The application of digital twin technology in building smart cities is becoming increasingly clear, serving as a crucial engine for driving urban transformation. In the development of smart cities in recent years, citizens can view the growth and development of the entire city, including population growth, new construction, and other major activities, in a 3D format, gradually emphasizing the concept of a virtual city. Digital twin technology can simulate disaster scenarios, including weather events and traffic accidents, assisting disaster response personnel in rapidly understanding the situation and optimizing the efficiency of disaster response. In recent years, with the advancement of aerial photography, simulation technology, and computing resources, The National Science and Technology Center for Disaster Reduction has leveraged advanced technology to create a mountainous flood inundation model system. This system enhances disaster warning and impact analysis, providing a comprehensive view of vulnerable settlements. It utilizes dynamic models and virtual-real integration, presenting alert information and disaster impacts through visual elements, contributing to informed decision-making in disaster situations.

Wave guide photovoltaic energy harvest system provides 75% more power than traditional solar panel. Highly decreasing cost of maintenance and set up. Waveguide owns unique talents of easy shapeable, colorful, and scattering light collection, which can help PVs to be lightly integrated into devices and create an energy-smart sustainable future.

Traffic approach warning system is the combination of smart detectors and LED warning signs. The intersection is divided into detection lanes and warning lanes. Smart detectors are installed on the detection lanes. When a vehicle enters the detection area, the signal is transmitted to activate the LED signs on the warning lane to warn drivers to slow down in advance.

VR environment that covers the terrain and seabed features of this world can be created easily in a short amount of time. Various VR environments and models including FBX models can be downloaded from the FORUM8 Web Server DB. The software supports the import/export of BIM data. Equipped with an ability to generate road alignments, cross sections, terrain, and the ability to position models and assign traffic and generate traffic movement within VR space; the software can help you give a real-time presentation for comparing design alternatives and stakeholder consultation as the Visual Options tools and presentation features will do all the tricks. As various types of high-level real-time simulation including driving simulation, daylight simulation, and traffic simulation are feasible, the software makes the lives of all engineers engaged in the work of design, development, and research easier.

AI Image Recognition (Intelligent Storage): Install surveillance cameras in the warehouse campus to accelerate the identification speed of AI Intelligent Image Analysis System through 5G network, and assist the management of the enterprise campus. AR Remote Equipment Maintenance: Use a 5G network to enable field workers to communicate with remote experts through AR smart glasses and simultaneously initiate multi-party video collaboration. Light A.I. Virtual Guard: Replace traditional human monitoring with AI cameras, connect to the cloud in 5G for real-time image recognition, and achieve real-time alerts via monitoring platforms and mobile app. AGV/AMR applications: Use 5G wireless connectivity technology to move cargo to designated picking stations and communicate with other equipment in the field to improve efficiency and reduce labor costs.

Infrared thermal imaging cameras use infrared thermal radiation emitted by objects to form a clear image and temperature distribution analysis image through the software to provide fast and non-contact temperature detection. For machine and manufacturing, thermal imaging cameras can be used to ensure electrical safety, and predictive maintenance of production machine and troubleshooting of after-sales services.

The Smart Mobility Solution is best fit for 2 industries: (1) With the occurrence of service demand, the service provider take requests that are to fulfill in limited time. Company such as ride-sharing, food or grocery delivery, professional services(car washing, garbage recycling, house maintenance, roadside assistance, etc., (2) Are required to deliver multiple shipments by 2/4 wheelers to destination at the same time. Factors such as specified time, locations, travel intervals, oil consumption, travel distance, are to be considered. A logistic company is the target audience under the scenario. The Smart Mobility Solution takes account of all possible concerns that the 2 industries encounter daily. With its unique AI algorithm, ETA data, etc., From the moment when the consumer inputs the address, the routing, distribution, delivery, records, optimization, all progress is assisted by 2-5 API tools. During implementation, industries are accompanied by Google premium partner Master Concept. Industries are expecting 1. Enhance to consumers and drivers experience 2. Increase to delivery efficiency 3. Cost saving to manpower and vehicles 4. Achieve ESG goals.

1. Directly driving fans with a motor increases transmission efficiency and highlights the superiority of direct drive systems over traditional transmission systems, especially when combined with a variable-speed control mechanism and at lower rotating speeds. 2. The absence of mechanical components in a direct drive system eliminates the need for regular maintenance of the reducer, gearbox, and transmission shaft, as well as reduces the risk of oil leaks. This results in lower maintenance costs, longer product life, and reduced operating costs for customers. 3. Installation of TECO's proprietary inverter for cooling tower can reduce operating noise, buffer activation, and lower mechanical impact. 4. A 30 kW motor in constant-frequency operation can reduce total operating costs by up to 18% over a five-year period.

For road safety, traffic efficiency, and energy savings, we adopt V2X and 5G C-V2X advanced technology to develop smart transportation including iDVR fleet management, driving assistant, AI sensors, RSU, OBU, etc., optimizing the driving and traffic operation.

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. A design-in service can provide ESS suppliers with the most suitable function integration without any interrupt.

Civil IoT Taiwan is part of the government’s Forward-looking Infrastructure Development Program under the Digital Infrastructure category. With the collective effort of the National Science and Technology Council (NSTC), the Ministry of Transportation and Communications (MOTC), the Ministry of Economic Affairs (MOEA), the Ministry of the Interior (MOI), the Ministry of Environment (MOENV), the Ministry of Agriculture (MOA), the Ministry of Digital Affairs (MODA) and the Academia Sinica, the project aims to address the core needs of the public by prioritizing four key mission areas, namely air quality, earthquake, water resources, and disaster prevention and response. By leveraging AI and IoT technologies, the project strives to deliver well-rounded, smart living services to facilitate the government and the people to respond to the challenges in an ever-changing environment.

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