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【2020 Solutions】 Fever Monitoring Gadget: Small Temperature Patch for 24-hour Observation

A stamp-sized flexible temperature patch became an essential tool for fever monitoring amid the ongoing COVID-19 pandemic, with orders soaring to over 500,000 units in just two months, proving useful for home isolation and medical quarantine.

iWEECARE, established just five years ago, has created the world's smallest connected smart thermometer, Temp Pal, which offers remote continuous temperature monitoring and alerts. iWEECARE has integrated a temperature sensor into a 3-gram, stamp-sized flexible patch, which is stuck under the arm's skin and can continuously monitor temperature between 36 to 48 hours without interruption, transferring temperature data via Bluetooth to a mobile app and cloud backend, displaying real-time temperature changes and setting fever alerts.

In this epidemic response effort, the rejuvenated hospital, equipped with negative pressure isolation wards, installed a temperature monitoring system. Unlike the common forehead or infrared temperature monitoring methods, the hospital uses Temp Pal smart temperature patches developed by iWEECARE, which are only stamp-sized (3*3 cm), stuck under the patient's skin under the arm, combined with a low-power Bluetooth receiver, allowing continuous monitoring of the patient's temperature, recording every 5 minutes. If a case of fever is detected, the system will notify medical staff proactively, enabling them to accurately monitor the patient's condition and handle it promptly, thereby enhancing patient safety care.

像郵票一樣大小的體溫貼片

▲像郵票一樣大小的體溫貼片

醫院設置即時體溫貼片監控系統 節省超過6萬件防護衣耗損

振興醫院表示,引進監控體溫的即時體溫貼片監控系統,對隔離患者進行24小時體溫監測,醫護人員可以在不進入隔離病房的前提下,事先擷取到病患重要的生理數據,在提昇照護品質同時,醫護人員進出隔離病房的頻率可以減半,1個月即可節省約6萬5千多件防護衣的損耗。

The Temp Pal smart thermometer is not just small and capable of continuous temperature monitoring; its biggest feature is the ability to 'actively and continuously monitor multiple people's temperatures,' ideal for group quarantine and mass isolation in hospitals, achieving efficient and thorough results.

Kang Ying-Cen, the marketing director of iWEECARE, mentioned that initially, the 'Temp Pal wearable smart thermometer' was mainly used in maternity centers or by new parents to continuously measure a baby's temperature, monitoring the temperature trends of newborns and early prevention of potential harm. Unlike standard thermometers that measure at singular moments and require manual adjustment every 4-6 hours, the smart thermometer, with its personal and soft design, does not cause any discomfort to the baby and monitors temperature continuously. If the temperature deviates from normal values, the mobile app will also sound an alarm to prevent scenarios where the fever could lead to grave consequences.

將體溫貼片貼於腋下,36小時監控寶寶的體溫

▲將體溫貼片貼於腋下,36小時監控寶寶的體溫

精準掌握基礎體溫 備孕效果佳

由於連網智慧體溫計蒐集了使用者的體溫趨勢的數據,未來透過AI演算法的導入,對於婦女的排卵期有精準的掌握,一般而言,適孕婦女的「基礎體溫」是指在較長時間的睡眠(約6~8小時)後,尚未進行任何活動前(含起身下床)所測得的體溫,且每天需於相同的時間進行,此為人在一天當中最低的體溫點。在健康的身體狀態之下,溫度曲線會隨著週期間的排卵而產生升高溫的現象,也就是說,即基礎體溫在排卵日當天會升溫,想要懷孕的女性可以藉此作為受孕及避孕的基礎。

現階段除了台灣外,連網智慧體溫計也銷售至東南亞、新加坡、加拿大及歐洲等地區,其中,位於泰國,屬東南亞最大的私人醫院集團在2019年底也開始採用 Temp Pal Group System(添寶群體監測體溫系統),該醫院目前在泰國各城市有 40 家分院。以往體溫正常者平均每 4 小時護理人員要量測病患體溫一次,體溫異常者則每 1 小時需量測一次,而採用 Temp Pal 群體監測體溫系統後,智能體溫貼片每次充電可使用長達 36 小時,每日最高可減少 23 次的體溫量測頻次,估計可節省每日每單位護理人員 2.5 小時以上的時間。

體溫貼片以藍芽傳輸,透過手機APP傳輸溫度變化

▲體溫貼片以藍芽傳輸,透過手機APP傳輸溫度變化

愛微科兩位創辦人為有電池設計專長的曾軍皓及擅長韌體開發的張和逸,一開始對於穿戴式智慧體溫貼片在台灣屬於第二類醫療器材的規定認知有誤,第二類醫材要上市,不光是要取得政府核發許可證,還得通過臨床前測試,而在歐美要通過認證,至少要花一年的時間,日本市場則需要投入兩到三年通過認證,難度更高。未來1-3年內,愛微科仍將持續研發新型的態體溫貼片,以提供更多元服務。

愛微科兩位創辦人

▲愛微科兩位創辦人

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

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Utilizing Extreme Present Tech's 4D Drone Cloud Platform Reduces Inspection Costs to One-Fifth

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【解決方案】光禾感知科技智慧球場體驗 AR互動讓看球變得更加有趣
OSENSE Technology Qubby AI customer service helps enterprises comprehensively upgrade from customer service to knowledge management

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【解決方案】瑕疵辨識率達百分百 耐銳利科技獲面板大廠青睞
Defect identification rate reaches 100%, Nairi Technology is favored by major panel manufacturers

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