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

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 project establishes a 5G private network in rural Tainan schools, introducing AR/VR gamified English teaching. Students engage in scenario-based games, simulating English conversations in virtual reality, fostering entertaining and interactive learning. The curriculum incorporates famous global landmarks and utilizes AR technology for checkpoint missions, enhancing student interest. Beyond English education, the initiative collaborates with the National Palace Museum, integrating AR/VR historical artifacts. Using 5G streaming, historical content is seamlessly integrated into campus teaching. The project not only enhances learning outcomes in rural junior high schools, reducing the urban-rural digital gap, but also has the potential for nationwide expansion. Through cross-disciplinary collaboration, it drives the development of both horizontal and vertical industry chains.

During the promotion of plastic life, we understand that only the concept of the circular economy can make the continuous reuse of resources. Therefore, we promoted the ”Plasticircular Project™” by using easily recyclable plastic as raw materials. Starting from the design of the product, the more we think about the end of the product, we are expecting to achieve the closed recycling model and system. All you have is what you want. In order to construct a service design for recycling packaging containers, to achieve a closed cycle of reuse and recycling of plastic packaging containers. We have the Project of the Plasticular and established a team to help with each step of the system.

FET uses cloud and IoT technologies launches a full range of electric vehicle charging services. It integrates all charging pile information on the market, provides complete information and cash flow services for both car owners and field owners to achieve real-time management. Features * Suitable fields：Apartment / Office building * Remote control within or without internet connectivity * Easy to use; Tap in access card and start charging * Convenient payment by telecom bill, credit card or LINE Pay * 24/7 operation & maintenance services

The Smart Dust Sensor technology is an innovative solution for integrating IoT networks into air quality monitoring. Developed collaboratively by the National Science and The National Science and Technology Council (NSTC), in collaboration with Taiwan Instrument Research Institute (TIRI) and Taiwan Semiconductor Research Institute (TSRI) of NARLabs, and leading academic teams in Taiwan, this technology has successfully miniaturized gas sensors while achieving low power consumption and high sensitivity. Its core features include exceptional sensitivity and stability, enabling real-time monitoring of multiple gases. Moreover, the fully domestically developed technology reduces dependence on imports and offers cost-effective sensor modules, driving the widespread adoption of air quality monitoring devices. The Smart Dust Sensor has undergone extensive field testing and third-party certifications across various applications. These include environmental monitoring stations (e.g., Taichung Dali Station), public recreational areas (e.g., odor monitoring in public restrooms), and industrial settings (e.g., semiconductor facilities and wastewater treatment plants). With its proven accuracy, reliability, and traceable data, the technology plays a key role in advancing air quality monitoring solutions, facilitating the development of smart cities, and contributing to improved environmental management.

Carbon Star is a specialized greenhouse gas (GHG) inventory management platform developed by StarTrust Systems, offering enterprises extensive carbon management capabilities. The platform encompasses organizational greenhouse gas inventories (ISO 14064-1) and product carbon footprint inventories (ISO14067), featuring the most extensive functional modules to enable enterprises to effectively gather carbon emissions data throughout their operations. 1. The platform is equipped with calculation benchmarks for carbon emissions and the latest factor data, facilitating enterprises in promptly collecting and computing data. 2. It integrates comprehensive management functions, including approval workflows and reminders, to assist various departments within enterprises in effectively managing greenhouse gas emissions. 3. Departmental access is segregated to ensure confidentiality across departments, allowing cross-departmental retrieval and referencing of only designated data. This measure guarantees the confidentiality of information from both manufacturing facilities and product domains. 4. Carbon Star automatically generates reports and emission inventories swiftly, streamlining enterprise management and verification processes. 5. Data analysis results are presented through a dashboard interface, empowering enterprises to compare and analyze data efficiently.

In recent years, the number of motor vehicle noise cases has increased, and it has been a concern for people in Taiwan. In order to protect the living environment and eliminate improper vehicle modifications, the Ministry of Environment has used acoustic camera technology for law enforcement since 2021. The system contains several scientific instruments, including a license plate recognition function that helps authorities identify noisy vehicles. Technology also improves inspection efficiency and quality of noisy vehicles. Existing roadside inspections require onsite noise measurement. The stationary noise test takes at least 20 minutes for each vehicle. Law enforcement using acoustic camera technology can simultaneously record videos, take photos, identify vehicles and complete noise measurements, to increase efficiency by a factor of 200. It is no longer necessary to use a large amount of manpower to carry out checks and inspections, greatly reducing labor costs. The Acoustic Camera equipment equipment used in this exhibition is provided by OE Scientech Co., Ltd. They not only supply fixed or mobile sound-based photography equipment to Taipei City, Taichung City, Chiayi City, and Changhua County but also have extensive experience in assisting with technology enforcement operations.

The device incorporates cutting-edge Edge control technology and is compatible with various sensors. • Independent Operation The device can operate independently even when powered off or disconnected from the network, ensuring continuous operation and functionality. • Remote Firmware Update and Configuration It allows for remote updating of firmware and configuration settings over the network, enabling easy maintenance and optimization of the device. • Data Storage and Transmission The device is equipped with capabilities for storing and transmitting data, facilitating the collection and transfer of information as needed. • LED Indicators The device is equipped with LED indicators for power and communication status, providing visual feedback on its operational status. 1.Model No: AIOT-C01 Fog Detection Controller Application Scope: Mountain Roads, Railways, Highway, Airport, etc 2.Model No: AIOT-C02 Rainfall Detection Controller Application Scope: Mountainous Area Water Level and Rainfall.

Powered by AI, this platform provides businesses with compliance management, risk intelligence analysis, and data-driven sustainable supply chain resilience, enabling them to effectively manage their supply chains.

The imbalance of agricultural production, sales and labor shortage have always been a huge challenge for farmers. The independent 5G private network with O-RAN effectively introduces affordable smart agricultural system through a leasing model, combining AI, unmanned vehicles, image recognition and other field information to upgrade smart farm production management system and increase the revenue.

• Features: With integrated AI-based image recognition, ultra-wideband (UWB) wireless positioning systems, warehouse management systems, and cloud platform services, the solution features automatically, real-time, and intelligent benefits to assist enterprises to achieve smart logistics and digital transformation with the enhancement of management efficiency and energy sustainability. • Functions: The solution includes AI-based image storage location identification, dynamic vehicle dispatching, automatic route planning, and display of available storage space. • Benefits: Higher management efficiency: Increases the inventory management efficiency by reducing the warehouse order pick up time by 12% on average. Energy sustainability: The system is estimated to save more than 6000 kg of annual carbon emissions for a single warehouse. Environmental benefits: Reduce 12% Warehouse order pick-up time, as well as an estimated annual carbon emission reduction of 6000 kg for a single warehouse.