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【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 fall detection solution

▲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's fall detection solution

▲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」

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【導入案例】巨量遙測空間數據AI分析雲端服務平台 使衛星遙測影像順利落地應用
AI Analysis Cloud Service Platform for Remote Sensing Big Data Enables the Smooth Application of Satellite Remote Sensing Images

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這是一張圖片。 This is a picture.
[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, 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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 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【導入案例】赫銳特科技VCSEL封裝元件瑕疵導入AOI檢測 提升產能效率20
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 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