect, the biggest problem with AI image recognition is the paucity of training data and its rarity, making implementation very challenging. E-Hui Technology, in collaboration with the Service Creation Institute of the Institute for Information Industry, has developed unsupervised learning technology, wherein the computer does not need to label specific items to recognize during its learning process. It classifies based on the characteristics of the data. For instance, in manufacturing, where defect detection is critical, the system first learns from the predominantly normal products on the production line. When a few defective items are mixed in, the machine uses classification rules to screen out the defective items. Similarly, if a consumer credit card transaction suddenly shows completely unusual characteristics that do not match typical patterns and habits, the machine autonomously detects this anomaly. Due to its distinctiveness, this technology is applicable to unique sectors.

Using unsupervised deep learning algorithms for developing AI anomaly detection technology eliminates the need for collecting and labeling anomaly data, reducing the introduction period to 1-2 months. The target market is traditional industries such as chemical and steel, which find it difficult to gather anomaly data. This technology has a high tolerance for image quality, requiring only regular surveillance footage from the production line to train the model. It can detect various types of anomalies and has a simple and fast implementation process. The system includes components for image acquisition, training mechanisms, edge real-time computing hosts, and cloud inspection services, forming a complete anomaly detection solution that can be integrated with factory patrols, apps, and other reporting mechanisms.

Anomaly Detection System

 

Anomaly Detection System-2

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

Recommend Cases

【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

【解決方案】運用極現科技4D無人機雲端平台 巡檢成本降為五分之一
Utilizing Extreme Present Tech's 4D Drone Cloud Platform Reduces Inspection Costs to One-Fifth

The use of drones for intelligent inspection is becoming increasingly common, with major petrochemical and solar power plants continuing to adopt drone applications Located in Hsinchu, Extreme Present Technology earthbook has established a 4D cloud platform using its proprietary technology, offering drone, software, and data analysis platform services for intelligent inspections at solar power and petrochemical plants, reducing the total cost to just one-fifth of traditional methods involving hardware and software purchases, and cutting down the time from one month to approximately 24 hours, making it highly cost-effective For petrochemical industry operators who are constantly in a high-temperature, high-pressure dangerous environment, the safety control and inspection of plant facilities are critical 'As long as we can enhance the capabilities of facility inspection and risk identification in petrochemical sites, resource input is absolutely not an issue,' said a petrochemical industry representative with emphasis By implementing the drone 4D AI inspection cloud platform, the efficiency and safety of facility inspections among petrochemical operators can be elevated, further reducing the risk of equipment downtime Founded in March 2018, Extreme Present Tech has become a consistent winner in domestic entrepreneurship competitions, including being crowned champion in the 2019 OPEN DATA Business Innovation Practice, selected into Microsoft's startup accelerator in 2020, chosen for NVIDIA's AI startup team in 2021, and its products have been launched on the Microsoft Azure platform, earning investments from the National Development Fund and major domestic groups, thereby securing strong market validation for its technical prowess and services The founder and CEO of Extreme Present Tech, Hsu Wei-Cheng, mentioned that at the beginning of its establishment, the company took on the national space center's satellite 3D photography scheduling system and specialized in the integration of geographic information into 3D images As drone hardware technologies matured, the company shifted its operations towards the drone market and combined it with AI image recognition systems to establish a 4D cloud DaaS platform, offering services including online aerial photography ordering DaaS, 5GAIoT cloud platform SaaS, and enterpriseAPI server software, to meet the demands of drones in smart cities, facility inspection, engineering management, disaster response, pollution monitoring, and other applications, maximizing the value of drone services Smart aerial inspection regularly tracks the health status of plant equipment at a glance The quantity and area of petrochemical plants in Taiwan are immense, lacking sufficient manpower for comprehensive equipment inspections Given that petrochemical plants produce high-temperature flammable and corrosive chemicals that must be transmitted and stored through pipelines and tanks, long-term risks like pipeline ruptures and tank blockages could lead to severe occupational safety disasters, equipment downtime, and production stagnation Given the shortfalls in personnel for equipment inspections among petrochemical operators, Extreme Tech has already implemented a 4D AI drone inspection cloud platform combined with AI image recognition technology in petrochemical plant areas, providing ground-breaking evidence through the use of drones and proprietary app software services that connect on-site aerial data collection to the cloud platform, achieving fully automated and real-time aerial monitoring of petrochemical plant equipment pipelines, tanks, and ensuring precise locations and angles for each aerial operation, effectively compensating for the discrepancy in human inspection Hsu Wei-Cheng pointed out that the inspection drones used in petrochemical plants are equipped with dual lenses, one visible light and the other thermal infrared, which allow for determining pipeline obstructions through temperature conditions, enabling clients to immediately view the inspection status of the plant area from remote locations via the earthbook website, enhancing clients' inspection efficiency and accuracy The 4D aerial data platform meets diverse applications such as smart cities, transportation, engineering management, and pollution monitoring DaaS Online Order-Use Model Innovates Aerial Photography Business Model Saving 15 Costs Apart from providing a 4D aerial data platform, Extreme Present Tech also offers DaaS Drone as a Service After customers place orders on the website, Extreme Present coordinates with professionally licensed aerial photographers to provide on-site services Customers can monitor real-time operations through the platform and quickly obtain aerial data to evaluate any abnormalities, enabling timely alerts Take the solar power plant monitoring service as an example Given that solar power plant areas are large and widely distributed, located in the remote Pingtung area with the headquarters in Taipei, for inspections of the Pingtung plant, the customer just needs to use the DaaS service model, directly order online and upload a map of the Pingtung plant, obtain a quote from the company, and then entrust local Pingtung pilots to perform aerial inspections of the solar power plant During the process, the drone's route is automatically calculated by AI to plan the flight path, and the aerial data is transmitted to the client's cloud account, allowing the Taipei headquarters clients to immediately see the inspection status of the solar power plant from the earthbook website such as the condition of the solar panels, dust detection, or abnormal heat generation from solar electromagnetism, effectively helping the customer significantly reduce operational costs and efficiently complete the solar power plant inspection service Introduction of DaaS online aerial photography service in petrochemical plants According to estimates, solar power plant clients often incur high personnel costs by purchasing drones or outsourcing aerial photography With the long-term provision of aerial photography devices and the DaaS business model by Extreme Present Tech, customers can save 45 of aerial photography costs, and obtain aerial inspection reports within 24 hours post-operation, helping clients efficiently identify issues with solar panels Aiming to become the largest aerial data service company and enter the Southeast Asian market Since its establishment in 2018, Extreme Present Tech has rapidly grown in the aerial photography market with innovative thinking, actively expanding its aerial data application services Currently focused on cultivating the Taiwan market, the company aims to enter Southeast Asian nations, with Indonesia chosen as the first stop due to its high demand for infrastructure Hsu Wei-Cheng hopes that earthbook becomes the world's largest aerial data service platform Besides completing the initial round of funding from the National Development Fund and major groups, to penetrate the international market, the company continuously improves its drone data services and AI technology innovations, while also requiring the assistance of entities like the Industrial Technology Research Institute to find strategic investors that complement the company, fulfilling its goal of becoming an international aerial data corporation in phases Founder and CEO of Extreme Present Tech, Hsu Wei-Cheng「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

這是一張圖片。 This is a picture.
Smart Construction Site Security Platform

In construction site operations, implementing safety protection measures and establishing related processes are essential for controlling workplace safety Every business owner strives to minimize industrial safety risks To reduce the probability of workplace accidents, it is particularly important to inspect personal protective equipment PPE and safety measures The Yongyi Smart Construction Site Security Platform utilizes an AI-embedded system, not only to detect whether workers are properly wearing helmets, but also to manage access control at construction site entrances and verify worker identity The Smart Construction Site Security Platform is also a part of the government's push for the Smart Construction Label Initiative 'Smart Site Management' is one of the three main items under the 'Maintenance Management' indicator, highlighting the importance of 'Smart Site Management' This solution includes access management, surveillance management, safety management, and environmental monitoring as aspects of its AIOT solution Feature Highlights 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-11-09」