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.

Billion Electric Group , in collaboration with Taiwanese partners, has successfully deployed 495 kWp of solar PV and 1,997 kWh of battery energy storage systems (BESS) in Palau, Tuvalu, and the Marshall Islands. These modular microgrids reduce reliance on imported fossil fuels, ensuring stable green energy supply for agriculture, aquaculture, and local communities. The project is expected to cut carbon emissions by 800 metric tons annually, with over 50% renewable energy self-sufficiency at aquaculture centers and demonstration farms. Meanwhile, livestock farms, offices, and dormitories now operate on 100% green energy, significantly lowering both energy costs and environmental impact. Billion Electric Group provides end-to-end energy solutions, from R&D and manufacturing to system integration and deployment. The project features MIT ( Made In Taiwan) renewable energy technologies, including Billion’s Fusio series BESS, Giga series PV inverters, and an AI-driven EMS (Energy Management System). The system enables real-time power optimization, bidirectional energy transmission, and cloud-based monitoring platform, significantly enhancing grid stability and energy efficiency.

The technical solution of Foxtron Electric Bus combines domestic and international resources, each contributing its strengths： 1. It adopts Foxtron's self-developed VCU software, integrates and develops the EEA architecture for electric buses, and utilizes motors, batteries, and chassis suspension systems from international major manufacturers. In collaboration with domestic manufacturers, Foxtron designs and develops dedicated low-floor bus frames for chassis cooperation. 2. In the product design of electric buses, Foxtron identifies pain points in traditional buses and improves upon them. For example, traditional buses often have issues with rollover protection and numerous blind spots, as well as differential wheel rotation caused by wheelbase, leading to frequent traffic accidents due to visibility problems. To address these issues, Foxtron employs Computer-Aided Engineering (CAE) and NVH (Noise, Vibration, and Harshness) analysis to verify the design of various systems and components. This ensures the overall strength of the vehicle body and chassis, enhances passenger safety, and incorporates features such as panoramic image display and an electronic wide-angle rearview mirror with a blind spot detection system to solve driver blind spot issues. Additionally, to alert pedestrians and other road users to the risk of differential wheel rotation, Model T projects prominent light beams onto the ground during turns, marking the danger zone.

The light rail transit (LRT) system could improve capacity of mass transit. However, most of the accidents occurred because road user run a red light, which affected LRT passenger rights. ž Using lidar/radar to detect the collision event may occurred. (reference the signal phase) ž Notify LRT driver the predicted event by C-V2X V2N solution. ž Outdoor N79 5G private network.

Integrated management platform, monitoring of real-time status in city and optimization of planning and operation with 3D digital twin model and data interface. On top of that, we have integrated with BriefCam Video Analytics Platform and advanced facial recognition system Corsight. BriefCam offers a robust portfolio of critical video analytics capabilities, fully integrated for video metadata search, alerting, and visualization. Corsight is an advanced facial recognition system that provides industry-leading accuracy in crowds and challenging environments. By applying the platform for various areas in smart cities such as smart building, smart factory, smart data center, and energy consumption, the users can gain an efficient integrated monitoring and management environment, intuitive monitoring based on 3D digital twin, and fast and effective response to events. It is an optimized solution for command and control centers in order to control every situation and manage operation centrally. Safety & Prevention of Accident • Detection of Aging • Failure of Infrastructure To Create a New Business Model • Management of City Resources and Core KPIs To Maintain Order in City • Public Transportation • Traffic • Parking Management ESG & Cost Control • Smart Energy Operation and Sustainability

Key Features: 1. First-Line Local Security Protection and Control - Equipped with a trusted edge computing platform, meeting industry needs for an IoT operating environment. 2. Quality of Service (QoS) Maintenance in Emergencies - Ensures system and service operation during unexpected network interruptions. 3. Trusted and Secure OTA Update Mechanism - Guarantees stability of device updates and prevents malicious software attacks on IoT devices. 4. Secure IoT Operating Environment Meeting Industry Needs - Industrial computer-grade hardware and software integrated system, resistant to extreme working environments, stable and reliable, compatible with OCPP 2.0 industry standards.

PD470 is industrial-grade Android handheld device. The rugged handheld enables 1.5m drop resistance and IP67 sealing level rate. It has built-in barcode scanners and a physical trigger button. This mobile computing device features multiple worldwide communication modes and has a 4000mAh high-capacity battery. PD470 weighs 243g only. It is slim, rugged, and explosion proof certified, making PD470 suitable for inspection in petrochemical plants, equipment, and construction areas.

“Chia-E Smart Patrol Car” utilizes AI image recognition and mobile edge computing technology to automatically compare license plate recognition results with stolen vehicles’ blacklist in real-time. If a match is found, patrol officers will be notified immediately by voice warning, so that they can stop the vehicle for investigation. By implementing technology, “Chia-E Smart Patrol Car” can improve the efficiency of investigation, maintain public safety, and maximize the effectiveness of patrolling.

By applying multiple disaster data on CIoT, including disaster warning and notification, rainfall, earthquake, regional drainage data, etc., collected from various public sectors, alongside with the on-site environment monitoring data, the data is verified and utilized by ThinkTron to develop the comprehensive All-Hazard Emergency Data Platform for the emergency response centers of some municipal fire departments in Taiwan. This not just enables the digital transformation but also boosts the digital governance. In addition, this GIS+IoT+AI integrated application is extended to smart industrial park management, helping corporate clients on achieving ESG goals accordingly by sustainable operation.

The 5G next-generation mobile network has the three characteristics of "eMBB", "URLLC" and "mMTC". Hwacom System Inc. creates diversified applications and promotes industrial innovation, such as artificial intelligence (AI) and Internet of Things (IoT) application integration platforms. In combination with domestic Netcom factories, vertical application integration is established to build a world-class application field. (Smart City, Smart Transportation, Smart Healthcare, Smart Factory)

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.

Enables on-premise training of medical AI models, including deep-learning and generative AI machine learning, from healthcare providers' own data lakes while ensuring data privacy, ownership, robustness, and cost-effectiveness.