TextileGPT is an AI platform specifically designed for the textile industry, combining TNet's historical expertise and professional knowledge to accelerate product launches, reduce development costs, and strengthen knowledge transfer. Built on the TNet knowledge base, it provides intelligent dialogue capabilities enriched with industry-specific knowledge to address various challenges. The platform supports processing multiple data formats, including PDF, PPT, DOC, XLS, and web content, and features a user-friendly interface for quick adoption. TextileGPT aims to tackle issues like talent gaps and difficulties in knowledge inheritance, driving innovation and efficiency to enhance competitiveness, making it a key enabler for the textile industry's future development.

Shoku-AI integrates artificial intelligence (AI) to deliver systematic, automated adjustment solutions with quantifiable results. The system captures and applies engineers' adjustment expertise, combining it with quantitative result analysis to automate production parameter optimization. By leveraging engineering knowledge, Shoku-AI streamlines the generation of production parameters, significantly saving time and costs. With the addition of automated and intelligent adjustment capabilities, further time savings can be achieved through strategic equipment investments.

Combining with barometric pressure MEMS (microscale electro-mechanical systems) modules and low power characteristic, the sensor is suitable to monitor and measure water levels of drainage, sewer systems or inundation depths. Having high accuracy, low power consumption and lightweight, the product can be easily installed and maintained. It has the feature and functionality of acquiring real-time data from fields for further analyses, computing and modeling applications.

Five Features 1. Remote Monitoring and Visualization 2. KPI and analytics of solar power & Comparison of equipment power generation: Check the health and aging of the power station.Display equipment power generation trend and equipment status. 3. Works Management System and Report of Works Statistics: Planned maintenance management, system dispatch, automatic scheduling, and analysis of maintenance deficiencies to improve and optimize. Analyze the data and give feedback to the maintenance team to improve the system availability and optimize personnel allocation. 4. Fault Detection & Customized Reports: With data processing and AI arithmetic, this system spontaneous alert, and detailed PV array condition monitoring. Regularly inspect the power generation and income of the power station. 5. Value Added Services: PV forecast in power dispatching and revenue estimation. Assess the power generation of the sites to assist financial analysis.

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.

As solar generation applications continue to evolve, ensuring stable equipment operation and maximizing generation efficiency have been a main concern for owners. The platform integrates AI-driven O&M technology with precise data analysis to provide comprehensive equipment monitoring, real-time anomaly detection, and intelligent maintenance recommendations. This reduces operational costs and significantly enhances overall power generation efficiency.

PALF is committed to developing eco-friendly textile products by using recyclable, zero-carbon emission agricultural waste "Pineapple Leaf" to establish the first localized sustainable yarn and fabric pilot production line in Taiwan. We promote the recycling of waste materials to create a more environmentally friendly, sustainable textile and fashion industry.

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.

Askey’s smart 5G private network is designed for enterprise customers to build a dedicated wireless network, which integrates highly efficient 5G Small Cells, advanced 5G CPEs, self-developed 5G Private Network Management Platform (AMP), ruggedized enterprise-grade 5G Mobile Computers and 5G Cameras, and has excellent features of Low Latency, High-speed Transmission, and Ultra-high Reliability, and key benefits of Low Total Cost of Ownership, Easy Deployment and Management, and Superior Performance. It can be applied to smart manufacturing, smart transportation, smart exhibitions, smart cities, and other fields. We can tailor the network environment and continuously optimize it for customers, hence help enterprises build their 5G private networks easily and realize digital transformation quickly.

Facing issues such as urban-rural development imbalance and population outflow, E.SUN took the lead among financial institutions across Taiwan in formally launching the "Regional Revitalization Project" in 2018 in order to provide integrated services combining business counseling and funding support for local businesses. Collaborating with third-parties, E.SUN has already fostered over 20 industries and assisted more than two thousand local enterprises in securing funding. Furthermore, E.SUN has supported regional revitalization businesses through "enterprise incubation," "brand exposure," and "talent cultivation" to build a supportive environment for regional revitalization. E.SUN is committed to integrating sustainable concepts into our core financial services. In response to the UN biodiversity framework and TNFD international standards, E.SUN collaborates with the Ministry of Agriculture, Tse-Xin Organic Agriculture Foundation, and Corporate Synergy Development Center to launch the "Energetic Leopard Cat Loan" project, assisting producers in producing agricultural products with sustainable concepts.E.SUN also cooperates with the Ministry of Agriculture to hold counseling meetings, connecting counseling and funding platforms to promote sustainable agricultural development. Additionally, E.SUN sets up an ESG area on the employee welfare website to encourage employees to purchase these sustainable agricultural products, promoting mutual benefits for the industry and ecology.

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.

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