Eup has developed a comprehensive video integration platform tailored for fire and emergency rescue operations. By connecting vehicle GPS, 360-degree cameras, body-worn cameras, and drone footage, command centers gain real-time, multi-angle situational awareness. This significantly enhances decision-making accuracy and frontline personnel safety—using technology to protect those at the very front line of emergency response. Unified Information Platform: Integrates ground-level and aerial perspectives to deliver complete emergency intelligence. Real-Time Command & Dispatch: Live video streaming ensures commanders stay fully informed of frontline conditions. Enhanced Responder Safety: Real-time monitoring of firefighter environments to predict risks and provide timely support. Cloud Video Backup: Secure cloud storage for rescue footage and operational records.

Prof. Chia-Hsin Chen’s Team – An Innovative AI-Powered Tongue Vibration Training System This project develops an AI-driven tongue vibration training system for dysphagia and obstructive sleep apnea. It combines a safe, adjustable tongue device, AI motion tracking with real-time biofeedback, EEG-based cognitive monitoring, and AR-based gamified training to deliver personalized, engaging, and data-driven rehabilitation.

Smart parking EV charger combines smart parking and charge service to provide total solution for roadside and off street parking. Integrates with license plate recognition system, it not only issue parking ticket, but also reduce occupation of fossil fuel vehicle and prolong parking with parking space barrier or other solutions. With smart card, the drivers do not require membership for charge and parking service.

Feature •Automatic Gain Control (AGC). •Backlight Compensation. •Automatic White Balance. •Wide Dynamic Range (WDR) function with 120dB at 30 FPS. •Night noise suppression function. •Nighttime shooting with automatic aperture adjustment. •Stable image quality during low-light shooting at night under stable external light conditions, ensuring no flicker or color rolling, and clear nighttime images. Specifications •Uses a CMOS 1/3” Image Sensor. •MAX Resolutions：2MP (1920×1080 pixels)，D1 (640x480 pixels) •Maximum Frame Rate：30 FPS @1920×1080，30 FPS @640x480 •Focal Length：2MP lens ： 2.8-12mm±5%，D1 lens ： Fixed •Minimum Illumination：Color： Below 0.06 Lux，Black：Below 0.02 Lux.

airaTrack is a comprehensive personnel tracking system that utilizes AI algorithms developed by our team to extract features from both the "face and figure." It generates unique biometric IDs with a recognition accuracy of up to 99%, all without the need for registering facial data, addressing privacy concerns. Capable of cross-camera searches and matching 10,000 faces per second, it significantly enhances the efficiency of traditional manual matching processes and increases search efficiency and accuracy by 97% enabling automatic path tracking of personnel in the field. The system also generates investigation reports for evidential preservation.

This service can avoid children and elders being lost. Users merely have to bring the device with them, through the sensor installed at the service area, family members can immediately receive users’ instant position through exclusive website, LINE or App. 【Real-time Positioning】 The caregiver can dynamically query and know about the real-time location and the path data for each care receiver. 【Guarding Area】 The caregiver can set different areas as guarding areas, and they will be notified if any care receiver enters or leaves these areas.

Integrated production management system covering 4M1E. Features real-time data collection, digital Kanban visualization, and full traceability. Enables paperless operations and complete process transparency. 1. Real-time Monitoring: Connects equipment signals to display WIP, utilization rates, and yield data instantly. 2. Traceability: Records comprehensive production lot numbers and process parameters for quality auditing. 3. Smart Scheduling: Optimizes production plans based on capacity constraints and order requirements.

"Hualien AI Agent: 24/7 Digital Travel Hub" is a smart solution specifically designed to enhance urban resilience and boost traveler confidence. Built on the LangGraph architecture and integrated with multiple Large Language Models (LLMs), the system utilizes Natural Language Processing (NLP) to precisely understand user needs. It supports over 20 languages, providing authoritative information ranging from local culture to real-time post-disaster traffic updates and safe routing. As the first AI Agent in Taiwan capable of proactively calling multi-source real-time APIs across various government departments, it combines LBS (Location-Based Services) with a professionally maintained RAG authoritative knowledge base. This allows the system to push precise safety alerts and personalized itinerary recommendations to users. Through deep OMO (Online-Merge-Offline) integration, the service extends from digital platforms to major transportation hubs, visitor centers, and local businesses. It not only demonstrates the resilience of digital governance but also fully empowers the tourism industry to accelerate its recovery.

• Features: With integrated AI-based image recognition, ultra-wideband (UWB) wireless positioning systems, warehouse management systems, and cloud platform services, the solution features automatically, real-time, and intelligent benefits to assist enterprises to achieve smart logistics and digital transformation with the enhancement of management efficiency and energy sustainability. • Functions: The solution includes AI-based image storage location identification, dynamic vehicle dispatching, automatic route planning, and display of available storage space. • Benefits: Higher management efficiency: Increases the inventory management efficiency by reducing the warehouse order pick up time by 12% on average. Energy sustainability: The system is estimated to save more than 6000 kg of annual carbon emissions for a single warehouse. Environmental benefits: Reduce 12% Warehouse order pick-up time, as well as an estimated annual carbon emission reduction of 6000 kg for a single warehouse.

Carbon Star is a specialized greenhouse gas (GHG) inventory management platform developed by StarTrust Systems, offering enterprises extensive carbon management capabilities. The platform encompasses organizational greenhouse gas inventories (ISO 14064-1) and product carbon footprint inventories (ISO14067), featuring the most extensive functional modules to enable enterprises to effectively gather carbon emissions data throughout their operations. 1. The platform is equipped with calculation benchmarks for carbon emissions and the latest factor data, facilitating enterprises in promptly collecting and computing data. 2. It integrates comprehensive management functions, including approval workflows and reminders, to assist various departments within enterprises in effectively managing greenhouse gas emissions. 3. Departmental access is segregated to ensure confidentiality across departments, allowing cross-departmental retrieval and referencing of only designated data. This measure guarantees the confidentiality of information from both manufacturing facilities and product domains. 4. Carbon Star automatically generates reports and emission inventories swiftly, streamlining enterprise management and verification processes. 5. Data analysis results are presented through a dashboard interface, empowering enterprises to compare and analyze data efficiently.

1. Economic line: outdoor bullet IP cam. Model No.: AH65C6D - Successful Case: Installed in "Taoyuan Shalun Industrial Zone" for offshore. - Sony Starvis™ sensor, 2MP, 5MP, 4K resolution available for selection - Different angle lens are available. Smart IR LED range is up to 30meter. - Edge AI including person detection as virtual fence, vehicle Detection - Aluminum die-cast chassis with stainless steel screws. IP68 certification and base on project requirements to provide salt corrosion resistant treatment on casing.

Prof. Ming-Yen Lin’s Team – A Prediction Model for Type 2 Diabetes Complications Our research group develops a decision-support prediction model for type 2 diabetes complications using data from over 163,000 Taiwanese patients. Integrating age, HbA1c, and other dynamic factors, the model estimates long-term risks of major complications and mortality, visualizes future trends, and supports personalized care planning to improve disease management and outcomes.