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.

Handling abnormal complaints requires extensive experience and expertise. However, the resignation or retirement of senior employees often leads to knowledge loss, impacting organizational efficiency and competitiveness. Through vector models, Morale AI transforms unstructured data (such as emails, PDFs, and Word documents) into structured data and integrates it into databases, enhancing data usability. Multi-modal models combine diverse data types, including text and images, to systematically record and preserve experience. By leveraging Retrieval-Augmented Generation (RAG) technology and similarity search, the model can accurately categorize issues, identify the root causes, and recommend relevant cases, significantly reducing manual processing time and error rates. This systematic approach not only enhances response efficiency and enables real-time analysis and resolution of customer issues but also reduces repetitive work for employees, improving overall productivity and customer satisfaction.

The Sustainability Performance Management Platform assists enterprises in extending their management perspective from direct emissions to the entire value chain, ensuring the precise implementation of supplier sustainability performance management. The system features a comprehensive digital survey and data management platform, covering everything from questionnaire design, distribution, and response collection to multi-level approval and statistical analysis, enabling companies to integrate supply chain data with maximum efficiency. With flexible template design and year-over-year comparison tools, enterprises can track trends in key issues in real-time. The system supports diverse data entry methods and automated chart generation, while also offering seamless integration with sustainability reporting systems to enable automatic data updates. By leveraging this digital system, companies can establish a highly traceable data management process and significantly strengthen supply chain resilience. Core System Features: 1. Supplier and Stakeholder Performance Assessment: Digitally collect and audit various ESG indicators. 2. Automated Statistical Analysis and Comparison: Generate real-time visual reports to track annual performance trends. 3. Data Integration and Report Linking: Streamline data aggregation to accelerate the production of sustainability reports.

The need of video surveillance has increased with the issues of campus, public places security and intelligent transportation. What’s more, high-resolution image, identification, analysis and AIoT applications are getting popular than before. People are strict in the performance of transmission and computing. Internet communication technology has entered a new era as well. To achieve intelligent service, zMEC ’s platform as service through Kubernetes-based architecture which can not only integrate with the third-party but also expand different AIoT software application modules, such as identification and analysis, electronic fence. Besides, the technology of edge computing can reduce the demand of video and audio data for cloud center computing access and network bandwidth resources, so as to make up for the problem of traditional cloud computing delay and unsafe transmission link. It meets the need of high frequency bandwidth and low latency, and to satisfy the needs of information security and privacy protection.

The Ministry of Economic Affairs, Department of Industrial Technology has commissioned the Industrial Technology Research Institute's Center for Smart Sensing and System Technology to develop a "Composite Long-Term Air Quality Sensor." This sensor is capable of simultaneously measuring particulate matter (PM2.5), ozone (O3), carbon monoxide (CO), volatile organic compounds (VOC), and other air quality monitoring parameters. The sensor utilizes optical detection methods to detect concentrations of suspended particulate matter (PM2.5) and ozone (O3) in the air. Innovative key technologies, including dual-channel micro-particle sieving, micro-particle signal feature recognition, LED dynamic light source stability, and multi-environmental factor compensation, are employed to enhance the sensor's lifespan and accuracy. Furthermore, semiconductor and micro-electromechanical (MEMS) technologies are utilized to create a micro-heating chip. This chip, combined with gas nano-sensing materials and a single-chip sensing control circuit, converts the detected gas sensing resistance changes into carbon monoxide concentration values for the detection of carbon monoxide (CO), total volatile organic compounds (TVOC), and other harmful and odorous gas concentrations.

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.

Smart Network Management Software (NMS) – Cyber Monitor ● Provide the management ● Based on SNMP, it provides a single and friendly web interface for network admin clearly and easily to grasp the network situation. ● Automatically detect and manage network devices to monitor network performance. ● For network abnormalities and failures, automatically forward alarm reminders and dependency analysis to network admin in order to solve problems. ● Network devices are automatically discovered and managed, and the device list can serve as a baseline for inventory taking. ● Analyze network traffic to improve the visibility and management of network operation. ● Provide network security management under the SNMP architecture to avoid external malicious attacks and internal misuse. ● Flexibly define groups to improve the effectiveness of network management. ● Highly flexible and scalable, it can be customized according to the company's attributes and needs, therefore, strengthen the efficiency of network management.

The diagnosis of ADHD is based on the core symptoms appearing in DSM-IV or V criteria. In addition to the criteria, some physicians use checklists to assist the diagnosis of ADHD. However, either symptoms or checklists are subjective, which leads to diagnostic problem. In this product, data from the gyroscope and accelerometer in a smart watch were used to analyze the movements of children with ADHD. The children with ADHD and controls wore the watches on their hands simultaneously in class and compared the data from recorders for analysis. This method can help us to establish a objective tool for diagnosis and evaluation of ADHD.

The Ministry of Environment integrates IoT and generative AI for smart environmental governance. For fire emergency response, our AI-powered system provides real-time assist during challenging periods like weekends and midnight hours. Through an AI Q&A system, emergency personnel can instantly analyze air quality data and weather information, enabling quick response and public notification. This has reduced response time by 66% and decreased public complaints from 70 cases to single digits.

NU1, for office buildings with mobile access control system, bringing down 70% cost on wire deployment and 80% energy saving while no need for host PC from the very beginning.

Automated License Plate Recognition (ALPR) is widely employed in areas like highways, parking lots, urban roads, and many other controlled areas that need traffic management or law enforcement to preserve both the safety of road users and vehicles. However, ALPR encounters diverse environments and unexpected challenges, making it crucial to develop more efficient and precise solutions. FETCi AI ALPR Supports license plate designs and formats from over 100 countries, including various colors and fonts used in Asia and the Far East. Stacked letters and complicated background can also be identified through the power of AI.​ FETCi's AI ALPR solution features easy integration and high recognition success rate; it combines FETCi's accumulated decades of Toll Collection experiences and practical events database and analysis. With the assistance of FETCi's professional technical team, you can quickly build a complete, highly accurate, and easy-to-operate AI ALPR solution.

1. Using mainstream proton exchange membrane stacks for system module design。 2. Accumulated twenty years of various durability and reliability tests. 3. Design for mass production。 4. 3~10 kW different power models。 5. Improved power density and specific power。 6. The Booster 100% MIT is a patented technology, the only one of its kind in the industry。