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」

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

On the machine tool production line, there are some slight differences in the first step of assembly Accumulated tolerances will cause the assembly work to be repeated, which is time-consuming and labor-intensive, resulting in shipment delays that will impact the company's reputation Narili Technology Company focuses on the field of smart manufacturing and provides various AI solutions It uses machine learning models to inherit the experience of old masters In the CNC processing machine assembly and casting process, it uses AI to analyze production line data, accurately adjust various data, and improve Production accuracy is 25 This AI production line data analysis system is called "Master 40" by Huang Changding, chairman of Naruili Technology It is the most evolved version of the master plus artificial intelligence It has been used in machine tool processing factories with remarkable results In addition, Nairi Technology used AI defect detection technology to participate in the 2021 AI Rookie Selection Competition of the Industrial Bureau of the Ministry of Economic Affairs, assisting AUO in advanced panel image defect detection, with an accuracy rate of 100, and won the award Assisted panel manufacturer AUO to solve problems with 100 accuracy in defect detectionHuang Changding further explained that during the production of general panels, edges and corners are There may be defects in the corners Although the defects are visible to the naked eye, AOI is often difficult to identify, causing the detection error rate to often exceed 30 Therefore, re-inspection must be carried out with manpower to improve the accuracy rate However, in response to the demand for a small number of diverse products and insufficient manpower, using AI detection is indeed a good method Nairui Technology, founded in 2018, has been able to win the favor of major panel manufacturers with its AI technology in just three years In fact, it has been honed in the field of CNC machine tools for a long time Tang Guowei, general manager of Narili Technology, pointed out that the top three CNC machine tool factories in Taiwan hope to introduce AI into the two production lines of assembly and casting Among them, on the assembly line, in order to maintain the accuracy of assembly, every part of the component is designed Tolerances are designed During assembly, each component is within the tolerance However, the cumulative tolerance still fails the final quality inspection and must be dismantled and reassembled This is not only time-consuming and labor-intensive, but also causes waste "After entering the production line, I realized that some masters have accumulated a lot of experience and are good at adjustment After his adjustment, the accuracy rate has improved a lot and the speed is faster" On the contrary, the new engineers did not Based on experience, it takes a long time to adjust and may not pass the quality inspection The yield rate of Master 40 system has increased significantly from 70 to 95Tang Guowei then said that the original size data set by Master during assembly All were recorded on paper After the information was written, it was stored in the warehouse and sealed No one studied the relationship between the dimensions Narili assists customers in designing the Fu 40 system Through the human-machine panel, the master can directly input the measured dimensions and related data during assembly After collecting data from different masters, AI algorithms are used to analyze the relationship between the data and create an AI model The AI model automatically notifies the operator what size to adjust to, and the quality inspection will definitely pass In this way, the yield rate will be improved It has increased significantly from 70 to more than 95 Narili Technology Company focuses on the field of smart manufacturing and provides various AI solutionsTang Guowei added, assembling the spindle of a CNC processing machine It took four hours In the first step, the machine made measurement errors, including vibration, temperature, speed, etc that were out of range It had to be dismantled and reinstalled, which took another four hours How to adjust after disassembly depends on the experience of the master At first, the master may have done the best assembly method based on experience, but the error rate was also 30, and the assembly took several days With the assistance of AI masters, the assembly time only takes half a day, and the yield rate reaches over 95, saving a lot of time and manpower "Use the AI model of machine learning to collect the experience of all the masters and provide it for AI learning The first step is digitalization, and the second step is knowledgeization This is the transformation of the enterprise "An important key", Huang Changding believes that Narili Technology is an important partner in the transformation of traditional manufacturing from automated production to digital transformation In addition, another industry that Naili Technology focuses on is the smart car dispatching system of the leading brand of elevator manufacturers The so-called car dispatch referring to the elevator car means that if there are more than two elevators, group management is required In the past, car dispatching was based on fixed rules If the elevator was closer to the requested car, that elevator would be automatically dispatched On the one hand, it did not take into account that dispatching a car if the elevator was called too many times might make other people wait longer The previous vehicle dispatching model did not take into account the usage characteristics of the building, resulting in a lot of waste For example, in an office building, there are peak hours in the morning, lunch break, and afternoon after work AI smart car dispatch can be flexibly adjusted according to off-peak and peak hours, increasing the efficiency of car dispatch, reducing waiting time, and reducing wasted electricity Introducing elevator smart dispatch to improve transportation efficiency and have environmental protection functionsHuang Changding added that just like the previous traffic lights at intersections, the system has already The number of seconds to stop and pass on highways, sub-trunks and small streets is programmed Smart traffic lights are now used to flexibly adjust waiting times to make road sections prone to congestion smoother Using AI to learn usage scenarios and introducing a smart dispatch system into elevators will improve transportation efficiency and make it more environmentally friendly In addition to introducing smart elevator dispatching, Nairili also introduced AI into the smart production and shipment scheduling system of elevator factories Elevator factories often cannot accurately estimate the customer's elevator delivery date For example, office buildings or stores must be completed to a certain extent before the elevator can be installed on the construction site If affected by unexpected factors such as delays in the customer's construction period, the elevator factory will often be idle or the schedule will be difficult to arrange Tang Guowei pointed out that generally those who understand the progress of client projects may be from business or engineering, but overall, the accuracy rate of shipments is only about 60, which means that 40 of them will not be shipped as scheduled Therefore, if the shipping schedule can be accurately estimated, the production line can be freed up for emergency orders or other product production needs The AI smart scheduling system will analyze past shipment data, about 20-30 parameters such as climate, distance between the factory and the construction site, and customer credit, and put them into the AI algorithm to accurately predict whether shipments can be made as scheduled goods Huang Changding also specifically stated that the machine learning of Naili Technology is not ordinary machine learning, but also incorporates various calculation methods such as traditional image processing technology and statistics Only by being very familiar with the domain knowledge can we make good products AI models are also where the company’s competitiveness lies He emphasized that the data that general SaaS platforms can process is very limited, and the accuracy rate has increased from 70 to 75 at most Naili’s strength lies in AI algorithms and machine learning, and it must be coupled with in-depth industry knowledge to produce output Good AI model Narili Technology started with the AI project, gradually deepened the technology, chose to start with the more difficult tasks, and accumulated rules of thumb It is expected to develop SaaS services this year 2022, based on customer needs starting point, gradually gaining a foothold and becoming an important partner in smart manufacturing The picture left shows the general manager of Naruili Technology Tang Guowei and Chairman Huang Changding right「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」