The system developed by this project provides a smart solution for station including digital fence system, platform pedestrian flow analysis, animal tracking expelled system, track water situation analysis system and platform digital information signage. The platform comprehensively analyses the image of around the station, train coordinates, passenger entry and exit, and water depth etc. Which can be used for follow up review and improvement of abnormal events such as track intrusion, crowd congestion and road flooding to achieve optimal train operation configuration and class spacing control. And provide abnormal event warning and troubleshooting and passenger intelligence information services. After the integration of multiple subsystem through the IOC platform, the system will automatically alert an alarm to the traffic control center and announce the train near the area to remind the driver to pay attention to the situation and enhance the safety of the train and the people or cars in the area when the detection system alarms.

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.

This project uses the 阡陌(QianMo) System, which drawing the road profiles, markings, signs, and signals based on the road geography data as a universal base map, to integrate cross-domain digital applications. Besides, 阡陌(QianMo) System has developed an application on mobile phone, through this application, user can complete the case opening, drawing, conversation recording, and photo-taking operations on-site, and convert the accident cases into collision elements in accordance with time, vehicle type, direction, collision type, and number of casualties. On the other hands, when handling improvements for accident-prone intersections, 阡陌(QianMo) System can overlay the elements to implement the collision composition analysis serves as a scientific proof and visualization tool for researching traffic improvement measures and explaining accident risk hotspots. Besides, after the subsequent engineering improvements, user can provide revision of road geography data as the feedback. Through this mechanism, which can achieve a digital governance cycle. Finally, through 阡陌(QianMo) System , this project integrates cross-domain applications related to police administration, transportation bureau, and engineering industry to improve driving environments and prevent traffic accidents.

WeatherRisk provides tailored energy forecasting solutions for the energy industry, including: 1. High-resolution, bankable historical data (metocean, solar irradiation) 2. Weather forecasting systems for O&M (offshore wind farms, solar assets) 3. Solar power forecasting (solar assets and grids) 4. Wind power forecasting (wind farms and grids) 5. Load forecasting Energy forecasting has a wide range of applications in the energy industry: • For FTM (front-of-the-meter) power dispatch, ancillary services, asset evaluation, and PV-Storage. • For BTM (behind-the-meter) virtual power plants, microgrids, renewable energy trading, as well as strategic support for energy market operations.

Exposure to “pesticide residues” has been linked to cancer, neurological diseases, reproductive health effects, and congenital developmental and learning disabilities; most fruits and vegetables are sprayed with pesticides, but we don’t know the extent of pesticide residues when we wash them Therefore, it is necessary to provide a device to help determine the pesticide residues in vegetables and fruits during cleaning, so that we can eat with peace of mind and eat healthily.

Our core product, AI-Stack, is a leading AI infrastructure management platform, essential for businesses adopting AI services. It integrates third-generation GPU partitioning, GPU aggregation, multi-node computing, a new user interface, multi-cloud management, open-source deep learning tools, and environment deployment features, helping enterprises tackle the challenges brought by fast-paced AI advancements.

Delta’s EV charging solution utilizes the self-developed DeltaGrid® EVM, an electric vehicle charging management system for smart charging, power allocation, and charging equipment management. To avoid exceeding the site’s power limit during simultaneous charging, which could result in fines or power outages, the depot adopted a smart charging management system to effectively address power overuse and charging allocation issues. Under limited power conditions, the system efficiently allocates charging power for the electric buses and provides flexibility for future fleet expansion. To address the challenges of charging commercial fleets, the system has dedicated features that were developed for electric buses and commercial fleet charging needs, including Vehicle Identification, Site Current Limitation, Real-Time Alerts, etc, effectively enhances charging efficiency, optimizes operational benefits for electric fleets, and successfully demonstrates the transformation to the electrification of transportation.

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.

A virtual power plant refers to the use of information and communication technology to integrate and regulate dispersed renewable energy sources, energy storage systems, power generation units, and adjustable electricity consumption. By aggregating small to medium-sized distributed resources to participate in power auxiliary service programs, it not only enhances the utilization of idle resources and generates additional revenue for operators but also contributes to the sustainable development of energy.

Founded in 2019, Millilab is a mmWave radar engineering services provider. The team comprises experts in RF, IC, and algorithms related to mmWave technology. Our mission is to apply the safest and most reliable sensing technology to the IoT domain, offering sensing solutions that are both privacy-preserving and accurate. Our services include mmWave radar total-solutions, as well as hardware and software development. Through our proprietary algorithms, we can detect object position, distance, movement, and vital signs, effectively distinguishing between adults and children. Applications include in-cabin sensing, smart home appliances, elderly care, and more.

eLAND specializes in intelligent data enriched with AI analysis, offering solutions through a Software as a Service (SaaS) model. Our product series are as listed below. Cloud Services, including OpView—the largest social listening platform offering business insights in Taiwan; PeopleView—describing the target market with AI while enhancing value of the customer database; and ECView, which monitors products in real-time across global e-commerce websites. For Intelligent Data Solutions, we tailor AI to diverse business needs. This includes AI Search for EC, the next-generation search engine and tagging system specifically designed for e-commerce, and AI Search for KM, which Integrates generative AI, search engine, and NLP technologies to deliver knowledge search and knowledge QA services. Within the Search Engine and NLP, our in-house technology excels in processing billions of unstructured data while maintaining exceptional efficiency, to fulfill customer's needs in digital era.

NCREE has developed a Hybrid earthquake early warning system (EEWS) by integrating on-site EEWS from NCREE and regional EEWS from Central Weather Administration (CWA). Within a 10 to 100-kilometer radius from the earthquake epicenter in the local region, this system can provide 3 to 15 seconds of warning time. To achieve effective alerts with the available warning time, the utilization of a Hybrid EEWS cloud platform is crucial. This platform facilitates the transmission of alerts and the affected administrative regions to various industries. Industries, in turn, leverage these alerts to develop warning systems and automated control devices tailored to meet the specific requirements of different environments. This approach aims to minimize secondary damages resulting from earthquakes, transforming EEWS beyond being notifications received Presidential Alert on mobile phones. Instead, it offers a multi-faceted alerting and disaster reduction application system tailored to different environmental settings.