Special Cases

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2021.9
【2021 Application Example】 Fongyu Uses AI Knowledge-based Fish Farming to Effectively Increase Aquatic Production by 10%

Fisheries is an important industry in an island economy However, the fish farming industry has faced severe challenges in recent years, including climate change, labor shortage, and rising costs In particular, nearly 110,000 workers in agriculture will retire due to old age over the next 10 years For this reason, the need for aquaculture to move towards smart farming is becoming increasingly urgent Founded in 2014, Fongyu Corp Ltd has developed a unique eco-friendly farming model based on its own fish farming It uses AI knowledge-based fish farming to effectively increase aquatic product production by 10, and reduced labor cost by 15 The word "Fongyu" has a profound meaning "Fong" represents good mountains and "Yu" represents good water, and is the hope that companies will allow Taiwan to always have good mountains and good waterIt is also a homophone for "having a full figure," expressing the hope that products will give consumers a full and healthy body and mind The founder of the company, Liu Chien-Shen, has been through the difficult entrepreneurial journey of becoming an apprentice in fish farming, raising funds, renting fish farms, establishing a fish farming company, building a brand, and expanding sales Labor shortage and aging workers are hidden worries in the fish farming industry Currently, fish farms in Taiwan are still mainly traditional fish farms, and farming techniques are still passed down through word-of-mouth In addition, the labor shortage and average age of workers exceeding 60 years old has made it impossible to effectively stably improve productivity and yield This farming method makes it difficult to prevent and control diseases, and greatly increases the possibility of excessive use of drugs, environmental pollution, and water quality and ecological damage, creating a vicious cycle that lowers the quality of fish farming In addition, 651 of workers in Taiwan's fish farming industry are inadequately skilled With limited support from IoT sensors, traditional fish farmers still mainly rely on their own experience and knowledge for water quality management, feeding, and disease detection Fish farming management relies heavily on the ability of individual fishermen Once experienced workers retire, the industry will not only face the issue of succession, but also the difficult of stably supplying a certain amount of harvest that meets quality standards This may cause a dilemma for the entire industry from fish farming to sales In order to improve the pain point of inability to pass on experience in fish farming, and at the same time create a "digital" foundation for fish farming, the top priority must be to collect farming behavior data and develop AI services as an important starting point Fishery digital twin technology helps fishermen transition to smart farming With the assistance of the Institute for Information Technology III, Fongyu implemented the "fishery digital twin" technology to dynamically adjust the farming schedule In other words, the fish farming schedule is adjusted according to the species, habits, and variables of the fish The use of AI in fish farming not only effectively increase aquatic production by 10, but also reduced labor cost by 15 In terms of specific methods, we first digitalized the fish ponds, feed, and decision-making behavior for each species, such as sea bass and Taiwan tilapia, and recorded the seasonal temperature changes from releasing seedlings to harvesting, all of which were digitalized, gradually recording the experience and methods of experienced workers into a rich database Based on the recorded data, we analyzed the compound variables to find the best farming behavior and generate a dynamic farming schedule The records for each pool provide data on workers' experience However, fish farming behavior generally relies on rules of thumb Even experienced fish farmers cannot ensure that they will find the best solution Therefore, new methods are proposed to solve this issue That is, "to determine the best fish farming behavior by predicting the interaction with water quality and past data on feeding, and evaluating fish farming behavior based on water quality and fish farming," and provide fishermen with the most intuitive recommendations through daily schedules To continue optimizing the dynamic fish farming calendar on a rolling basis, iterations of the model will be developed through the three-step cycle 1 Input the current fish farming calendar into the model 2 The model predicts the future environment 3 Shortcomings of the fish farming calendar are corrected based on the future environment to obtain a new version of the fish farming calendar In the process, the experience of aquaculture experts is used to establish the causal relationship between fish farming behavior and the environment The establishment of a dynamic fish farming process and technology-based fish farming recommendation services provide a traceable and detailed fish farming process It is one of the few technologies that can digitalize fish farming Fishermen can quickly and easily record their daily behaviors to build knowledge without taking up too much time, but in the long run it can reduce labor cost by 15 and increase output and revenue by an average of 10 Smart fish farming has achieved outstanding results, reducing labor cost by 15 and increasing output by 10 At the same time, the fish farming calendar can also be extended to different aquatic species, such as white shrimp, milkfish, clams, and Taiwan tilapia, to produce fish farming schedules for ponds with different specifications, and the harvested aquatic species can be traced according to different specifications, establishing vertically integrated services for safe food products Fongyu's main products are divided into two categories One is aquaculture modules, including fry, feed, materials and probiotics, production planning and processes, and monitoring, which can be sold separately or exported as modules The high-quality aquatic products produced by Fongyu have repeatedly won awards Figure Fongyursquos official website The other category is high-quality aquatic products, including seabass fillets, seabass balls, oil-free seabass balls, seabass dumplings, and seabass soup The products have won various awards, including the top ten souvenirs in Pingtung in 2017, "Barramundi Fillet" won the 2017 Eatender of the Council of Agriculture COA, "Oil-Free Barramundi Fillet" won the 2018 Eatender Gold Food Award of the COA, and "Dumplings of Barramundi" and "Barramundi Broth" won the 2019 Eatender of the COA The consecutive awards represent that the "quality" of Fongyursquos aquatic products can be seen and eaten with peace of mind In addition, Fongyu has exclusive fingerlings that meet international needs, such as Pure seawater cultured tilapia fingerlings and seawater Taiwan tilapia fingerlings from selective breeding FY-01 are items that aquaculture companies in many countries are looking forward to The company also has aquaculture modules, disease monitoring tools, and feeding materials designed in accordance with the environment, in order to provide customers with more stable income

2021-09-28
【2021 Application Example】 Hamastar Technology Builds an AI Model Management Platform to Accelerate the Application of AI

Riding the AI hype train, financial service providers are using their solid foundation in the industry to not only transform themselves, but also assist their customers with transformation Hamastar Technology, which has been established for over two decades, has been developing AI technology and assisting industry customers with the implementation of AI in recent years Hamastar Technology believes that to implement a complete AI project, in addition to AI theoretical knowledge, data analysis, and model training capabilities, it is also necessary to develop APIs for data, establish databases, develop front-end RWD web pages, and even consider layout design and user experience based on customer needs These tasks create technical barriers for AI startups Even from the perspective of companies that have reached a certain scale, it is hard to accumulate technical experience and accelerate business growth due repeatedly investing manpower developing similar functions in each project Institutional customers still require high level of customization for AI Using the requirements of government Agency A implemented by Hamastar Technology as an example, users must control false information from specific channels The platform needs to provide data ingestion functions for training models and predictions, and can complete natural language processing NLP text classification model training and use When the model discovers false information, it needs to immediately notify responsible personnel through messaging software The need of Agency B is to use an AI model to automatically classify petitions and immediately provide information on past cases as reference for the petitioner or officer Although the project models are similar data ingestion, model prediction, warning notification, the required functions still need to be separately developed for individual projects, and existing programs and models cannot be reused to speed up the implementation of subsequent projects After in-depth discussion, Hamastar Technology found that pain points of enterprises implementing AI projects include high implementation costs and lengthy project schedules It is difficult for a single enterprise to simultaneously have data scientists, analysts, engineers, and designers Current projects are all focused on solving the needs of specific fields, and it is difficult to reuse the AI models in other fields of application At the same time, the tools are concentrated in AI projects and cannot provide customers with total solutions In other words, due to the "limited manpower," "restricted fields," and "insufficient tools" of AI service providers, the implementation of AI technology projects requires high costs or lengthy timelines These are common problems that companies urgently need to solve Therefore, if there is an AI model application service management platform, it will be able to solve the above difficulties and not only reduce costs, but also accelerate project implementation and provide customers with one-stop solutions AI model application service management platform assists in quickly completing projects Therefore, with the support of the AI project of the Industrial Development Bureau, Ministry of Economic Affairs, Hamastar Technology carried out the "AI Model Application Service Management Platform AISP RampD Project" and engaged in the RampD of AISP products The purpose is for AI service providers to complete the AI projects with twice the result using only half the effort The AISP provides one-stop AI solutions AI service providers can quickly assemble required functions, such as data API, model management, and model prediction result monitoring subscription through existing module functions of the AISP It also provides commonly used graphical tools to help companies quickly design interactive charts or dashboards required by users, effectively reducing the labor costs required to execute projects, shortening the solution POC or implementation time, and accelerating the implementation and diffusion of industry AI In terms of product business model, in the short term, the company will extensively invite IT service providers with expertise in the field of AI to work together, and use platform services to solve the AI implementation problems faced by requesting units in various field, gradually building trust in the platform brand In the mid-term, the company hopes to gradually expand the market based on its past success, and form strategic alliances with multiple IT service providers to solve more and wider problems in specialized fields and provide more solutions for units to choose from The platform combines field experts to jointly expand overseas markets In the long term, after establishing AI strategic alliances in various specialized fields, the platform will have a large number of AI solution experts for specialized fields After accumulating a large amount of successful project experience, Hamastar Technology hopes that the AISP will be able to work with experts companies to expand into the international market Harmastar Technology Co, Ltd was formed in 2000 by recruiting numerous senior professional managers and technical experts in related fields It is committed to software technology RampD and services, and aims to develop into an international software company, actively creating opportunities for international cooperation in the industry Under the excellent leadership of its first president, the company has rapidly grown into a major software company in Taiwan

2021-11-08
【2021 Application Example】 Transforming into a Large-Scale AIoT Technology Playground: The Spectacular Makeover of the National Museum of Marine Science & Technology

Taiwan is a maritime nation When you visit the Badozi Fishing Port or Tidal Park in Keelung, do you also explore the mysteries of the ocean world at the 48-hectare National Museum of Marine Science amp Technology To get more people closer to marine technology, Keelung's Marine Museum has introduced technological services, transforming the venue into a large technology playground that delights both children and adults, fully utilizing the 'learning through play' approach After a lengthy planning process, Northern Taiwan's largest marine science museum in Keelung opened in January 2014 The museum focuses on marine education and technology, boasting Taiwan's largest IMAX 3D ocean theater The unique themes and modern viewing facilities should make it a well-known landmark in Keelung However, the original exhibition planning was static and highly specialized, lacking sufficient interaction with the public Visitors who have attended the museum also reported that the exhibits were limited and quite boring, leading to poor overall consumer experience ratings The top three dissatisfactions with the museum were weak connections to surrounding attractions, unengaging display content, and lack of exhibit material According to statistics from the Marine Museum, the ratio of local to visiting guests is approximately 64, with most foreign visitors coming from the north transportation is primarily by car and bus common types of visits include family, parent-child, and friends and the stay duration is generally 1 to 2 hours Upon deeper investigation, the top three visitor complaints were weak linkages to surrounding attractions, unengaging display content, and insufficient number of exhibits The museum analyzed potential reasons, including some displays being too specialized, making it difficult for the public to understand, and a lack of interactive elements, making the exhibition boring and the visit hurriedly brief Analysis of visitor profiles revealed that since half of the museum's visitors are locals, and accessing the museum is not so easy for out-of-towners who must travel by car or public transport, the design of the venue and exhibitions must incorporate more interactivity and intrigue to encourage locals to return and extend the duration of visitors' stays while using technological services to highlight the museum's unique features Through a recommendation from the Information Software Association, part of the Ministry of Economic Affairs' Industrial Bureau AI team, the Marine Museum commissioned Jugu Technology to resolve the issue of uninspiring venue attractions Preliminary interviews by Jugu Technology revealed that many visitors were attracted by the architectural design of the museum, notices posted on nearby walls, flags, or events being held the most interesting feature for visitors was the 3D ocean theater, indicating that content presented through audio-video and physical scenic methods was more engaging Seven major AI technologies lead to a boost in regional tourism at the Marine Museum Through the introduction of technology services, Jugu Technology designed the 48-hectare site with seven major services AI voice tours, treasure hunt puzzle games, AI exhibit interactive revitalization, AI space exhibition interactive experience, AI crowd control, Face AI interactive experience, and AI voice customer service system By utilizing AIoT and cloud technology, they made the exhibition more interesting, not only solving the issue of boring static viewings for children but also doubling the learning efficiency and dramatically improving public perception of the Marine Museum, thus increasing visitor intent and boosting regional tourism The National Museum of Marine Science and Technology introduced seven major technological application services including AI voice guide Jugu Technology aimed to improve the space optimization of the Marine Museum, using the special exhibition of coastal birds in northern Taiwan as a prototype, integrating 'face', 'limb', 'crowd' as three main axes to enhance functionality and assist in improving the museum's application of AI Practically, the Marine Museum and Jugu Technology selected the on-site special exhibits to avoid any installation of water and electricity works or pipelines in active exhibits, thereby maintaining the quality of the viewing experience Instead, they selected exhibits that were not yet open to introduce a series of technological services tailored to the unique characteristics of the exhibits In the coastal bird special exhibition inside the Marine Museum, initial construction discussions with the curators utilized Bella X1 for a welcoming interactive introduction at the exhibition entrance This was followed by an AI-powered smart guide in both Chinese and English using X1 for narration, coupled with a fun treasure hunting stamp-collecting activity - APP X1, allowing visitors to participate in challenges Subsequently, bird species within the bird exhibition were brought to life interactively using X1, and AR scenarios X1 were introduced into the exhibition space to add elements of fun and entertainment Finally, Face AI was used to interactively test facial expressions and score smiles The gorgeously transformed Marine Museum will become the best travel destination for families with children ImageMarine Museum FB Page The AIoT services introduced by the Marine Museum could be extended to various exhibition-type museums and even static art galleries in the future, tailored to the unique characteristics of different venues They could also be promoted through government projects and related plans, aiding in rural revitalization, making visits more than just sightseeing in rural areas, and breaking free from stereotypes associated with different venues The applications of these services are broad「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

2021-10-17
【2021 Application Example】 Savior of Wastewater Treatment: Combining Big Data and AI Technology Opens Another Horizon in the Environmental Industry

As water resources deplete and environmental protection needs increase, wastewater treatment plants have increasingly adopted AI technology to assist in monitoring and warning systems Zhongxin行's integration of big data and AI technology has opened up new possibilities in the environmental industry In the future, besides boosting the technological momentum of the wastewater treatment industry, it can also be promoted to other industries to foster technological and economic development Founded in year 1980 as Zhongxin Engineering later renamed to Zhongxin行 Company Limited, it is one of the largest and most technically equipped environmental companies in the domestic operation and maintenance field Zhongxin行's achievements in the operation and maintenance of sewer systems span across Taiwan, including science parks, industrial zones, international airports, schools, collective housing, national parks, and factories Introduction of AI systems in wastewater plants Precisely reduces medication addition times and lowers the risk of penalties for water quality violations At the wastewater treatment plant in Hsinchu Science Park, Zhongxin行 introduced the 'AOMBR Carbon Source and Aeration Intelligent Enhancement Control System Development,' which accurately predicts air volume control and reduces medication times, thus lowering the risk of hefty fines Zhongxin行 points out that with the vigorous development of advanced industries and increasingly strict effluent standards, a slight misalignment in equipment control can lead to major discrepancies in water quality In recent years, many wastewater treatment facilities have incorporated automatic control functions, yet onsite conditions often deviate slightly from theoretical expectations, causing situations where good treatment technologies must continuously adapt and adjust to achieve effective effluent water quality control 'The better the quality of the effluent, the greater the pressure on the operators This is the biggest pain point for Zhongxin行,' said a senior manager candidly Regular water quality testing and equipment maintenance ensure that effluent water stays below legal standards This means that operators need to be on top of equipment and water quality conditions daily If there are sudden anomalies in influent water quality or equipment malfunctions, linked issues can lead to pollution Therefore, besides performing regular maintenance and testing, it is critical to constantly monitor the dashboard to ensure system stability, consuming both manpower and mental energy Zhongxin行's on-site operators work 24-hour shifts, constantly monitoring effluent water quality Combined with laboratory water testing and analysis, if the wastewater treatment values do not meet requirements, they face both administrative and contractual fines from environmental agencies and granting authorities, which also create significant psychological pressure on the employees Over the years, Zhongxin行 has built up a vast database of water quality information and invaluable experience passed down among employees, allowing a comprehensive understanding of the entire system's operational characteristics Moreover, by analyzing equipment or water quality data for key signals, problems in the treatment units can be pinpointed If AI technology could be adopted to replace manual inspections of wastewater sources and generate pre-warning signals for systematic assessment, it would significantly alleviate the pressure on staff Response time reduced from 8 hours to 4 hours, saving half the time By implementing 'AOMBR Carbon Source and Aeration Intelligent Enhancement Control System Development,' Zhongxin行 utilizes accumulated wastewater data along with verbal recounts of operator experiences on-site With the support of AI technology and environmental engineering principles, key parameters in the biological treatment unit such as carbon source dosages and aeration can be effectively controlled Through the AI transformation of wastewater treatment, a balance is achieved among pollutant removal, microbial growth, equipment energy conservation, and operation economization, achieving rationalized control parameters Carbon source and aeration parameter adjustment steps range from data collection, model training to prediction verification In the long run, incorporating historical data calculations, AI can operate within known boundary conditions, not only recording past water quality and equipment operational characteristics far more accurately, but also developing predictive models to find optimal solutions that offer the best results in terms of chemical use, energy saving, reduced greenhouse gas emissions, and pollutant removal According to Zhongxin行's estimates, originally due to human parameter adjustments leading to errors, controlling response time would take about 8 hours With the introduction of AI technology, not only can measurement errors be reduced, but also the control response time can be shortened to 4 hours, saving around half the time This enhancement increases the turnover rate of personnel and effectively reduces the risks of penalties due to operator errors and thus markedly reducing the pressure on employees Dashboard digital display panel illustration「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

2021-10-11

Records of Application Example

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【2024 Application Example】 AI Assists the Red Cross for Smarter Emergency Response

More Preparation Less Loss The Taiwan Food Bank Association, a non-profit organization, collects donations daily from wholesalers, retailers, manufacturers, and even kind-hearted individuals across Taiwan They also rescue consumable materials that are about to be discarded, properly allocate and deliver to households in need, aiding local underprivileged populations When natural disasters such as earthquakes, landslides, mudslides, typhoons, floods, and droughts occur in Taiwan, the food bank's resources can be immediately deployed for disaster relief This field verification unit is the Nantou County Red Cross AssociationOne of the food bank locations, hereinafter referred to as the Nantou Red CrossIs responsible for tasks like pre-disaster supplies preparation and disaster relief material distribution, helping the government bear the responsibility of disaster relief and aid In Taiwan, various natural disasters have characteristics of different duration and spatial coverage, wide or narrow With the normalization of extreme weather, the scale and number of disasters are gradually increasing and becoming harder to predict The required amount and type of materials differ by disaster, and they must address the lifestyles of the affected areas, rescue needs, traffic conditions, geographical restrictions, and other factors for varied material allocation, facing numerous challenges Typhoon Kanu severely damaged transportation in Nantou mountain areas Nantou County Red Cross planned the mountainous route Puli gt Fazhi Elementary School gt Qin'ai Village gt Aowanda to deliver supplies Disasters happen repeatedly We need to be prepared at all times Effective disaster preparedness can mitigate the impact, including swift response to material needs in affected areas, aid distribution, and even psychological support, providing added security for life and property of those in disaster zones Lack of Timeliness in Disaster Information To improve the living conditions and address the lack of supplies in remote areas, the Taiwan Food Bank Association has partnered with the Nantou Red Cross and has successively established food bank points in Nantou City, Puli, and Ren'aiLixing, Ruiyan, XinyiWangmei, Tongfu, Shuili, Lugu and Caotun among others9establish food bank locations, providing supplies worth a certain amount per household every month6001000in New Taiwan Dollars However, many challenges still need to be overcome during natural disasters For example, when typhoons, earthquakes, and landslides occur, the information source for disaster relief dispatch systems relies on post-disaster reports The time lag between reporting, response, and execution prevents timely adjustment and distribution of 'disaster relief' supplies based on the needs of affected areas, affecting rescue efficiency due to lack of timely information The 'preparedness' supplies of the Nantou Red Crosssuch as dry food, water, instant noodles, etc,are recorded manually in terms of stock, expiration dates, and distribution,When a disaster occurs, there is a chance that 'preparedness' supplies have expired and cannot become 'disaster relief' supplies It’s also possible that both conditions mentioned above occur simultaneously, leading to a need for more time to reassign 'preparedness' supplies into usable 'disaster relief' materials On the other hand, upon receiving information about shortages in disaster areas, the supplies donated by the public often grossly differ from the actual needs of the disaster zone, leading to an excess of supplies The Process of Material Operations Before and After a Natural Disaster AIAnticipating Natural Disasters Reinforcing the Accuracy of Preparedness Material Dispatch Application API Technology connects to compute the state of the climate, the intensity of disaster rescues, prioritizing the main tasks of the Nantou Red Cross and the needed areas of search and rescue Coordinated with the existing heavy rain and typhoon simulation disaster training of the Nantou Red Cross, a 'Natural Disaster Emergency Preparedness Material Dispatch and Supplement Decision System' is establishedreferred to as the Emergency Preparedness Material System。 In material management, inventory data along with immediate supply data are entered into the Emergency Preparedness Material System for comparison and analysis, helping the Nantou Red Cross quickly recognize materials like cookiesdry food, beverages, frozen food, toilet paper, etc, and determining whether they should be 'preparedness' materials or regularly distributed materials Adding to this, information forecasting understands the potential disaster conditions in remote areas, facilitating food delivery, addressing both front-end food wastage and backend practical needs When a natural disaster occurs, it enables faster response and decision-making, completing material deployment, hence increasing the speed of material operation transition20。 AI Emergency Preparedness Material System Helps Rapidly Adapt Material Distribution Through the field verification of the Nantou Red CrossAIthe system, material management, and related applications are promoted to more emergency response organizations in different areas, while continuously improving the alert functions within the Emergency Preparedness Material System, strengthening the technological foundation for alerts, enhancing prediction accuracySystem immediacy, and optimizing the data collection and analysis process Simultaneously, it can collaborate with government agencies, meteorological departments, or other rescue teams to discuss integrating more data sources, establishing a mechanism to share resources and data promptly, sharing information in real-time, helping more emergency response organizations enhance their disaster response abilities, seizing the golden rescue time 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-12-12」

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【2024 Application Example】 CCTV Intelligent Video Search System

Search for a specific person, find someone with a suitcase entering the factory in Gao'an area Color features of the person and the object confirmed, person in blue and black top, suitcase in black color, throughCCTV the intelligent video search system, by setting object and color retrieval conditions, it can successfully locate three video clips containing the target subject This greatly aids operational staff in finding the target items, and through this system, search speed can far surpass manual effort6fold Pain Points The CSE-Kaohsiung Plant is densely equippedCCTVto monitor every corner of the plant area, but when an incidenthappens, it's impossible within a limited time throughCCTVvideo playback to find the incident, the implications and risks behind this are self-evident Many areas that are usually unmanned can easily become security blind spots Thus, how to monitor a vast plant area more intelligently and effectively is one of the crucial aspects of building a smart plant for the semiconductor industry The AES Plant in Kaohsiung covers a vast area, with many important sites requiring monitoring of personnel movements to ensure corporate secrets and employee safety 1 Automated production lines and warehouses In semiconductor enterprises’ automated production lines and warehouses, oftenAGV(Automated Guided VehicleAGVs automated guided vehicles travel at high speeds if plant personnel inadvertently enterAGVthe moving area and cannot issue a warning to the person, then the regrettable accidents that occur will be too late to reverse 2 Material and product storage areas Materials used in semiconductor-related processes are costly if areas storing materials or products are breached, there is a risk of loss of high-value materialsproducts 3 High-security areas Trade secrets relate to the core technological competitiveness of semiconductor-related enterprises if someone breaches the high-security areas, there is a risk of corporate secrets being leaked The safety of trade secrets has always been one of the most critical issues for semiconductor enterprises 4 Loading docks At AESLButthe dock area often has loading vehicles coming and going if someone intrudes into the dock area, there is a risk of vehicle collisions and accidents Additionally, goods awaiting shipment at the dock area could be stolen or potentially damaged from collisions, thus causing significant reputation and financial losses for the company, further leading to production and shipping inconvenience When an abnormal event occurs, how to quickly search for the relevant key footage from massive data Many important locations within the AES Kaohsiung Plant need to be equippedCCTVfor safety checks, butCCTVWith thousands to tens of thousands of cameras, manually searching through footage for an event requires laborious frame-by-frame review which is time-consuming and inefficient In light of advancements in computer vision, it's beneficial to utilizeAIto replace manual playback and searching Problem Scenario Object Detection The data source for object detection comprises two parts Open-source datasetsOIDv4and AES Kaohsiung PlantCCTVImage files For these files, search for usable data, specificallyOIDv4image files For these files, extract the defined nine major categories of objects for training data among them, two object categories, knives and gasoline barrels, were not found inOIDv4found usable data for knives and gasoline barrels, while the remaining seven categories of objects are available fromOIDv4useful training data found for the remaining seven categories of objects, all marked Regarding the Kaohsiung PlantCCTVimage files, select some frames Frame of the footage, and manually annotate the objects to be_detected for training and testing data Nine Major Objects Color Recognition The data source for color recognition is divided into two partsInternet image screenshots, and Kaohsiung PlantCCTVimage files Currently, no publicly available open-source datasets specifically for color recognition applications have been found, so images are collected from the web Search the web for images of the defined nine major object categories, save the images after separating the objects from the background, keeping only the object sections, and mark the images according to color Additionally, for the Kaohsiung PlantCCTVimage files, use the already-markedbounding boxextractCCTVimage files from variousFramesections of objects identified by color, and finally, visually identifiable images are marked according to color Each object category has its specific color definition, depending on the usual colors seen in these objects in real life Dynamic Ignore during Training FromOIDv4during the training of the object detection pilot model, since each image in this dataset is only marked for a single category, but the image may contain other desired detection categories unmarked For such cases, dynamic ignore techniques will be employed during training to avoid confusion Next, use the extracted training data from the Kaohsiung Plant toFine-Tuneenhance the detection rate of the object in specific designated areas Finally, select the model that computes the lowest loss value in the test set during the training process as the main object_detection model Dynamic Ignoring AIHelp You View CCTV The intelligent video search system primarily serves as an assistive system for searching surveillance footage, capable of speeding up the process of finding target events by setting search conditions for objects By simply defining the search conditions, you can quickly produce thumbnails of critical objects and playback for review, shortening the time required for manual case retrieval of the past The search time is quickly6doubled, allowing the front-end security unit to use this platform to strengthen the first line of risk management supervision and take timely preventive measures 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-12-12」

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【2024 Application Example】 [2023 Case Study] AI Steps into Philanthropy: Stylish Tech at Food Banks

Taiwan Food Bank AssociationHereinafter referred to as 'the Association'With the mission of providing food aid, poverty relief, reducing food waste, and building a hunger-free network, there are locations across Taiwan that gather donations from wholesalers, intermediaries, retailers, manufacturers, and even generous individuals These sites also rescue food that would otherwise be discarded, properly allocate and distribute it to needy households, thus aiding local vulnerable families55Food banks at various locations collect daily donations from wholesale stores, intermediaries, retailers, manufacturers, and even benevolent individuals from all over Taiwan These places also rescue about-to-be-discarded edible materials, properly sort them, and distribute to needy households, assisting local vulnerable populations However, each location requires significant human and volunteer resources to manage daily operations using traditional methods of communication with non-profit organizations and donors After receiving donations, these resources are then allocated to needy families or individuals There is a potential issue of uneven distribution of resources due to a lack of digitalization and integrated information management in these processes Warehouse and Transportation Centers and Mini Food Banks Distributing Resources to the Disadvantaged The location under validation by the Kaohsiung Charitable Organizations Association,Hereinafter referred to as 'Kaohsiung Charity' In109year6month24Officially inaugurated Taiwan's first 'Food Bank-Warehouse and Transportation Center' at a location measuring200square meters, enhancing the efficiency of food resource redistribution, proper storage, and management So far, nearly two hundred tons of vegetables and fruits have been saved, serving over a hundred organizations and benefiting over5thousand vulnerable households, and continues to serve19mini food banks, with planned completion across multiple districts in Kaohsiung, distributing food resources to over10ten thousand vulnerable families Kaohsiung Charity 'Food Bank-Warehouse and Transportation Center' in the Dasha Community Photo Source Kaohsiung Charitable Organizations Association Challenges in Labor and Food Resource Management Facing the needs of a large number of economically disadvantaged families, the management of the 'Food Bank-Warehouse and Transportation Center' is particularly critical During procurement, tasks such as sorting, purging, and bookkeeping must be performed, while during shipment, food resource needs suggested by social workers must be followed These activities rely on manual judgment and accumulated experience Many volunteers involved are elderly and have limited physical strength, making warehouse tasks physically demanding and recruitment challenging If a large batch of food resources arrives, space and manpower are consumed in sorting and inventory management, raising concerns about the effective use of resources and turnover rate This highlights the challenge of scaling up food bank services while lacking corresponding labor and material management systems At the same time, food bank resources come from various donations, thus they vary greatly in type, shelf life, standards, and quantity Volunteers at mini food banks, mostly also elderly, must handle multiple responsibilities such as case services, food resource management,resource allocation, and resource development Sometimes they must also explain and accept immediate, large quantities of specific resources, such as adults receiving baby formula 'Food Bank-Warehouse and Transportation Center' Resource Inventory Relies Entirely on Manual Labor Mini Food Bank Volunteers Handle Multiple Responsibilities Photo Source Taiwan Food Bank Association Reducing Scrap Resources60 Increasing Speed of Resource Transfer80 To enhance resource management and ensure effective use of materials, and to address personnel shortages, this field validation case has introduced 'Food Bank Warehouse Resource CollectionAITo advance resource management, ensure effective use of resources, and solve manpower shortages, this validation site has implemented an 'Automated Early Warning Needs Assessment System' for the food bank's warehouse resource gathering The first part involves building a classification model, setting up and collecting warehouse information at the site, andAItraining the model Past sitewarehouse information is collected and stored in a database, allowingAIfor preprocessing, classification, and other tasks At the same time, depending on the dependency conditions of the types of goods as features, algorithms are introduced for computation and modeling, and the data collected is used for retraining, ultimately validating the field and organizing data for the five most common types of goods into training and test datasets as required The second part involves constructing the classification model using AI techniques further use of reinforcement learning constructs the management mechanism for the food bank's warehouse, perfecting the classification of donated goodsRNNTechnical construction of classification models further use of reinforcement learning constructs food bank warehouse management mechanisms, making the classification of donated goods perfectlike white rice, instant drinks, noodles, instant noodles, and canned goodscan then be automatically assigned storage based on storage assignment principles AI Service System Process and Description Source Taiwan Food Bank Association AtAIUnder forecasts, it can optimize the speed of resource transfer and allocation, effectively and accurately match resource donations reducing the loss in the donation process, increase the accuracy of resource distribution, and improve the service rate—the successful donation rate—reducing the waste of resources due to incorrect items, and enabling instant monitoring of food resource stock, ensuring operators can respond quickly to needs, effectively providing resource assistance WithAIthe system's introduction and the establishment of data intelligence, it helps the operations of the warehouse and transportation center, allowing more time for the allocation of donated goods The introduction aims to accelerate the digital service rollout for social welfare organizations, thoroughly addressing the needs of the overall vulnerable segments of society Using the system for resource allocation and dispatching Photo Source Kaohsiung Charitable Organizations Association Following this field validation, it is possible to expand the system to other food bank service pointsAIThe system can also collaborate with more non-profit organizations, public welfare groups, and charitable organizations, expanding 'Food Bank Warehouse Resource CollectionAIAutomated Early Warning Demand Assessment System' application range such as medical supply distribution, helping more organizations manage and distribute more intelligently, reducing resource wastage, and enhancing social welfare 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-12-12」

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【2024 Application Example】 Testing Seat Contact Components AI Intelligent Flaw Detection

With rapid development in 5G, AIOT, automotive electronics, and other downstream sectors, the entire supply chain is expected to benefit from this consumer market As product demand momentum gradually increases, increasing production efficiency and reducing operational costs become the most important issues In order to meet the needs of customers for various packaging types, Yingwei Technology has been committed to developing highly customized test seats However, a resulting pain point is the inability to mass-produce and fully automate operations with machines some tasks still rely on manual execution In this project, the probe part of the test seat was outsourced in 2021, and under current and future large-scale demands, work hours, costs, supply, and quality are issues Yingwei faces The company achieves a defect detection rate of 9995, which seems high, but with an average inspector able to inspect 10,000 needles per day, there would still be 5 defective needles On a test seat that is only 3 cm wide with approximately 1,000 needles, just one defective needle could potentially lead to faulty testing at the customer end As the current operational mode relies on manual visual inspection, external factors such as fatigue or oversight of personnel, and subjective judgment by inspectors may lead to the outflow of defective products, which necessitates strict quality control of contact components We once sought to utilize optical inspections Rule-based for controlling the quality of appearances, but the metallic material of the contact components leads to light scattering, background noise interference, background scratches, and material issues that could result in misjudgments Therefore, we decided to look for AI technology service providers to solve our detection difficulties Developments of Dedicated AOI Line Scan Equipment To meet the needs for inspecting thousands to tens of thousands of probes within our company's IC test seats, traditional surface imaging and individual needle imaging would be too slow to achieve rapid inspection and labor-saving goals In response, the service provider proposed a trial with an AOI dedicated line scan module solution Utilizing a width of 63mm on the X-axis for reciprocal scanning of all probes on the test seat, the tests allowed for the simultaneous scanning of 8-9 probes, significantly enhancing the future detection efficiency of AOI machines This project will proceed with the aforementioned innovative Proof of Concept POC, focusing on the development of the line scanning equipment and performing imaging, learning, and training on both normal and abnormal probes provided by our company, with initial AI model training aimed at preliminary approval This project's customized line-scan imaging module Ideal future imaging result illustration A Single AI Technology Solution for MeasurementDetection Needs Unified use of AI DL CNN learning methods, instead of the current Rule-based system which necessitates defining each defect individually, to meet the needs for abrasion measurement and appearance defect detection of malfunctionsforeign objects When the same machine uses both measurement and detection technologies, not only does it increase costs, but it also affects the detection speed Hence, the service provider recommends the use of a line scan device for imaging Its resolution is sufficient for AI to simultaneously determine appearance defects and assess the condition of needle tip abrasion, as detailed below Line scan pixel imaging displaying needle tip abrasion conditions This AI detection technology meets both measurement and inspection needs for Yingwei, not only bringing more benefits to future probe testing but also introducing an innovative axis in AI technology Change the method of human inspection, enhance work efficiency and product quality After combining both hardware line scan and software AI model training approaches, we successfully ventured into new AOI detection applications Following the AI implementation POC, including the development and validation of a customized line scan module and an initial AI model, the plan is to officially develop the AOI machine next year and integrate it into the IC test seat production line Future Prospects Probe manufacturers upstream and downstream IC factory users both have needs for the AOI inspection machine upstream can ensure probe quality before leaving the factory, while downstream users can use this machine to regularly inspect the condition of numerous IC test seats in hand Given the future demands, the AOI machine is poised to have a significant positive impact on the IC testing industry in the foreseeable future 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-12-12」

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【2024 Application Example】 AI-Based PCBA Surface Defect Detection Improvements

With the introduction of theAOIAIWith the introduction of the system, we can improve product yield, reduce costs, and from a business perspective, increase customer trust and sales revenue Moreover, AIit has advantages that are difficult to imitate, unlike other equipment that can be bought with money, making it hard for our competitors to catch up with us Our company's current development We are committed toIOTsmart manufacturing our systems already include smart materials systems, environmental humidity control systems, anti-miscarriage systems, smart procurement computation systems, smart inventory systems, solder paste management systems, and production management systems We have asked other manufacturers about the possibility ofAIinspectingPCBAsurface defects, each hoping that we would purchase their equipment, but none were effective upon verification After discussing with IT service providers, we defined it asAOIAIa feasible operational model Tzuhong Technology has invested inAOIAIan inspection plan to checkSMTtext on components, solder joints, polarity, missing partsand usingAIto replace manual learningAOIand define the 'potentially defective' parts, enhancing productivity and reducing misjudgment rates Industry pain points Taiwan faces a severe labor shortage, especially those willing to perform visual inspections are few and typically older, increasing the frequency of missed inspections Thus, the most critical bottleneck in the pursuit of high-quality electronics has become post-production inspections Previous consumer products with undetected anomalies were acceptable within a certain ratio However, in the automotive industry today, undetected defects could lead to fatalities hence, the automotive industry has extremely high quality demands To survive in the automotive supply chain, we must address the issue of undetectable anomalies Moreover, as wages in Taiwan continue to rise, we can only endeavor toAIreplace traditional manpower with technology, otherwise, even if the anomaly leakage problem is resolved, the relatively high labor costs will still prevent competitiveness in this industry Application technology and explanation Initially,Figure 1,PCBUpon emerging,Reflowsystem, it will undergoAOIwill undergo inspection, dividing into 'suspected defective' and good products At this point, the 'suspected defective' portion accounts for20manual review for these20parts, further classifying the 'suspected defective' portion into good and defective products With We aim to leverageAItechnology, to shift from manual re-inspection of these20technology, we aim to replace manual review of 'suspected defective' products withAIand after review, the results still yield 'good' and 'suspected defective' products, but now 'suspected defective' comprises only3thus reducing the workload of Tzuhong's employees from20down to only3In theory, it isAOIIn theory, after inspection, it is further reviewed byAIbut it appears to go throughAOIonly, so we call this technologyA0IAIDetectionFigure 2。 The original AOI inspection process The operator will place the testPCBboard intoAOIthe inspection equipment, outputtingAOI information on defective products, then manually re-inspect one by one to determine if they are defective AOIAI inspection process The operator will place the testPCBboard intoAOIthe inspection equipment, outputtingAOIinformation on defective products after, then proceed byAIfirst performingAOIre-assessment of defective products, outputtingAIinformation on defective products afterward, then manually re-inspect one by one to determine if they are defective Process differences By introducing theAOIAIsystem, not only can we enhance the efficiency and yield of visual inspection personnel, we also have this timeAIexperience in system introduction, we will also incorporateAIthe use of big data into Tzuhong's existing smart manufacturing systems, further enhancing the performance of our smart manufacturing systems and reducing the pressure on employees Difference between pre and post-introduction Promotion strategy 1 Similar field diffusion allSMTmanufacturers face bottlenecks in inspections leading to shipment delays introducing this system can solve the severe labor shortage issue and enhance shipment speed and quality, allowing self-promotion to customers or through equipment dealers to cater to relevant needs 2 Cross-industry expansion plans negotiate withAOImanufacturers to directly integrateAIthe system intoAOItheir systems, enhancing their market competitiveness Profit strategy 1 In collaboration withAOImanufacturers, collect licensing fees 2 Direct sales toSMTthe manufacturing industryAIsystems 3 ProvideSMTmanufacturing industryAOIAIsystem subscription model「Translated content is generated by ChatGPT and is for reference only Translation date:2024-12-09」

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【2024 Application Example】 Using Plant Growth Chambers as an Example - Standardizing Electronic Device Procedures Based on Imaging

In recent years, global climate change and environmental issues have become increasingly severe, causing major impacts on agricultural production Traditional agriculture heavily relies on weather conditions, facing challenges such as unstable crop quality, plummeting yields, and difficult pest control Particularly in Taiwan, agricultural biotech companies and farmers have suffered continuous losses, creating an urgent need for innovative solutions Meanwhile, Taiwan's plant factory industry faces many challenges high equipment and labor costs, an incomplete industrial chain diminishing international competitiveness, and a lack of cooperation among enterprises, all of which limit industry development Additionally, COVID-19the pandemic has highlighted the importance of remote monitoring and management Traditional manual inspections and data collection methods no longer meet the needs of modern agricultural production These issues collectively underline the urgent need for smart agricultural solutions, driving companies like Taiwan's HaiBoTe to develop innovative projects integrating IoT, cloud computing, and artificial intelligence technologies HaiBoTe Cloud Data Integration and Analysis Platform Facing these challenges, the agricultural sector urgently needs a system that can precisely control growth environments, improve resource efficiency, enable remote monitoring, and facilitate intelligent management Existing plant factory equipment often requires complete replacement, with poor compatibility with older equipment, and sensors and camera systems may require different interfaces, making them inconvenient to use Therefore, there is a need for a flexible solution that can integrate various equipment and technologies, providing real-time monitoring and data analysis, and automatically adjusting environmental parameters based on plant growth conditions This demand exists not only in Taiwan but is also a global trend in the development of smart agriculture By incorporating artificial intelligence, more scientific evaluation standards can be established, optimizing production processes, improving yield and quality, while reducing energy consumption and environmental impact Additionally, such smart solutions can attract more young people to participate in agricultural production, promoting industry upgrading and sustainable development Overall, the demand for smart agricultural solutions stems from the urgent requirements to address climate change, enhance production efficiency, reduce costs, and achieve precise management, and this is exactly the problem companies like Taiwan's HaiBoTe are striving to solve Taiwan's plant factory operators are facing a series of severe challenges, which are gradually eroding their competitiveness and survival space Firstly, the high cost of equipment and operations is their biggest burden Each electricity bill feels like a heavy blow, forcing them to balance between ensuring product quality and controlling costs Secondly, the unpredictability brought by climate change has become their nightmare Sudden extreme weather events can destroy their carefully nurtured crops in a short time, causing massive economic losses What's worse, they find themselves increasingly at a disadvantage in international market competition In contrast, large overseas plant factories, with their advanced automation technology and well-organized supply chains, can produce stable-quality agricultural products at lower costs, putting unprecedented pressure on Taiwan's operators On the technical level, they also face numerous challenges Compatibility issues between new and old equipment often put them in a bind, encountering various technical obstacles when trying to integrate different systems Lack of precise data analysis and forecasting capabilities also makes it difficult for them to make production decisions and accurately determine the best growth conditions for each crop Existing monitoring systems provide data that is often disorganized, difficult to interpret and apply Human resource challenges are also severe, with young people generally lacking interest in agricultural work, making it difficult for them to recruit employees with modern agricultural skills Even existing employees often feel exhausted from tedious manual operations and monitoring tasks These problems are intertwined, creating a complex dilemma that leaves plant factory operators confused and anxious They urgently need a comprehensive solution that can enhance factory operational efficiency, reduce costs, and improve product competitiveness, helping them overcome difficulties and regain their footing in the fierce market competition In facing the various challenges of plant factory operators, Taiwan's HaiBoTe company has demonstrated exceptional technical innovation and a flexible customer-oriented development strategy They deeply understand that the solution must be able to seamlessly integrate existing equipment while providing highly intelligent management functions To this end, HaiBoTe's RD team adopted a modular design approach to develop a system that can be flexibly configuredIoTIoT system The core of this system is a smart control hub that can communicate with various sensors and actuators During development, HaiBoTe worked closely with customers, deeply understanding their specific needs and operational environments They even dispatched engineers onsite to observe the daily operations of the plant factories, ensuring that the developed system actually solves practical problems This in-depth cooperation not only helped HaiBoTe optimize their product design but also established a close relationship with customers, laying the foundation for subsequent continuous improvements HaiBoTe's innovation is not just reflected in hardware design but also in their developed intelligent software system This system integrates advanced machine learning algorithms, capable of precise forecasts and optimal control of plant growth conditions based on large amounts of historical data and real-time monitoring information To help customers overcome technical barriers, HaiBoTe designed an intuitive and easy-to-use user interface, which even non-technical operators can master easily Additionally, they provide comprehensive training and tech support services, ensuring customers can fully utilize all functions of the system When facing challenges, HaiBoTe's technical team can quickly identify problems through remote diagnostics and provide solutions In one incident, during a serious equipment failure emergency faced by a customer, HaiBoTe's engineers guided the customer through system remote access, successfully instructing them on repairs and avoiding potential massive losses This full-range service not only solves customers' immediate difficulties but also strengthens their confidence in intelligent management, driving the entire industry toward more efficient and sustainable development HaiBoTe's developed smart agriculture solution not only brought revolutionary changes to plant factories but also painted an encouraging picture for the future of the entire agricultural industry The excellence of this system is evident in several aspects firstly, it achieves precise control of the plant growth environment, significantly improving crop yield and quality stability Through advanced artificial intelligence algorithms, the system can forecast and adjust optimum growth conditions based on historical data and real-time monitoring information, ensuring each plant grows in the ideal environment Secondly, it significantly reduces energy consumption and operational costs, improving resource efficiency The intelligent management system optimizes water, electricity, and nutrient supply, reducing waste and lowering manpower costs Additionally, the system's modular design and strong compatibility allow it to seamlessly integrate various new and old equipment, providing a flexible solution for gradual upgrades of plant factories Most importantly, the system injects a sense of technology and modernity into agricultural production, helping to attract the younger generation to the field and injecting new vitality into the industry Looking ahead, HaiBoTe's smart agriculture system has broad application prospects and expansion potential In addition to plant factories, this system can also be applied to traditional greenhouse cultivation, urban agriculture, and even home gardening In the field of aquaculture, similar technology can be used to monitor and optimize the breeding environments for fish or shrimp In the food processing industry, similar intelligent monitoring and forecasting systems can be used to optimize production processes and enhance food safety Even in the pharmaceutical industry, this type of precise environmental management system could be applied to drug research and production processes To further promote this system, HaiBoTe could adopt a multifaceted strategy Firstly, they could collaborate with agricultural colleges and research institutions to establish demonstration bases, allowing more people to experience the benefits of smart agriculture firsthand Secondly, they could develop customized solutions tailored to different scales and types of agricultural production, expanding the applicability of their products Furthermore, they could raise awareness and acceptance of smart agriculture within the industry by hosting forums, online seminars, and sharing success stories Lastly, they could explore collaborations with government departments to integrate this system into policies supporting the modernization and sustainable development of agriculture, thereby promoting the widespread adoption of smart agriculture on a larger scale Through these efforts, HaiBoTe not only can expand its market share but also make a significant contribution to the sustainable development of global agriculture, truly realizing the vision of technology empowering agriculture 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-12-09」

【解決方案】搭上綠能商機 華鉬實業打造全釩液流電池儲能系統設備 長效儲能的最佳選擇
【2022 Application Example】 Taking advantage of green energy business opportunities, Hua Molybdenum Industry creates all-vanadium redox flow battery energy storage system equipment, the best choice for long-term energy storage

Green energy is the future trend and will surely lead to huge business opportunities in the future Wind power has been one of the green energy sources that have attracted global attention in recent years It will become an important force in my country's renewable energy and help Taiwan's power generation reach the goal of 20 by 2025 to improve Taiwan's energy independence As the number and power of domestic wind turbines wind turbines increases year by year, it is particularly important to ensure that the power storage equipment achieves safe, long-term performance, is not easily attenuated during charging and discharging, and is sustainable, low-carbon and environmentally friendly At the same time, the wind turbine equipment itself Health inspection, maintenance and repair have also become the focus of wind farm operators In order to meet the needs of wind farm customers, the green energy business unit of Hua Mo Industry has launched long-lasting energy storage all-vanadium redox flow battery electrolyte and wind turbine AI predictive operation and maintenance, providing 100 safety, long-term efficiency and reducing customer initial manufacturing costs cost-effective power energy storage equipment, and through AI predictive operation and maintenance services to help customers reduce power generation costs by 10 and save up to 30 in maintenance and warranty costs Hua Molybdenum Industry was established in 1998 The industry started by refining vanadium, molybdenum and rare metal elements and other products, and used them in high-end steel, professional chemicals and specialty chemicals industries, and vanadium is more like a steel-making Vitamins can increase the effectiveness of steelmaking Among them, vanadium and molybdenum related products are one of the company's main projects The company sees that the all-vanadium redox flow battery, which is 100 vanadium-based, will be a very promising mainstream green energy technology in terms of long-term energy storage in the future, and before 2010 The government has actively invited legal entities such as the Industrial Research Institute to conduct research on related component materials in solid-state batteries and all-vanadium batteries In addition, the Ministry of Economic Affairs expects renewable energy to account for 20 of power generation in 2025 and reach 15GW Based on the above Considering this, Hua Molybdenum Industry decided to devote all its efforts to research and invest in the technological development of self-developed all-vanadium redox flow battery electrolyte in 2017, in order to accelerate the compliance rate of renewable energy in 2025 Hua Molybdenum pointed out that "renewable energy power is relatively unstable, and Taiwan itself lacks lithium resources In lithium battery manufacturing, almost 80-90 of battery cells must rely on foreign procurement, and there is a lack of 100 domestic self-sufficient energy storage Resources and technology "Similarly, how does Taiwan overcome the problem of having no natural vanadium resources To this end, Hua Molybdenum Industry uses original technology to use waste catalysts from petrochemical industries such as CNPC refineries or Taishuo petrochemical processes Up to 10 of the vanadium ion content can be used to extract high-value vanadium resources, thereby producing Taiwan's 100 self-made all-vanadium redox flow battery electrolyte without being affected by resources, effectively achieving resource recycling Since 2017, Hua Molybdenum Industrial has successfully created all-vanadium flow electrolyte technology, and has successfully passed product verification by the Industrial Research Institute, the Nuclear Research Institute and many international manufacturers Taiwan’s power storage energy target is to reach 15GW in 2025 Its power distribution includes 500MW in Taipower’s automatic frequency regulation system, 500MW in E-dReg and 500MW in existing or newly built solar power plants For example, electricity consumption is mainly between 4 pm and 10 pm, which is the peak period for people's daily electricity consumption For this reason, the Energy Administration specifically requires Taipower to strengthen the upgrade of energy storage equipment, which has also driven the market's interest in all-vanadium redox flow batteries Energy storage system equipment is in high demand In addition, Taiwan's current total power reserve construction and contribution has not yet reached 100MW, and the gap from the 2025 target of 15GW of power storage is still more than 15 times Using all-vanadium redox flow batteries to successfully create 100 safe, low-carbon, environmentally friendly and long-lasting energy storage system equipment Compared with the short-term power storage of lithium batteries, the biggest advantage of all-vanadium redox flow batteries is that it is globally recognized as a long-term power reserve It can store energy for a long time up to 12 hours, which means that if it is charged for 12 hours, It can release power for 12 hours Compared with the electricity measurement method of general energy storage systems, which is daily electricity consumption power in kilowatts x time in hours, for all-vanadium redox flow batteries, power and hours are different Special design, the power is also called a stack, which is composed of four materials metal, polymer mold, carbon felt and graphite plate, and the power consumption time is calculated based on the amount of electrolyte in cubes Therefore, when the power electric push x the amount of electrolyte the daily electricity consumption of our all-vanadium redox flow battery for energy storage The product features of the all-vanadium redox flow battery energy storage system equipment include four major features safety, long-term performance, not easy to decay during charging and discharging, and sustainable, low-carbon and environmentally friendly The quality of the all-vanadium flow battery is 100 safe Since the electric energy is stored in the vanadium-containing electrolyte, it can avoid any flammable accidents caused by a fully charged energy storage system In terms of battery life, compared to the short battery life of lithium batteries, all-vanadium redox flow batteries can have a battery life of more than 20-25 years through changes in price Regarding the charge and discharge performance of energy storage, unlike lithium batteries which have a certain number of charge and discharge times 5000-600 times, there is no limit to the number of charge and discharge times of all-vanadium redox flow batteries Regarding zero carbon emissions, which is highly valued globally, unlike lithium batteries which have recycling issues, the electrolyte of the all-vanadium redox flow battery can be used permanently The material components of the stack are environmentally friendly and fully recyclable to create a truly sustainable and low-cost Carbon-friendly energy storage system Onshore wind turbine AI prediction smart operation and maintenance allows customers to reduce power generation costs by 10 and save maintenance and warranty costs by up to 30 Hua Molybdenum Industry not only improves the long-term power storage efficiency of renewable energy customers through all-vanadium redox flow battery energy storage system equipment and helps customers reduce initial purchase costs, but also uses AI smart operation and maintenance empirical calculations for offshore and onshore wind turbines Field demonstrations were drawn on Taipower's onshore wind farm, and we actively accumulated our own technical experience and energy in AI predictive operation and maintenance With the support of the AI HUB project of the Industrial Bureau of the Ministry of Economic Affairs, the cooperation site will focus on the Phase I wind farm of Taipower Corporation and provide smart operation data of wind turbines for more than 6 months for analysis The AI predictive operation and maintenance system for onshore wind turbines uses machine learning The main technology provider comes from ONYX Insight, a subsidiary of British Petroleum BP The company uses AI Hub analysis software technology to analyze the wind turbines faced by Taipower Pain point analysis, including power generation loss of road-based wind turbines and damage prediction of key components of land-based wind turbines such as gearboxes, pitch bearings under abnormal vibration three-dimensional vibration frequency or abnormal temperature, etc output Through this implementation, it can effectively help Taipower reduce power generation costs by 10, increase asset value by 12, and save up to 30 in maintenance and warranty costs In the past three years, ONYX Insight has successfully predicted and operated more than 20,000 offshore or onshore wind turbines around the world, accumulating extremely high AI model accuracy It is believed that the international partnership established with ONYX Insight will effectively guide and accelerate the green energy division of Hua Molybdenum Industry in its goal and layout to become an independent technology service provider for wind turbine AI predictive operation and maintenance Works with partner ONYX insight to provide customers with an AI predictive operation and maintenance system, including wind turbine power generation loss and damage prediction of key wind turbine components Building a solid foundation for domestic wind turbine operation and maintenance, using Taiwan as a base to expand to Southeast Asian wind farms The market output value of offshore wind turbine AI predictive operation and maintenance in Taiwan will exceed NT30 billion in the future, and the energy storage market has an output value of more than 100 billion US dollars globally In the future company vision, Hua Molybdenum Industrial hopes to become An independent technical service provider for vanadium flow battery electrolyte and wind turbine AI predictive operation and maintenance The long-term goal is to establish a local supply chain of vanadium flow battery electrolytes around the world by accumulating abundant technology and performance capital to supply industry needs nearby 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】佐翼科技無人機導入高爾夫球場域 可節省一半人力
【2022 Application Example】 Droxo Tech Applies Drones in Golf Courses to Reduce Manpower by Half

For most golf courses, the operations and management is a headache "Golf courses are selling turf and need to be properly taken care of," a golf course manager bluntly pointed out Facing the market pain points of labor shortage, aging population and high cost, the use of AI drones for pesticide spraying and pest control will reduce labor costs by more than half and greatly improve the overall operational efficiency At noon in early summer, an AI drone is slowly taking off at the Taipei Golf Club in Taoyuan Its main task is to test AI drone fertilizing and pesticide spraying on the golf course In fact, drones of Droxo Tech, the company performing this task, are widely used for fertilization, pesticide spraying, and pest and disease control for rice, bananas, and tea trees For golf courses with turfs that often cover tens to hundreds of hectares, AI drones are needed to assist in turf maintenance Data collection, development of pesticide spraying AI models, and multispectral image analysis and testing will be carried out in the current stage In the future, large-scale technology implementation and verification will be carried out to set an example for applying drones to golf courses Using AI drones to fertilize and spray pesticides can reduce the manpower required by half The traditional way of maintaining the turf in golf courses is to carry spray buckets or drive spraying vehicles to spray areas one by one "Domestic golf courses began to plant ultra-dwarf Bermuda grass in 2001 This grass species prefers a cool climate and is not suitable for Taiwan's hot and humid weather" Droxo Techrsquos CEO further pointed out that to prevent turf from pests and diseases, pesticide spraying is necessary For an 18-hole golf course, it is equivalent to spraying pesticides once a week, and the T-ground and fairways are sprayed every two months For golf courses, spraying pesticides is time-consuming and labor-intensive It is important to note that large-scale spraying will increase the risk of personnel poisoning and increase the amount of pesticide used Benefits of applying agricultural drones to golf courses According to Droxo Techrsquos research, golf course pests include Spodoptera litura, which comes out at night to look for food, so pesticide spraying must be carried out in the evening According to the traditional method, pesticide spraying requires two vehicles and three personnel for a total of 45 hours If AI drones are used for fertilizing and pesticide spraying, it only takes one operator to spray 08 hectares of land in 20 minutes, saving about two-thirds of the manpower and reducing operating costs by about 30 Using AI drones to fertilize and spray pesticides on golf courses can reduce the manpower required by half In addition to the significant benefits of using agricultural drones for golf course turf maintenance, Droxo Tech also specially introduced AI multispectral image recognition for NDVI Normalized Difference Vegetation Index analysis "The so-called multispectral is to direct light with different wavelengths on the turf, and the reflected images are collected for analysis" Droxo Tech CEO Liu continued to explain that each plant absorbs light with different wavelengths, so multispectral imaging can determine the growth status of grass species At the same time, combined with AI image recognition, the distribution of pests and diseases can be accurately detected, and the amount of pesticide used is determined on this basis Cross-domain collaboration to build a multi-source turf image databasenbsp Using AI multispectral image recognition technology, Droxo Tech will collect visible light, multispectral, thermal images, and hyperspectral images to establish a multi-source turf image database to fully understand the growth cycle of Bermuda grass Droxo Tech has accumulated rich experience in agricultural AI drone pesticide spraying , but there are still many problems that need to be overcome to implement AI solutions in golf courses For example, it is necessary to establish a new pesticide spraying model and test flight methods, especially the application of multispectral image recognition PoC is not difficult, but actual implementation requires more test evidence, repeated inferences, and collaboration with plant experts This part must rely on the cross-domain integration of legal entities such as the Institute for Information Technology III, gathering more fields for verification, and creating a paradigm before it can be more widely adopted by golf courses There are not many international cases on the application of AI drones in golf courses During the verification process, it is not yet known whether it can be quickly copied to the next golf course However, Droxo Tech CEO Liu believes that through cross-domain collaboration, clearly defining the problems and listing them one by one, supply and demand parties can reach a consensus, propose solutions to each problem, and seek cooperation with internal and external resources Only then will we be able to gradually achieve the goal of making golf courses smarter and smoothly assist the industry with transformation Zuoyi Technology's CEO, Liu Junlin 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】優式AI智能割草機器人 搶攻高爾夫藍海市場
【2022 Application Example】 USRROBOT's AI Lawn Mowing Robot Enters the Blue Ocean of Golf Market

An AI smart lawn mowing robot, resembling a vacuum robot, shuttles back and forth on the 30-hectare golf course lawn for weeding This robot, independently developed and designed by Taiwanese, is equipped with the world's first electronic fencing positioning technology which utilizes high-precision GPS integrated with cloud AI computation to determine the most efficient mowing paths, targeting the lucrative blue ocean market of golf courses This AI lawn mowing robot was developed by USRROBOT, a Taiwanese startup established in 2019 Chao-Cheng Chen, the president of USRROBOT, once served as the executive vice president of one of the top five ODM tech companies in Taiwan, and specializes in software and hardware integration When he served as the chairman of the Service Robot Alliance, he knew that the service robot industry was bound grow rapidly due to declining birth rates and the growingly severe labor shortage New demand - The horticulture market is large and the has rigid demand "To develop the core technology of service robots, we must find rigid demand Looking at European and American countries, there is a shortage of labor, but demand for horticulture has increased, and there has been a long-term shortage of 7-10 of horticultural workers" Under this strong "rigid demand," Chao-Cheng Chen established USRROBOT, and the company's first product is the AI lawn mowing robot In terms of overseas markets, the United States is the world's largest horticulture market, accounting for 30-40 of the global output value It is estimated that there are about 1 million horticulture workers, but they have been experiencing a labor shortage of 7-10 in recent years and have not been able to improve the situation The main reasons for labor shortage are Aging population and gardening is a labor-intensive job, so young people don't want to do it Unlike in Taiwan, European and American countries attach great importance to lawn maintenance and have expressly stipulated in the law that heavy fines will be imposed for failing to mow the lawn Therefore, the AI lawn mowing robot has considerable market development potential The introduction of AI multi-device collaborative mowing sensor technology is expected to reduce the burden of staff maintaining the golf course The AI lawn mowing robot developed by USRROBOT is currently in its second generation Domestic universities and well-known art museums are using the latest model M1, and it is also being used by some world-renowned high-tech companies and well-known universities in the United States The company is currently involved in negotiations for subsequent business cooperation USRROBOT stated that the professional RTK system currently used can reduce the original GPS positioning error from tens of meters to about 2 centimeters, allowing the robot to move accurately outdoors After setting the boundaries, it can be easily operated using the app New application - Implementation in golf courses solves the problem of labor aging and shortage Chao-Cheng Chen further explained that the National Land Surveying and Mapping Center is a RTK service provider RTK provides the error reference map of the positioning point USRROBOT can access the positioning error value of a specific position through 4G Internet access The AI algorithm of USRROBOT reduces the general 10-20 m error of GPS to 2 cm After positioning, USRROBOT then uses six-axis accelerator positioning, gyroscopes, and wheel differential sensing devices for software and hardware integration Only by matching the wheel's movement pattern and the terrain can accurate mowing path planning be achieved The AI lawn mowing robot, which is 62 cm wide, 84 cm long, 46 cm high, and weighs only 25 kg, can set the mowing boundaries in the cloud It can avoid pools and sand pits through settings, using AI algorithms to automatically calculate the optimal path It is able to mow approximately 150 ping of grass in one hour The battery can be used continuously for more than 6 hours The battery life is currently the highest in the world In addition to general gardening companies, with the assistance of the AI project team of the Industrial Development Bureau, Ministry of Economic Affairs, USRROBOT's AI lawn mowing robot has been applied to golf course lawn mowing A well-known golf course located in Taiping District, Taichung City currently has a staff of 5 people who are responsible for the lawn, planting maintenance, and other landscape maintenance of the entire 30-hectare course However, the average age of staff is as high as 55 years old, and the golf course has been unable to recruit new staff members for a long time In view of the aging staff and the shortage of manpower, the golf course hopes to mitigate the impact with AI technology, and is therefore using AI multi-device collaborative mowing sensor technology, in hopes of reducing the burden of staff maintaining the golf course New challenges - Expert systems are needed to overcome difficulties with different grass species "This AI lawn mowing robot has low noise, low pollution, low labor costs, and is waterproof and anti-theft In the lawn mowing process, it can identify and avoid obstacles through ultrasonic sensors while maintaining mowing quality, maintaining aesthetic and consistent grass length" Chao-Cheng Chen went on to say that the most important part about golf courses is that the grass pattern should be beautiful and free from diseases and pests Based on the site survey, golf courses are mainly divided into three major areas green, fairway and rough There is no problem using the current mowing robot to mow the rough area, and it can overcome slopes within 20 degreesThe short grass in the fairway area may only be two centimeters long, and the grass types are also different, so the cutterhead design needs to be modifiedAs for the grass in the green area, the grass must be mowed close to the ground and maintained in a consistent direction because it affects the putting speed Many factors will affect the green index, and this part requires more research and testing The AI lawn mowing robot can identify and avoid obstacles through ultrasonic sensors while maintaining mowing quality The AI smart lawn mowing robot has a built-in camera that can be used to detect the health condition of the lawn Chao-Cheng Chen said that in the future, an expert system will also be introduced for early determination of whether there are diseases, pests in the lawn or whether there is sufficient moisture, and provide lawn health data analysis to customers, so that they can take preventive and response measures sooner to reduce disaster losses Chao-Cheng Chen, who is also a good golfer himself, said that golf has developed well in Taiwan However, due to weather factors, such as rainy and humid climate and typhoons, Taiwan's golf courses have harder soil and more potholes compared with top tier golf courses overseas If AI lawn mowing robots are to be widely introduced into golf courses, there are still many difficulties that must be overcome However, Taiwan's difficult terrain creates a good testing ground Once Taiwan can overcome the many problems and successfully introduce the robot, it will be able to expand to overseas markets and seize new market opportunities in a blue ocean Chao-Cheng Chen, President of USRROBOT nbsp

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