Millilab provides non-invasive and contactless vital sign detection solutions. These solutions monitor a subject's heart rate and respiration rate while ensuring privacy. The results are visualized in real-time through a GUI (Graphical User Interface). Applications include smart home appliances, intruder detection, sleep quality analysis, and more.

The Central Weather Administration (CWA) is the government agency responsible for earthquake monitoring and reporting in Taiwan. In order to reduce fatalities and property losses caused by earthquakes, a high-density real-time seismic network and the advanced earthquake early warning (EEW) system have been implemented and in operation. Currently, the CWA EEW system can issue the warning message in about 10 seconds after a strong earthquake occurring in or very near Taiwan. Starting from 2021, in order to further enhance the benefit of EEW to the practical earthquake hazard mitigation, the CWA has begun to develop the customized urban EEW system. By means of introducing the on-site earthquake early warning methods, and developing the artificial intelligence models. The systems, particularly for the big urban shallow earthquake, aim to further shorten the time of EEW to 7 seconds. That means it can give warning to the areas about 25 km away from the epicenter, and more people could be alerted before the destructive shaking.

By leveraging AI digital twin models, we predict KPI performance to support decision-making for backup machine selection, enabling energy savings and operational efficiency. Explainable AI is used to analyze the parameters influencing KPI, revealing that air compressor efficiency is strongly correlated with its shaft bearings, highlighting the importance of predictive maintenance for these components. Additionally, an intuitive dashboard visualizes the relationship between demand and supply data, facilitating real-time decision-making and responsiveness. With the integration of LLM Agents, users can communicate seamlessly with digital twins through natural language, enhancing usability and interaction efficiency.

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.

The power of 5G opens new opportunities for manufacturing upgrades. FET integrates Big data, AI and IoT technologies to build the first “5G Smart Factory” in Taiwan. We provide comprehensive smart manufacturing solutions from IT to OT, accelerating the progress towards Intelligent Manufacturing！ Features * 5G Private Network as a Service：Enhancing network security with MEC, seamless movement between buildings and flexible production with different industry I/O to 5G wireless network * AI Production Line Auditing：Manual process motion detection and intelligent control without omission * Smart Sensing：Real-time sensing of machine and pipeline abnormalities through flexible soft sensing patches * Enterprise Intelligent Cloud Center：Based on the “IT as a Service” concept to assist enterprise to build up Intelligence Cloud Center, which supports multi- services like virtual machines, virtual desktops, container and extension to the cloud

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 Civil IoT data service platform collected and stored environmental sensor data in four key areas: earthquake, water resources, air quality, and disaster prevention, and provides real-time data service using the OGC SensorThings API that conforms to the international data modeling standards for value-added services through a unified data modeling framework. In order to solve the problem of insufficient communication in remote areas, Band20 frequency band is utilized to build a backbone network core service for IoT application, which provides remote areas with the use of Band20 frequency band as a network communication method for IoT data transmission, and expands the scope of IoT deployment in remote areas.

Knowledge management solution receives another level! Integrating Generative AI, Search Engine, and NLP technologies, AI Search for KM produces precise and customized responses, offering users a better experience in knowledge search and QA services. We integrate Generative AI and intelligent Search Engine for knowledge management, assisting in the digital transformation of enterprises and enhancing productivity. Solving pain points encountered by technicians and aligning with user application needs.

Civil IoT Taiwan is part of the government’s Forward-looking Infrastructure Development Program under the Digital Construction initiative. With the collaborative efforts of the National Science Council, Ministry of Environment, Ministry of Economic Affairs, Ministry of Agriculture, Ministry of Transportation, Ministry of the Interior, Ministry of Digital Affairs, and Academia Sinica, the project is jointly executed across departments, prioritizing four key areas: air quality, water resources, earthquakes, and disaster prevention and response. By leveraging artificial intelligence and IoT technologies, various smart living services are developed to assist the government and the public in jointly addressing the challenges brought by environmental changes. By combining the innovative power of industry, academia, and research, the project aims to develop the IoT industry ecosystem and export solutions internationally.

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.

"EUP Fleet Management System" can easily manage the core needs of vehicle dynamics, task progress, emergency response, and utilize AI to analyze driving behavior, fuel consumption, and effectively control costs. In addition, EUP provides comprehensive safety driving checks, tracks driver driving habits and physiological monitoring, significantly improving driving safety, and assisting companies in building a safe, efficient, and low-carbon transportation fleet.

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.