Special Cases

21
2021.1
【2021 Application Example】 AI Complements the Disruption of Traditional Industry Experience: Production Forecast Analysis in Plastic Recycling Process

As the number of veteran craftsmen in traditional industries diminishes In Taiwan, SMEs have always played a central role in Taiwan's industry, accompanying Taiwan through various 'economic miracles' periods But as time progresses, the old masters gradually became elderly craftsmen Coupled with the phenomenon of fewer children and changes in the overall industrial structure, fewer and fewer of the new generation are willing to enter traditional industries Now, it can be observed that the main combination on most SMEs' operational fields is formed by 'elder craftsmen' together with 'foreign workers' These experienced craftsmen, who act as living dictionaries of field experience, suffer from a lack of successors to continue the tradition, leading to a growing difficulty in sustaining on-site experience transfer in traditional industries The limits of traditional hands-on process optimization are in sight Located in Tainan Baoan Industrial District, 'Tangxian Company' was established in 1972, initially manufacturing high-quality weaving equipment It possesses the capability to manufacture machinery, and in recent years it has actively developed environmentally friendly plastic recycling equipment in response to international green energy, recycling, and environmental protection demands Ultimately, they have successfully developed low energy consumption, low waste, high purity, and high output recycling granulators with a sleek and efficient machine design supplemented by advanced intelligent control technology Tangxian Company's self-developed plastic recycling granulator equipment However, in the production process of plastic recycling, when faced with hundreds of material types and dozens of process temperatures, speed settings, what is faced is thousands of possible parameter combinations Previously, the adjustment of various production process conditions was reliant on the on-site staff the experience of the craftsmen Thus, during the transition of production of different incoming materials such as PET, PP, PE, a significant amount of raw materials would be wasted during the trial phase The professional information gap in traditional industries Tangxian Company recognizes the importance of data In the past, although process parameters were recorded, due to a lack of data capabilities at the time, it was primarily in paper form, manually written down by the operating staff, accumulating a large amount of paper data However, this also meant a lack of scientifically accurate and detailed information available for real-time reference and adjustment Process parameters logbook, records the state of about a dozen machines and production figures hourly In quality control as well, due to a lack of control over the quality of output and monitoring and feedback mechanisms for unit time production, it becomes difficult to predict the profit conditions of each batch Production management can only estimate and average cost and productivity changes over the process from the outcomes, without being able to objectively and timely restore the production conditions to reasonableness or make clearer adjustments when facing quality abnormalities Site reality left image shows recycled scraps right image shows pellet production Taiwanese manufacturers possess strong machinery manufacturing capabilities, and many modern machines now have data capabilities, recording real-time status and information via IoT But is the infrastructure of the factory's on-site and information systems ready yet When the Old Master Meets AI With government referral, Tangxian Company partnered with a Taiwanese data science company, working together to integrate AI services and optimize internal processes using AI They started with a medium-sized plastic recycling production line within the factory as a trial field After establishing a successful benchmark, this model was expanded to larger plastic recycling machinery within the factory to continue verification and application Initially, both parties converted the past handwritten paper data into digital format using OCR supplemented by manual correction Tangxian Company also worked with the supplier of the human-machine interface of the machinery to integrate the control panel and parameter data into the factory's database, allowing real-time monitoring of machine status and eliminating the complexities and potential errors of manual transcription Panel of plastic recycling granulation machine, showing current process temperatures, speeds, and power usage Meanwhile, the Taiwanese data science company further modeled dozens of parameter data through AI, conducting scenario analysis to simulate various production possibilities under environmental parameters and material inputs, identifying key characteristic parameters and providing parameter adjustment recommendations to decrease costs during the trial phase Applying data analysis to traditional industry machinery processes After the old master receives the raw materials, they only need to enter the relevant material characteristic parameters, and the system automatically generates recommended process parameters After small adjustments by the old master, they proceed with the trial production of the material, effectively reducing the waste of materials, water, electricity, and manpower caused by incorrect attempts Moreover, Tangxian Company has proactively deployed the concept of 'production pedigree' in the plastic recycling process, allowing the batch's raw materials and process parameters to be accessed by scanning a QRCode Production and sales pedigree of plastic recycling pelletizing Taiwan's SMEs have strong machinery capabilities, just waiting for the 'east wind' of data From industrial revolutions 20 to 30, even 40, many Taiwanese SMEs face challenges in transitions not just in upgrading machinery, but after investing in modern equipment and generating data, they do not know how to utilize it effectively It is impractical for these manufacturers to develop a specialized data analysis department on their own meanwhile, Taiwan also has many innovative teams with strong software capabilities in AI and data analysis, possessing the technology but lacking the field and data Therefore, if the traditional industries of Taiwan could be fully integrated with the innovative teams in AI and data analysis, it would not only address the current challenges of manpower and experience transfer faced by traditional industries but also advance Taiwan's development and application of AI significantly「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

2021-01-21
【2021 Application Example】 AI Analysis Cloud Service Platform for Remote Sensing Big Data Enables the Smooth Application of Satellite Remote Sensing Images

Although satellite remote sensing images can make all surface objects visible, it still requires a lot of time and manpower to be truly applied to the industry In order to effectively solve the problems that customers face in digesting huge amounts of image data and eliminate technical obstacles for cross-domain users to process satellite remote sensing images, ThinkTron has developed an "AI Analysis Cloud Service Platform for Remote Sensing Big Data" as a new beginning for cross-domain AI applications for spatial information In recent years, in response to the impact of industrial globalization, Taiwan's agriculture has continued to transition towards technology-based and higher quality, improving the yield and quality of crops by solving problems, such as microclimate impacts and pest and disease control The demand of agriculture on images has expanded endlessly to accurately grasp the growing environment of crops In the early years when UAVs unmanned aerial vehicles were not yet popular, manual field surveys were the most basic but most labor-intensive work With the emergence of UAV drones, aerial photography operations might not be difficult, but the range that can be photographed is limited Furthermore, surveying expertise is required to accurately capture spatial information At this time, the use of satellite remote sensing data may break away from the past imagination of using image data Taiwan Space Agency TASA ODC data warehouse services In the past ten years, with the breakthrough of modern satellite remote sensing application technology, Digital Earth has become a new trend in global data collection Countries have developed data cube image storage technology, and the development of smart agriculture has become one of the largest image users Determining planting distribution is the first step in understanding crop yields Free satellite remote sensing images, powerful data warehousing support, and the team's robust image recognition technology are important supports for accelerating agricultural transformation Using satellite remote sensing image data can accelerate the development of smart agriculture However, in the past, it was difficult to extract large-area crop distribution through satellite remote sensing images, not to mention the cost If you wanted to use free information, you had to visit all websites of international space agencies, look through the wide variety of satellite specifications, and carefully evaluate the sensor specifications, image resolution, and revisit cycle After finding suitable images, you had to look at them one by one to filter the ones you need Next is downloading dozens of images that are often several hundreds of Megabytes MB each, which might exceed the capacity of your computer Also, after overcoming image access and preparing data, you must then start to confirm the downloaded image products and which bands you want, because the image you see is not just an image file jpg or png, but rather complex multi-spectral information, attribute fields and coordinate information It takes a lot of effort just to confirm the correct information Facing GIS software packages with complex functions is the start of another trouble The complex image pre-processing process and the inflexible machine learning package greatly reduce the efficiency of analyzing data After finally getting the results of crop identification, you might find that the best time for using map information may have already passed The above-mentioned complex and time-consuming satellite image processing problems are precisely the pain points of the market ThinkTron expanded from traditional machine learning to modern deep learning applications, and developed an "AI Analysis Cloud Service Platform for Remote Sensing Big Data" under the GeoAI framework, breaking through the constraints of details in the spatial information for customers Differences between the process before and after introducing the AI analysis cloud service platform ThinkTron said that Taiwan's ODC Open Data Cube system has been completed and began providing services after years of efforts from the Taiwan Space Agency TASA, formally becoming aligned with international trends The powerful warehousing technology allows users to easily capture and use image data of a specific time and spatial range according to their needs The warehouse stores multiple satellite image resources from international space agencies, including the ESA's Sentinel-1 one image every 6 days, Sentinel-2 one image every 6 days, USGS's Landsat-7 one image every 16 days, Landsat-8 one image every 16 days, and the domestic Formosat-2 one image every day and Formosat-5 one image every 2 days ThinkTron develops satellite image recognition tools based on Python Breaking free from the limitations of GIS Geographic Information System software packages, ThinkTron integrated GDAL Geospatial Data Abstraction Library based on Python, and considered computing efficiency and parallel processing when developing all tools required for satellite image processing and image recognition modeling, including coordinate system and data format conversion, grid and vector data interaction, and data intra-difference and normalization All of the tools are designed with AI applications in mind, and some commonly used tools are packaged into an open source package under the name TronGisPy to benefit the technical community ThinkTron utilized the team's understanding of satellite remote sensing images and the collected tagged data crop distribution maps to preset the image recognition modeling process, the required training data specifications, and dataset definitions This is imported into the machine learning LightGBM or deep learning CNN framework that was completed in advance, and the entire training process to be performed in the Web GIS interface, providing users with partial flexibility to freely filter images, confirm spatial and temporal ranges, select models, and adjust hyperparameters In addition to the operation of training models, it also provides historical models to output identification results, and finally displays the identification results of crop distribution on the Web GIS map In fact, agriculture is not the only industry that needs satellite remote sensing applications AI applications of spatial information have also appeared in various fields as companies in different industries aim to enhance their global competitiveness For example, surveying and mapping companies that have a large amount of map data can use the AI analysis cloud service platform to store map data while also accelerating the efficiency of digital mapping Under the severe global climate change and the risk of strong earthquakes, there is a wide variety industrial insurance, agricultural insurance, financial insurance, or disaster insurance are all inseparable from spatial information The use of remote sensing image recognition to understand insurance targets has long been an international trend AI Analysis Cloud Service Architecture for Remote Sensing Big Data

2021-11-28
【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】 HRT Technology Improves Production Efficiency by 20% Through AOI Detection of Defects in VCSEL Packaging

In 2017, the launch of the iPhone X made 3D sensor technology used in Face ID highly popular, which drove the development of VCSEL, a core component in the 3D sensor module In the detection of defects in incoming packaged VCSEL, the use of AI inference models can solve the industry's issue with low yield and improve reliability to 95 VCSEL technology currently can be used in many applications and various end consumer markets, including robots, mobile devices, surveillance, drones, and ARVR VCSELs are a good solution in applications that require high-speed modulation capabilities, such as cameras and biometrics VCSEL technology has a wide range ofnbsp applications, including in drones Pictured Zoyi Technology's Agricultural Drone VCSEL technology has a wide range of applications, AI technology assists in defect detection HRT Technology stated that the packaged VCSEL market is also facing strong price competition from competitors, and needs to further reduce costs and enhance product competitiveness One of the key problems is the replacement of glass lens with epoxy resin lens The production of traditional glass lenses has high yield, but the cost is higher than that of epoxy resin lenses Due to the cutting process of epoxy resin, the side wall of cutting lines can easily have rough edges, causing it to be oversized The release of stress caused by heat during the mounting process will directly cause the optical lens to break HRT Technology pointed out that the incoming inspection of VCSEL epoxy resin lenses is very important Under the constraints of packaging space, the space for fitting the package and optical lens is limited Moreover, the optical lenses will be confined to a metal frame If the dimensional tolerances are properly controlled, stress release due to heat during mounting can easily cause the optical lens to break, resulting in a yield loss of up to 10 in the VCSEL package reliability verification, resulting in an increase in production costs In order to solve the problems above, HRT Technology hopes to use AI to monitor the size and appearance defects of epoxy resin components in the VCSEL epoxy resin lens incoming stage, verifying whether their dimensions meet specifications, whether the cutting edges are smooth, and whether there are any defects in their appearance Since traditional incoming material inspection requires a rough visual inspection by humans to distinguish the quality The problem of image collection needs to be solved first to successfully collect image data Therefore, HRT Technology first developed an Automated Optical Inspection AOI device, which includes X, Y, Z three-axis motion, high-resolution cameras, and related control software to automatically record images After collecting the image data, opencv aligns the test image and a normal image to determine differences between the two images, and then pixel mapping is used to compare the pixel area to complete initial screening Manual labeling is carried out according to the image classification above, including samples that are normal, have defects in appearance, or have different shape characteristics, and then algorithm training and verification is carried out Residual neural network ResNet or other related algorithms are used for deep learning to identify the quality of lenses Implementation of AOI inspection improves production efficiency by 20 and above Comparing the differences before and after the implementation of AI image inspection, the incoming VCSEL lens inspection before implementation only involved manual inspection of the appearance The lens is packaged on the VCSEL package that has completed die bonding After passing the general light up test, the final reliability test high temperature reflow is performed Failed samples go into the rework process However, after the implementation of AOI inspection, it can screen defective lenses sooner and reduce the cost of subsequent materials input, it can also reduce the need for rework due to failure, improving yield to 95 and above in the reliability verification This is expected to help companies reduce production costs by 10 and increase production efficiency by 20 and above The difference before and after implementing AI image detection HRT Technology pointed out that this technology is an AI application developed based on tiny images It uses deep learning algorithms to identify defects in the images The trained network automatically classifies image data to predetermined categories Defect categories can be determined through reference images, so cumbersome programming is not required In the industrial machine vision environment, deep learning is mainly used for classification tasks in applications, such as inspection of industrial products or identification of parts In the future, with the development of IoT wearable devices and the trend of energy saving, the size of optoelectronic components will continue to shrink This technology can be applied to the detection of defects in the appearance of other tiny optoelectronic components in the future

2021-12-05

Records of Application Example

【導入案例】動態車牌辨識系統 省時省力方便管理
【2020 Application Example】 Dynamic License Plate Recognition System: Time-Saving and Convenient for Management

Jiude Songyi Company, with 40 years in motor-related equipment manufacturing, introduced a dynamic license plate recognition system with an accuracy rate of 989 to effectively monitor vehicles entering and exiting the factory area The system uses AI technology, making vehicle management both time-efficient and effortless License plate recognition systems are a fundamental application of intelligent image analysis Using cameras to capture images of license plates, the system then analyzes and processes these images to recognize the plates Kangqiao Technology, established in 2008 by a team of LED developers and software engineers, specializes in LED product applications, developed license plate recognition and Etag integrated systems, primarily for domestic and international public works projects Recently, the III AI Team collaborated with the Taiwan Energy Technology Service Industry Development Association to explore real-world applications of license plate recognition technology They identified three major issues faced by Jiude Songyi Company at this stage 1 Currently, the company gate has no barrier machine or other control equipment Vehicle entry and exit rely entirely on manual control and recording If no personnel are present, vehicle movements cannot be controlled 2 When issues arise, the existing surveillance system has to slowly search for data to locate the problematic vehicle, which is very time-consuming and inconvenient 3 When the footage is found, it is often difficult to clearly identify the license plate, and even if found, it is not possible to verify the vehicle owner Solving Three Major Problems, Providing Four Major Functions After understanding the actual needs of the enterprise, according to the license plate recognition system architecture established by Kangqiao Technology, real-world validation was conducted on-site, with monitoring computers set up in the control room Kangqiao Technology License Plate Recognition System Architecture After installation, the main functionalities of the license plate recognition system are as follows 1 When vehicles enter or exit, high-resolution smart cameras can identify license plates and capture images, recording the license number and vehicle status 2 When file retrieval is needed, vehicle data can be searched by time or license plate information, allowing quick access to the required video files, saving considerable time 3 The use of high-resolution smart cameras significantly improves image quality, which helps in clear identification in case of incidents 4 With registered license plate data, a blacklist and whitelist database can be set up, facilitating the management by security personnel The advantage of license plate recognition is that it fully automates vehicle entry and exit control, reducing labor costs The software helps to prevent misuse of license plates and eliminates the issues of remote control, induction buckle loss, and borrowing by unauthorized persons Vehicles can enter and exit without using a remote control or rolling down the window The long-distance license plate recognition allows gates to open while the vehicle is still moving, eliminating the waiting time for parking Kangqiao Technology License Plate Recognition System Setup in the Management Room The III AI Team states continually collaborating with relevant associations, from identifying corporate needs, setting topics, linking teams, introducing real-world validations, to systematically assisting enterprises in need to adopt AI technology and solve industrial problems, aiming for the AI transformation of industries In the future, it will continue to help enterprises harness technology tools to overcome business challenges「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【導入案例】核電廠「不玩了」 安全管理智慧化更重要
【2020 Application Example】 Nuclear Power Plant Calling It Quits: Elevating Importance of Smart Safety Management

Plant safety is a crucial aspect of industrial security Currently, many surveillance cameras are used in conjunction with manual monitoring by security personnel to provide information However, manual monitoring has its limitations Implementing an AI system to assist in detecting abnormal behaviors and facial recognition can significantly aid security personnel by covering blind spots in manual monitoring Located in Shimen District, New Taipei City, the Jinshan Nuclear Power Plant is nestled between mountains and the sea, boasting picturesque scenery However, this first nuclear power plant in Taiwan is entering its decommissioning phase and will soon become a part of history With the decommissioning process underway, numerous external contractors will be entering and exiting the complex, complicating access management The need for continual safety monitoring of external construction to ensure nuclear safety is critical Additionally, although the Lungmen Nuclear Power Plant is currently mothballed, it still contains sensitive areas and requires a reduction in staff presence, thus prompting an urgent demand for smarter safety management With assistance from the Taiwan Nuclear Level Industrial Development Association, the AI team at the Institute for Information Industry aims to tackle the issues of safety and occupational safety at the Jinshan Nuclear Power Plant with minimal staffing Based on interviews, the technology needs identified for AI implementation at the plant include personnel access control and safety monitoring of personnel and the plant area Facial Recognition AI Solves Two Major Challenges Personnel Access Control and Plant Safety Monitoring For personnel access control, a facial recognition system is deployed at the nuclear power plant Utilizing the uniqueness of human faces and AI's high recognition rate, the effectiveness of the plant's personnel access control is enhanced In terms of personnel operations and plant safety, an abnormal behavior detection system is also deployed This system utilizes AI to recognize abnormal or dangerous behaviors from the postures of individuals captured by surveillance cameras, promptly providing feedback to safety personnel for action Selected by the Institute for Information Industry, the solution from Wantech Intelligent Sensing abbreviated as Wantech focuses on developing facial and posture recognition functionalities After several discussions with Wantech, Google's Facenet and Posenet algorithms were chosen for implementation Facenet, requiring only 128 dimensions per face image, achieves optimal performance with just a few photos, making it particularly suitable for building industrial-grade facial recognition systems Posenet, used for motion detection, transforms data via a Data Processing Unit DPU into a format suitable for machine learning algorithms—Support Vector Machine SVM—for binary classification of human postures into falling or not falling categories Utilizing Visual Pages for Clear Management Interfaces The user interfaces for both systems are implemented using Python's web framework Flask, which provides web services adaptable across different operating systems, achieving a cross-platform purpose The Glasses App is developed using Unity to access web data In recent years, advancements in AI technology have increasingly incorporated facial recognition into safety management The unique characteristics of facial features eliminate the risks associated with RFID forgery and offer higher accuracy compared to other biometric recognitions fingerprints, voiceprints, complete objectivity devoid of personal bias, easy system setup and maintenance, and fully automated operations requiring no additional manpower Undoubtedly, incorporating facial recognition into safety management systems can significantly enhance the safety factor of the plant while reducing management complexities Body Posture Recognition Operating in the Laboratory Taiwan has four nuclear power plants, bearing significant management costs Continued implementation of AI technology solutions can not only reduce labor costs but also significantly enhance the effectiveness of safety management「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【導入案例】AI導入營建業 減少工安意外 安心看得見
【2020 Application Example】 AI Implementation in Construction Industry Reduces Workplace Accidents: Safety Visibility Enhanced

The construction industry is Taiwan's leading industry, supporting the architecture, decoration, and repair sectors However, the high incidence of occupational accidents in this sector is a major concern for both employers and workers The introduction of AI for equipment recognition in the construction industry reassures companies and protects workers, creating a win-win situation According to the Ministry of Labor's 2017 statistics on occupational injuries, the average rate of occupational injuries per thousand workers across various industries is 2773 However, the construction industry tops the list with a rate of 10036, which is 36 times the average and categorizes it as a high-risk group for occupational injuries Proactive early warning measures can significantly reduce the rate of workplace accidents In light of this, the Institute for Information Industry, under the mandate of the Ministry of Economic Affairs' Industrial Development Bureau, has initiated an AI project that prioritizes the implementation of AI technology in the construction industry Selecting well-known construction firms in Taiwan, the project applies Canon's safety helmet proper wearing recognition solution to reduce occupational accident rates Smart Recognition of Safety Helmet Wearing A Solution for Employers Senior executives in the construction industry emphasize that compared to other industries, construction workers face higher health and safety risks primarily at construction sites Many risks arise from the workers not properly wearing or using personal protective equipment, such as safety helmets Relying solely on human supervision for ensuring safety gear compliance is time-consuming and often ineffective Implementing AI technology for smart monitoring on construction sites can save corporate resources while ensuring worker safety, achieving dual benefits Indeed, to protect workers during operations, construction plants require workers to properly wear safety helmets Wearing a helmet does not imply it is worn correctly To prevent the helmet from falling off during operations, it is necessary to securely fasten the chin strap directly under the chin after putting on the helmet 工地用安全帽正確佩戴方法 At construction sites, many foreign workers often do not follow proper safety protocols, such as not wearing safety helmets correctly If supervisory personnel were to be assigned, it would entail excessive use of human resources With the assistance of the information strategy team, major construction companies have adopted Canon's image recognition technology To determine the optimal placement of image recognition cameras, both teams first conduct site surveys and collect various types of safety helmets used on-site Subsequently, standard cameras are installed at entry points of construction sites and work zones to capture footage of the site personnel This footage helps Canon develop models for correctly and incorrectly worn helmets, aiding the image recognition software in its learning phase Canon's engineers regularly visit the site to retrieve footage, and once the image recognition software achieves a certain accuracy level, the image recognition cameras are then installed at the construction site 佳能工地安全帽資料搜集攝影機設置 Improving Recognition Accuracy for Concrete Implementation of Workplace Safety Currently, no local technology can accurately recognize the proper wearing of safety helmets Therefore, Canon has developed and trained its own recognition software The complex environment at the actual installation sites can impact the effectiveness of recognition In the future, machine learning will significantly enhance the overall recognition accuracy, ensuring that safety measures involving the wearing of safety helmets are concretely implemented While AI recognition technology is introduced in the construction industry's safety domain, it can also be integrated with mobile devices for early warning In practice, once a camera captures recognition data and processes it, the results can be pushed immediately to specific individuals such as safety managers on their mobile phones, tablets, or even linked to access control systems If a worker is detected without a properly worn safety helmet, relevant personnel can be alerted promptly Access can be denied until the worker correctly wears the safety helmet, offering considerable potential for future applications「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【導入案例】AI點點名 掌握長者進出 解決日照中心人力荒
【2020 Application Example】 AI Roll Call to Monitor Elderly Entry/Exit and Solve Staffing Shortages in Daycare Centers

The silver storm is coming Taiwan will enter an 'ultra-aged society' by 2026 Daycare centers across Taiwan are facing a 'staffing shortage,' with AI facial recognition introduced to monitor entries and exits, making reliance on AI for roll calls a comforting solution for day centers How serious is the aging population issue in Taiwan Let's consider a figure by 2018, the proportion of the elderly population aged 65 and above in Taiwan had already exceeded 14, officially entering an aged society Moreover, according to estimates by the National Development Council, Taiwan will enter an 'ultra-aged society' where the elderly population exceeds 20 by 2026, aging even faster than Japan The council also predicts that by 2065, Taiwan's elderly population will exceed 40, implying that every 12 working individuals will need to support one elderly person Faced with a massive elderly population, daycare centers are bound to experience severe staffing shortages The informatization of Taiwan’s long-term care institutions is insufficient and urgently needs AI technology to address the staffing crisis Ian Wen, the vice-president of the Taiwan Long-Term Care Association National Federation, which has 800 members, states that unlike the medical industry continuously incorporating cutting-edge technology, Taiwan's long-term care sector has not benefited from Taiwan's world-class technological advances Small and medium-sized institutions depend heavily on manual labor With the introduction of AI technology to solve transformation problems, there can be substantial benefits for both the institutions and the elderly Responding to the industry's urgent calls, the Ministry of Economic Affairs' Industrial Development Bureau and the Institute for Information Industry have been actively seeking solutions Initially, the Institute focused on needs, collaborating with the Long-term Care Association to visit multiple institutions and understand their issues Most venues claimed that controlling exact attendance of elderly residents daily is necessary to comply with the long-term care subsidies Just before 7 AM, care recipients come in wheelchairs, with canes, driven by family members at the back door, and some who are supposed to arrive yet remain unseen The chaos at the entrance -- elders, families, and caregivers talking and bustling around -- makes it impossible to even hear each other By the time the roster call finishes, breakfast bought early in the morning is still sitting on the table This is a typical morning for caregivers at the daycare centers AI roll calls help solve current issues of staffing shortage and information inaccuracy Daycare centers commonly face issues with seniors having irregular attendance and check-in times Current operations only manage these through manual registration With multiple entrances, large and multi-level premises, and complex traffic including caregivers, administrative staff, elders, their families, and visitors, it's challenging to effectively manage them Additionally, manual roll calls can lead to errors during busy hours and even create misunderstandings regarding subsidy counts, causing problems for both the Ministry of Health and Welfare and the providers Thus, industry stakeholders are keen on using AI-enhanced devices to help healthcare staff, reduce manual documentation, and free up administrative staff time to assist more elderly care recipients With the mediational and advisory support from the Information Industry Institute, security monitoring providers Qizhuo Technology and Hangte Electronics have integrated facial recognition technology into long-term care institutions By setting up facial recognition devices at entrances and creating an innovative long-term leasing business model, they not only solve budget and staffing issues for small and medium-sized institutions but also help electronic device providers find suitable field verification sites, effectively solving problems for both supply and demand sides Qizhuo Technology solution implementation, left shows discussions with venue staff about installation details, right shows the detection screen Hangte Electronics solution recognition screen Facial recognition technology in long-term care progresses rapidly, capable of replacing the manual roll call systems and assisting caregivers during nighttime inspections, ensuring the whereabouts of elderly residents The application within daycare centers is expected to continue expanding「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【導入案例】防範於未然 跌倒及危險區域偵測維護長者安全
【2020 Application Example】 Proactive Prevention: Fall and Hazardous Area Detection to Safeguard Elderly Safety

We all know that falls are a major concern for the elderly Once a fall occurs, it could lead to injuries or even life-threatening consequences that may be irreversible such as remaining undiscovered after a fall To counteract this, early warning through AI technology for fall and hazardous area detection can greatly enhance the safety of the elderly According to international statistics, the fall incidence rate among people aged 65 and above is 30-40 This implies that out of ten elderly individuals, 3 to 4 might experience a fall annually Indeed, falls are the most common cause of injury among the elderly Additionally, detections and warnings of risky behaviors in hazardous areas, such as scalds or slipping in the bathroom, can significantly reduce injury risks for elderly individuals To ensure that the elderly lead a long and healthy life with minimized accidental injuries, the AI team from the Institute for Information Industry actively collaborates with long-term care centers and AI device manufacturers Their goal is to meet the most urgent needs of the elderly, addressing areas where care centers, due to limited staff and resources, can't provide comprehensive care Accidents and injuries are among the top ten causes of death The establishment of an early warning system is urgently needed Statistics show that among the top ten causes of death for people over 65, in both Taiwan and the United States, accident injuries such as falls are included Post-fall, elderly individuals often experience a decline in mobility and quality of life In addition to physical injuries like fractures and bleeding, psychological impacts can also occur, causing them to avoid going out and leading to further physical decline Thus, preventing falls and providing immediate warnings to minimize fall-related injuries are crucial issues in elderly care Currently, the Institute for Information Industry's team is guiding collaborations between elderly care providers and AI device manufacturers The focus includes developing AI technologies for elderly facial recognition, along with technologies for detecting falls and hazardous behaviors, which are now being implemented in three elderly care facilities across northern, central, and southern regions for practical validation Collaboration between smart surveillance manufacturers and facilities effectively enhances recognition rates Mr Wu Jiachen, Vice President of Chiztech, stated that their smart surveillance technologies, including fall detection, facial recognition, and electronic fencing, have been well-developed but require practical validation sites to accumulate big data Introduced by the Institute for Information Industry, demonstrations in long-term care settings significantly improve recognition rates, greatly benefiting future applications Chiztech's developed fall detection solution Moreover, Mr Guo Hongda, Vice President of Hantech Electronics, who has been involved in safety surveillance for over 30 years, pointed out that the greatest key to successful smart surveillance lies in data accumulation and smart image analysis Establishing an AI database for various applications is crucial For instance, detected wandering can initially indicate whether the person's movement suggests discomfort or an anomaly, allowing immediate alerts to the monitoring center If an elderly person approaches potentially dangerous areas like a water dispenser or water heater, service personnel can be notified quickly to assist and prevent possible accidents, thus effectively facilitating early warning measures Hantech Electronics' developed fall detection solution With the assistance of the National Federation of Taiwan Long-Term Care Association, which has about 800 members, approximately 100 small and medium-sized care institutions have expressed interest in adopting the technology Once these facilities are fully equipped, they will become the seedbeds for advancing the AI transformation of Taiwan's eldercare sector「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【導入案例】從一顆包子窺看如何應用AI減少50報廢率,為冷凍食品提升60生產效能
【2020 Application Example】 Peeking into a Baozi to See How AI Reduces Scrap Rates by 50% and Boosts Production Efficiency by 60% for Frozen Foods

From production line to dining table, who oversees the hygiene management of what we eat In recent years, there has been a continuous stream of news reports concerning food safety, such as repackaging expired goods, and poisoning incidents at Hong Rui Zhen It's clear that people are increasingly concerned about the hygiene of their food However, due to various quality control methods in food processing, there are inherent risks The World Health Organization WHO has pointed out that unsafe food and water cause physical harm to 2 million people each year Hence, international markets demand that food processing companies must establish a traceability system for products This is why major domestic food processors also aim to set up a production traceability system to quickly trace back to problematic raw materials and initiate recall and destruction of problematic food Visible assurance, implementing production transparency A major domestic food manufacturer producing frozen food and instant meals has expanded its market presence to North America, New Zealand, Japan, etc They are also at the forefront in promoting food management domestically, having obtained certifications such as HACCP, ISO22000, ISO14001 Since food production is labor-intensive, it is prone to quality impacts caused by worker fatigue Additionally, the production lines often have unclear records of production quantities, processes, and timing This obscurity in traceability makes it difficult to track production information when defects occur, leading to food safety management gaps that result in the scrapping of entire batches To address this, the Production Development Center at National Sun Yat-sen University utilized its advisory resources to help the food manufacturer tackle food safety management challenges, planning the use of AI technology to collect production data and establish anti-fraud and traceability for food production Intelligent manufacturing boosts food safety Although the level of automation is not high in the processing of bakery products, the food plant in this case is keen to enhance the automation of its production lines and introduce smart manufacturing For businesses, a traceability system not only helps establish brand image and increase product and brand value, but also gives consumers peace of mind due to the transparency of production lines Therefore, the Production Development Center at National Sun Yat-sen University matched AI technology service providers, Hong Ge Technology, in the first phase to plan the introduction of data collection devices to link food work orders information, reducing human operational omissions and capturing real-time production information through dashboards to ensure the consistency of production stage information potentially affected by human factors Schematic for intelligent production line planning The second phase involves using deep learning during the dough fermentation stage to calculate size and volume, analyze the relationship between temperature, humidity, fermentation time, and product volume, and assess whether to introduce AOI foreign object detection after freezing as a second quality control step Schematic of AI-integrated quality control for finished products Food processing ID card, launching the AI-era of food safety tracing In Taiwan, the understanding and acceptance of production history by consumers is gradually improving From the supply of raw materials, processing, production, to distribution and sales, it is necessary to have complete control and provide transparent information Publicly disclosing the production history not only increases trust between enterprises and consumers, but also aligns Taiwan's food safety environment with international standards In 2020, the Production Development Center at National Sun Yat-sen University will assist enterprises with the adoption of advanced AI technology, documenting the entire data process from industry to dining table and supervising food production processes to successfully implement product tracing, prevention of adulteration, and the establishment of high standards for products, thus advancing food processing products to international standards「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【導入案例】AI建構最佳塗裝模型,降低電磁鋼片廢材檢驗成本,每年可省200萬
【2020 Application Example】 AI constructs the best coating model to reduce the inspection cost of scrap electrical steel sheets, saving NT$2 million per year

Surface treatment applications face rising costs and talent gaps The development of metal surface treatment technology affects the quality of aerospace, automobile, machinery, home appliance, communications, and fastener products sold domestically and exported At the same time, it plays a pivotal role in domestic smart machinery, national defense, and circular economy in the " 52 Industrial Innovation Plan" According to 2018 survey statistics, the output value of the metal surface treatment industry reached NT1515 billion, an increase of 36 compared to 2017 However, metal surface treatment is a labor-intensive, energy-consuming, and pollution-intensive industry It has long suffered from a shortage of professional and technical talent, and the tightening of environmental regulations has caused processing costs to continue to rise As a result, the industry is facing a crisis of survival and a crisis of competition from international high-value supply chains Manual quality control faces market challenges, while the coating process has found new opportunities Overseas markets currently account for 70 of the revenue of a domestic steel plate coating plant It expanded into the automotive steel, diverse supply chain, and various special steel product markets in 2016 It is imperative to improve the quality of surface treatment through innovative technologies, in order to seize international markets In the continuous steel plate coating process, the price difference between finished steel plate products and defective products is about 10 times Manual inspection is used in the current stage During the production process, 10 m needs to be cut from each steel coil and becomes fixed inspection waste, incurring a significant amount of cost for waste materials, and also delaying production At the same time, the instability in manual inspection quality also makes production quality unstable The Southern Taiwan Industry Promotion Center STIPC utilized the guidance capabilities it accumulated over a decade in Southern Taiwan, and matched the steel plate coating plantrsquos pain point with an AI optical measurement technology service provider This reduced the cost of consumables used in steel plate inspection, and reduce errors caused by fatigue during manual inspection Stabilizing steel plate coating quality with optical measurement technology In order to control the quality of the coating process, image recognition must be used to identify product yield General measurement technology requires contact to detect the thickness of coating Therefore, the STIPC match the plant with an AI optical measurement technology service provider to assist in the development of a non-contact optical measuring instrument, record coating data, and then compare the data to obtain the best process parameters Illustration of 3D non-contact measuring instrument testing Presentation of measuring instrument data Rapid scanning through AOI achieves non-contact measurement It can quickly scan the profile and overall dimensions of the object being measured without directly making contact with the product or damaging the surface of the steel plate It can immediately control coating thickness and quality of steel plates without increasing cost We hope to calculate data of the process environment and design the product abnormality warning range, so that it can be used to make the process smarter In the future, this solution will further detect surface defects and color differences of finished steel plates to reduce the proportion of discarded material, solve the problem of the gap in professional and technical talent, and improve product yields Schematic diagram of non-contact measuring instrument Establish an AI coating model to create world-class steel plate supply standards With the guidance of the STIPC in 2020, the steel plate coating plant accelerated the application of advanced process technology and established quantified indicators of surface treatment process quality standards, which will help domestic surface treatment companies produce high-quality electrical steel sheets, and is expected to increase the product price by 2 In addition, it can also assist companies in the industry obtain heat treatment certifications for high-value aerospace, electric vehicle, fastener, and aerospace products, increasing the industryrsquos added value through innovative thinking, and continuing to lead the metal industry forward

【導入案例】LEO國眾電腦AI行動視力智慧箱 定點視力檢測關懷行動不便長者
【2020 Application Example】 LEO National Computers AI Mobile Vision Smart Box - Fixed-Point Vision Testing for Mobility-Impaired Elders

When it comes to vision testing, most people think of visiting an ophthalmologist, but this can be inconvenient for those living in rural areas or for older elders Mobile vision testing could easily solve this issue LEO National Computers has launched the 'AI Mobile Vision Smart Box', aiming to provide vision tests deep into rural and community areas to solve the medical disparity between urban and rural areas The 'AI Mobile Vision Smart Box' resolves urban-rural medical disparities Taiwan has officially entered an aging society According to health insurance data, the rate of cataract changes in individuals over 70 is as high as 90 In the 29 districts of New Taipei City, up to 13 districts lack ophthalmology clinics Some areas due to their remoteness and low population density have no doctors willing to provide services, highlighting the significant disparity in medical resources LEO National Computers, founded by Dr Jian Ming-Ren in 1985, aims to tackle the issue of insufficient medical staff by using AI technology, thus cooperating with the team from the Service System Technology Center of the Industrial Technology Research Institute Since 2014, the Industrial Technology Research Institute has been involved in the integration platform for fundus cameras, collecting millions of fundus photographs from teaching hospitals and clinics, from which they selected about several hundred thousand suitable data entries Professional ophthalmologists review, annotate, and grade each photo into one of four different disease condition levels, which are then fed into artificial intelligence for training Following this, new functionalities were gradually developed according to medical field needs, offering a fully automated self-service fundus photography service This case was facilitated by technology transfer coaching from the Industrial Technology Research Institute, with National Computers providing integrated service operation and customer service The Industrial Technology Research Institute was responsible for system integration and platform maintenance Additionally, the field service was provided by a university optical ophthalmology department offering testing locations and services, promoting to diabetes care networks, optometric centers, opticians, ophthalmology clinics, and community service points for fundus camera testing The 'AI Mobile Vision Smart Box' was also officially showcased at the AI HUB conference, aiming to enhance the provision of vision tests in rural and community areas in the future, addressing the issue of insufficient medical resources in rural areas The 'AI Mobile Vision Smart Box' integrates ophthalmic handheld instruments like slit lamps, tonometers, and fundus cameras with a mobile vision testing system into a single suitcase, capable of providing 2 to 5 vision tests 'AI Mobile Vision Smart Box' instantly uploads data The usage of the 'AI Mobile Vision Smart Box' is quite simple, with a built-in local area network allowing for the immediate uploading of scanned images and data The 'AI Mobile Vision Smart Box' combines ophthalmic handheld instruments such as slit lamps, tonometers, and fundus cameras with a mobile vision testing system into a single suitcase, offering 2 to 5 types of vision testing functions The design is patient-centered, providing identity verification, test data retrieval, an automatic retina comparison system, and medical record file management, especially enabling individual patient file management Additionally, with the built-in local wireless network and smart gateway, it facilitates the immediate upload of all testing data, including images and measurements Currently, the 'AI Mobile Vision Smart Box' has collaborated with major hospitals in Taipei and family medicine clinics in New Taipei City, with plans to expand further into rural areas 'AI Mobile Vision Smart Box' apart from being used in fixed locations such as medical institutions and health check centers, its portability allows optometrists or nurses to carry it to ordinary homes or rural areas to perform eye examinations, enhancing the convenience and mobility of medical staff, and allowing vision testing to move out of hospitals into communities Currently, the 'AI Mobile Vision Smart Box' is collaborating with major hospitals in Taipei and family medicine clinics in New Taipei City, hoping to bring eye examinations closer to mobility-impaired elders in rural and community areas, aiming to achieve early detection and treatment「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【導入案例】公廁如何靠IoT及雲端科技變乾淨、解決7成客訴,並且提昇120倍效率
【2019 Application Example】 How can public restrooms rely on IoT and cloud technology to become cleaner, solve 70% of customer complaints, and increase efficiency by 120 times?

IoT smart restroom A revolution of clean, power-saving, and convenient new smart restrooms Six sensors are used to detect toilet paper, hand soap level, water leakage, odor, people flow, and toilet usage conditions, and combined with NBIoT transmission, cloud system, and LINE robot It greatly reduces customer complaints and improves the efficiency of replenishing consumables in restrooms Coupled with real-time notifications, it can prevent illegal smoking in restrooms and improve safety Users will no longer face the dilemma of wet, dirty, smelly restrooms, or toilet paper running out, greatly upgrading their experience What is your impression when you walk into a public restroom in a popular tourist area No hand soap No toilet paper Or even a dirty, smelly, and leaking restroom The IoT big data smart restroom solution of the Institute for Information Technology III solves all inconveniences of restrooms all at once According to statistics of the Environmental Protection Administration EPA, Executive Yuan, there were more than 43,000 public restrooms registered and managed in Taiwan as of the end of September 2019, but the entire EPA only had over 34,000 people Cleaning and managing such a large number of sites is obviously not an easy task Coupled with the inevitable arrival of an aging society, the number and quality of personnel cleaning restrooms will inevitably encounter unprecedented bottlenecks The introduction of effective service processes and assistance of technologies has become a major issue that must be faced sooner or later The IoT smart restroom service solution demonstrated by the III at over 20 restrooms around Taiwan may provide a good direction for us to solve this problem Overwhelming number of customer complaints, four major problems, and three solutions of the III In 2016, when the MRT Songshan Station, which is connected to the train station, was officially opened, the public restrooms that were already at full capacity resulted in serious customer complaints due to the overwhelming use Songshan Train Station, which originally had an average daily passenger volume of only 40,000, was already near a bottleneck in service capacity After the connected MRT Songshan Station was opened, the number of passengers increased to 70,000 The restrooms that were already near full capacity were completely unable to cope with the additional passenger volume after the MRT station was opened Cao Xueqin once wrote a classic line that touched people's hearts in the novel "A Dream of Red Mansions" "When a wall is about to collapse, everybody gives it a shove" may be able to describe this phenomenon The toilet paper and hand soap in each restroom was never replenished in time, the sinks were dirty, and the toilets could never be cleaned in time There was an overwhelming number of customer complaints about the restrooms as a result In addition, the public restrooms of Songshan Train Station are closer to the main passageways of passengers than the public toilets of MRT Songshan Station At this point Songshan Train Station had to face and solve this problem Since Songshan Train Station has worked with the III for a long period of time, it commissioned the III to help solve this troublesome problem Edison has a famous saying "If I find 10,000 ways something won't work, I haven't failed I am not discouraged, because every wrong attempt discarded is another step forward" The first thing that the III needs to do is conduct pain point analysis and think about the underlying problem After reviewing customer complaints and discussing and analyzing them with front-line cleaning service companies, the III found four problems and three solutions The four problems are Toilet paper and hand soap are not promptly replenished, sinks are damp, and the space has a foul smell The three solutions correspond to these four problems respectively 1 Delicacy management of consumables such as toilet paper and hand soap 2 Digitize the key performance indicators KPI in the service process, such as the dampness of the sink, or the odor concentration in the space 3 Use new Internet of Things IoT technology to implement the first two solutions, and assist big data and cloud technology in achieving efficient site cleaning management "Technology features and RampD process" The combination of six key sensors with IoT cloud motherboard and big data, thoroughly resolving 70 of customer complaints and increasing efficiency by 120 times I Delicacy management of consumables To achieve delicacy management of toilet paper and hand soap, the first step is to develop sensors to detect these two consumables Starting in 2017, the III began to design the first infrared toilet paper detection module The module mainly uses the physical characteristics of toilet paper usage habits for detection Under normal use, toilet paper is placed on an iron drum holder, and its thickness slowly becomes thinner as it is used This module requires the combination of a position sensitive detector PSD , infrared emitting diode IRED, and signal processing circuit SPC to effectively determine the length of toilet paper with accuracy reaching one decimal place When the detection module was first developed, there were no designs that could be referenced, so sensor selection, circuit board designing and planning, sensor programming, and even the light-cured 3D printed casing design were all completed in the III However, despite overcoming all the difficulties in designing and producing the toilet paper sensor, there was no way to foresee that fixing the sensor in place would be the most difficult problem The III team shared with us ldquoAt first, we used hot melt adhesive to fix it in place, but cleaning personnel needed to open and close it every time they replenished toilet paper The sensor fell due to too much vibration and not being firmly fixed in place The worst situation was in the women's restroom When a female passenger was using the toilet, the sensor was not properly fixed in place and fell Donrsquot you think this sensor looks like a pinhole camera If something like this suddenly falls on the ground in the women's toilet, how bad do you think it will be laughs Fortunately, our superiors supported us, and we continued to develop the technology until we were able to successfully fix the sensor firmly in place Otherwise, this project would have been aborted a long time ago" After the toilet paper detection module was launched, an inspection of toilet paper usage that once took cleaning personnel 15-20 minutes to complete now only takes 10 seconds by opening the app This greatly improved efficiency by 120 times Now that the consumption of toilet paper has been solved, the next problem is detection when hand soap is at a low level Unlike toilet paper, the amount refilled each time for hand soap isn't always the same Because the design philosophy was to use the lowest cost and most stable components to complete this function to facilitate future scaling, a common Hall sensor was chosen It was mounted on the exterior of the soap dispenser to achieve the detection of low soap levels The principle is actually very simple Once the liquid level is lower than a certain percentage, the Hall effect sensor can sense the change in voltage from electromagnetic induction of the liquid level The sensor sends a signal to the back-end cloud server, and then the server then sends a message to cleaning personnel the same as the toilet paper sensor II Digitization of key performance indicators KPIs in service processes If the sink is wet, water will often seep onto the floor In addition, the bottom of passengersrsquoshoes will inevitably carry dust, so the floor will become dirty when they step on the wet floor Visually, this will give people a sense that the ldquorestroom is dirty" However, it is impossible to have cleaning personnel on duty in the restroom at all times, so a special sensor is needed to detect this situation The III uses the resistance characteristics of thin film resistors When there is liquid on the surface of the thin film resistor, it will lower the overall resistance value and further change related values of the analog signal output In this way, moisture can be detected by simply laying thin film resistors on surfaces that often become wet For example, next to the windowsill or on the sink However, since sensors are relatively expensive and scratches will damage the performance of the sensors, this moisture detection sensor is only used in specific public restrooms Apart from looking dirty, if a foul smell comes from a public restroom, people will think it is dirty even if it looks bright and clean However, odor detection is not that easy to solve At first, we searched all kinds of sensors in Taiwan and overseas to find this "electronic nose" We eventually found a suitable MEMS chip in the product line of a major Japanese manufacturer that specializes in the production of gas sensors The III started from breadboard testing, circuit design drawings, to outsourced chip production, taking nearly six months to complete the design of the sensor Furthermore, in the process of developing smart nbsprestrooms, we also received requests to develop other modules, such as people flow detection and usage detection During the development process, we found that users may accidentally close the door of some accessible toilets after use and forget to turn off the lights, so it seems as if the toilet has been occupied all day long However, people who really need to the toilets are blocked outside the door of accessible toilets that are actually vacant This problem was relatively simple The engineer found a ready-made people flow sensor module and installed it under the sink, and the problem was easily solved In addition, environmental protection and carbon reduction requirements are hard to meet for some remote public restrooms, such as Tri-Mountain Lishan National Scenic Area Due to the remote location, responsible personnel must turn on the lights every day at work and turn off the lights when they get off work Sometimes not many tourists use the public restroom all day long, but all the lights and equipment are still on all day long, which is a waste of electricity Generally, commercially available sensors are very dull and will turn off the power as soon as the set time of 30 seconds to 10 minutes is up Such a sensor may be adequate at home when only one person uses the toilet However, in a restroom that can easily reach 60 ping or above, several detectors will be needed to work together to ensure whether there are still users in the restroom This is another problem without a commercially available solution The III had no choice but to integrate multiple sensors and develop algorithms on the MCU to solve this problem III The introduction of new IoT, cloud, big data, and 5G NBIoT technologies On the path of innovation, there are always difficulties waiting for engineers to overcome In the process of solving problems as they come, we also refined the solution step by step, making it cheaper, more reliable, and more convenient After the sensors described above were completed, the system gradually generated new problems for the III to solve For example, the barrier of user habits, power consumption issues, cost issues, etc The app was changed to a LINE group robot to become more aligned with user habits When the public restroom of about 60 ping at Songshan Train Station was completed for the first time in 2017, MCU and WIFI communication were used to monitor and transmit data to the server around the clock After the system determines an abnormality, it uses the mobile app developed by the III to notify cleaning personnel This design seems to be impregnable at first glance However, the average age of on-site cleaning personnel is over 50 years old, no one used the dedicated app, and front-line personnel often deleted the program within a few days of use There is a whole set of sensors monitoring, but no cleaning personnel actually use it User habits are often the biggest obstacle to the introduction of new technologies After conducting user interviews we found that the cleaning personnel of every public restroom have a LINE group The III team mentioned "Knowing that they cleaning personnel have a LINE group makes things easier At first, we cautiously asked the cleaning personnel if they would invite a robot "new colleague" to help inspect toilet paper and determine abnormalities in the restrooms At the beginning, the cleaning ladies were a little skeptical When they discovered that this robot "new colleague" was very useful, they fell in love with it" Due to cost, environmental protection, and convenience issues, WIFI was upgraded to NBIoT communication protocol WIFI is fast and has wide bandwidth A restroom has a men's room and women's room, which requires two separate systems for monitoring, and each system needs an independent 4G network to connect to the cloud system Therefore, the construction and communication costs are relatively high, and the power consumption is also relatively high At this point, readers may have questions Public restrooms are all set up in public spaces Is there no public WIFI network available The III team gave us a very in-depth answer "Actually, almost every public space has a WIFI network that can be used However, sharing WIFI with other people is prone to interference, and IoT devices are simple and lack security control mechanisms If you use public WIFI, there is a certain degree of security risk Therefore, in our solution, we still designed a closed WIFI communication system to solve the communication problem In addition, since a WIFI base station can only support 20-30 nodes, a women's room with 18 toilets requires a separate systems Coupled with the fact that it is separated by a concrete wall, the signal will be very weak and even affect the stability of the signal Therefore, a public restroom installing two systems is mainly due to stability considerations rather than cost considerations" In densely populated areas, using WIFI to transmit data to the server is not too troublesome However, when smart restroom systems are beginning to be applied to restrooms in remote areas, such as Lishan, Guguan, Shitoushan and other public restrooms of national park visitor centers, maintaining network connection is indeed a difficult problem Fortunately, new generation mobile communication networks of 5G includes narrow-band Internet of Things NBIoT specially designed for the Internet of Things The III is the first in Taiwan to develop Taiwan's first NBIoT MCU control system designed for smart restrooms using the NBIoT chipset of a domestic chip manufacturer In addition to the significant cost reduction, this system is also very energy efficient, requiring only 16 of the power of the original WIFI system The most important thing is that compared to traditional WIFI, which requires a relatively stable 4G signal connection, this system has wider coverage and allows communication deep in the mountains and out in the wild This allows wider coverage of smart restrooms in the future without being limited by network signals IV "Effect Analysis and Future Outlook" IoT smart toilet A revolution of clean, power-saving, and convenient new smart toilets As the complete set of sensors, cloud system, NBIoT, and LINE robot are gradually launched, the benefits are clear In the case of public restrooms at Songshan Train Station, from being overwhelmed at first to greatly reducing the number of customer complaints by 70, the time required to inspect toilet paper use was shortened from the original 15-20 minutes to only 10 seconds Once an abnormal situation occurs, it has gone from being undetected to the prompt notifications today Interestingly and unexpectedly, this entire system also brings the added benefits of safety and thorough enforcement of tobacco hazards prevention laws When a toilet is occupied for more than 40 minutes, a warning will be sent to the cleaning personnel group Hence, when a user occupies a toilet for too long, cleaning personnel will knock on the door This greatly improves safety In addition, odor detectors are also very sensitive to the smell of smoke Since smoking is prohibited in national parks, tourists sometimes sneak into public restrooms in remote areas to smoke In public restrooms of national parks, once the odor detector detects the smell of smoke, it will play a voice message about the Tobacco Hazard Prevention Act to let tourists clearly know that smoking in public restrooms will result in a fine of NT2,000 to NT10,000 Since the installation of odor detectors, the number of users smoking secretly in public restrooms has significantly decreased The "smart public restrooms" at Songshan Train Station won the "Golden Way Award" from the Ministry of Transportation and Communications for overcoming various difficulties, which made it famous From a constant stream of customer complaints to model public restrooms that the public sector has enthusiastically visited, the additional workload on the case officer from handling group visits is actually a luxury to be worrying about Future Outlook The system has proven its stability and cost effectiveness during the three years of RampD and field experiments, and has now been successfully transferred to domestic system integration companies The III also hopes that this system can be expanded in the future, and the technology can even be transferred to Europe and the United States In addition, on the basis of stable and reliable data flow and communication connections, the introduction of big data for analysis may make the deployment of manpower more delicate, and the problem of uneven work distribution can be expected to be fundamentally corrected Facing the arrival of an aging society, NBIoT communication systems, combined with various IoT sensors, may be able to bring us a healthier and safer living environment Some repetitive tasks that traditionally relied heavily on manpower can also use technology to greatly improve efficiency

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Rows:73, 9 pages