This exhibition is an atmospheric physical-chemical grid model for prediction of changes in air quality, utilizing data from the U.S. NCEP global weather forecast and regional air pollutant emissions. Local scientific investigation data has been used to adjust and calibrate the model and thereby largely improve the accuracy of the air quality forecast over Taiwan. The system is capable of simulating the changes in air quality over the next three days (72 hours) in Taiwan, with a temporal resolution of 1 hour and a spatial resolution of 3 km. The simulated data can be integrated with air quality data from the Civil IoT Taiwan, informing regulatory authorities the changes in air quality for the near future, and key information for formulation of control strategies

In order to achieve the goal of intelligent transportation in Hualien and alleviate the crowds and traffic problems brought about by the opening of the entire Suhuakai line and the traffic problems in the city center, the Hualien County Government has developed a design that conforms to the local characteristics and constructs intersection numbers through the "Development and Construction Design of Intelligent Transportation System". Using smart technology to make traffic policies more accurate. Entrusted "Chunghwa Telecom Co., Ltd." to stage software and hardware in the "2018 Hualien Intelligent Traffic Integration Management System Construction Plan in Response to Su Hua Changing Vehicles", "2019 Hualien County Smart Traffic Management System Expansion Plan", The "109-Year Hualien County Smart Parking and Guidance System Construction Plan", "110-Year Hualien County Smart Road Network Management Integration and Traffic Corridor Improvement Plan" and other projects have been completed successively. There are five functions for overall optimization and refinement: "Cloud Smart Traffic Control", "Restructuring Time Signs", "Traffic Big Data Value-Added Application", "Signal History", and "Smart Parking"

Currently, the prognosis of critically ill patients in the intensive care unit (ICU) is often assessed using the APACHE or SOFA scoring systems to predict mortality rates. However, these systems have been in use for over 20 years, and the data they are based on is outdated. Today, clinical data is more abundant and precise, and advancements in machine analysis capabilities have made traditional scoring systems insufficient for meeting the demands of accurate predictions and personalized medicine. To address this, our team has developed a survival prediction device for critically ill patients. Using an AI algorithm model, it utilizes clinical data such as physiological, laboratory, and examination results to predict the patient's survival rates for the next 30, 60, and 90 days, providing a more accurate reference for prognosis assessment and medical resource allocation.

Smart Multifunctional Periodontal Pathology Quick Screening System (SMPPQSS) is the first product able to automatically identify the position of teeth and then to calculate the distribution area of dental plaque simultaneously. The system also provides a new painless gingivitis examination method that could relief examining discomfort. Neither the need of the plaque disclosing tablet nor a probe to penetrate into the patient’s periodontal pocket to determine the degree of periodontitis. Once all tooth-related data is automatically filled into the periodontal digits, the medical record sheet is uploaded to the system directly. It shortens the process to less than 10 minutes, greatly reducing the discomfort of patients during the examination as well as shortening the time doctors need to diagnose and record. SMPPQSS is easy to operate and portable. Dentists or dental assistants can check periodontal health quickly with no restriction of facilities, patients can receive a more convenient medical care even in remote rural areas or at home, or with limited mobility.

With the NFC technology of the Internet of Things, the” Chia-E Patrol & Sign” APP was created by bringing together the nation’s first "Smart Patrol Box" and 5G police mobile device.” It is able to find patrol blind spots, high-risk hotspots, and key time zones for duty, and so on by collecting real-time patrol data, further integrated and analyzed within the big policing data. Moreover, the system can automatically plan the best patrol route, and precisely deploy police force to public security and traffic hotspots by using AI data modeling, developing decision-making models and providing decision-making suggested values for task planning. Meanwhile, the nation’s original real-time intelligence push notification service helps the patrol officers stay on top of the surrounding conditions of the patrol box and the duty priorities, in order to prevent cases of traffic and public security disturbances.

Through Huijia Health's globally exclusive nFOPT® optical fiber monitoring technology, we have developed new products and solutions ESG AI Box (LiBox) that can be used in Industry 4.0. We plan to enter the semiconductor, petrochemical, energy, In the global market of industries such as electronic technology and machine tools, we provide ESG AI carbon reduction solutions to solve the dual-axis needs of industrial digital transformation and net-zero carbon reduction.

-)Data Collections -)Real-time Monitoring -)Decision Analysis -)Data Visualization Increase Capacity, Raise Efficiency, Cost Down

This service can avoid children and elders being lost. Users merely have to bring the device with them, through the sensor installed at the service area, family members can immediately receive users’ instant position through exclusive website, LINE or App. 【Real-time Positioning】 The caregiver can dynamically query and know about the real-time location and the path data for each care receiver. 【Guarding Area】 The caregiver can set different areas as guarding areas, and they will be notified if any care receiver enters or leaves these areas.

ARBOR’s smart medical wristband efficiently improves body temperature monitoring to tolerance within ± 0.1°C. With MediaTek’s IoT platform integrated, the wristband provides health condition information to be uploaded to synchronized with smartphones and the regional epidemic prevention system in real time so that patients’ vital signs can be monitored instantly and precisely. Collect the data on disease carriers and its environment, it can analyze patients’ medical and health information, and send the information to the patients and medical professionals. The public can also then receive the warning for diseases or epidemics.

Delivering a comprehensive fire and disaster information service, it allows users to access evacuation information even in offline environments. Based on the user's location, it provides immediate push notifications for 21 types of disaster alerts, including heavy rain, typhoons, and earthquakes. Additionally, it updates critical maps such as shelter locations and air-raid shelters as offline resources.

The Supplier and Investment Management Module is an extension of Carbon Star, allowing enterprises to manage not only their own carbon emissions but also conduct inventory and management of carbon emissions from suppliers or investment companies. The module features complete functionalities for carbon emission data inventory, registration, and management. Additionally, it offers comprehensive education and training services for enterprises regarding suppliers and investment companies. This enables enterprises to view and integrate supply chain data within the platform, and allocate and calculate data according to relevant criteria. The Supplier and Investment Extension Module includes the following functionalities: 1. Supplier greenhouse gas inventory 2. Supplier education, training, and guidance 3. Integration and management of carbon data within the supply chain

The BSMX series of early warning modules for lithium battery thermal runaway, developed by Taiwan Intelligent Pollutant Sensing Co., Ltd., is a next-generation BMS upgrade solution that requires only simple installation to integrate with existing systems. The module is equipped with high-sensitivity sensors developed specifically for energy storage safety applications, with a rapid response time of as fast as three seconds. The module offers multiple signal output interfaces to choose from and features a proprietary smart algorithm that eliminates the need for calibration after installation. It is particularly suitable for energy storage systems that operate continuously for long periods and are difficult to maintain