To enhance facility management efficiency and visitor service quality in Nantou County’s scenic areas, the Nantou County Scenic Area Administration Office is implementing a Smart Management System. The system applies digital technologies to strengthen operations, safety management, and data-driven governance. It integrates maintenance and inspection records for key facilities such as trails and suspension bridges, establishing a centralized database. Through data analysis, authorities can monitor facility conditions, identify maintenance needs, and implement preventive maintenance strategies, reducing costs and improving operational stability. CCTV and smart sensors are gradually deployed in high-risk areas to enable real-time monitoring and anomaly alerts. During extreme events such as typhoons or earthquakes, managers can quickly assess infrastructure safety, improve emergency response efficiency, and reduce manual inspection workload. A QR Code-based smart reporting function allows visitors to instantly report facility issues. Reports are automatically recorded and assigned for follow-up, accelerating response time and enhancing visitor safety and service experience. Through smart management and data-driven decision-making, Nantou County is building a safer, more efficient, and sustainable scenic area management model, supporting smart tourism and long-term development.

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 Track Safety Management System is primarily aimed at addressing safety concerns along the track. It provides real-time monitoring, statistics, and detection-triggered alerts for trackside environments including stations, level crossings, along the track, and slope areas. The goal of this management system is to establish early warning alerts and prevent accidents from causing damage. Through the intelligent AIOT recognition monitoring system, it detects and analyzes station pedestrian traffic, tracks pedestrians at level crossings, identifies passing vehicles and traffic flow, detects foreign objects at level crossings and activates alarms, monitors personnel lingering and debris along the track, conducts rockfall monitoring on slopes with a rain gauge, monitors the environmental conditions in equipment boxes, and oversees the operation status of level crossing equipment. The monitoring data and image information are transmitted to the management system platform for integrated management via fiber-optic networks, NBIOT, or mobile communication. Additionally, it provides central management personnel with real-time interpretation and remote control in case of anomalies.

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.

Criminal and street violence cases will affect and cause panic to citizens. In order to diminish street violence cases, reducing the time to solve these cases, protecting citizens’ lives and properties, and allow citizens to live without fear, the Kaohsiung City Police Department (KCPD) built the “3D Street Violence Early Warning, AI Intelligence Collection and Integration Platform” (hereinafter called “the Platform”). The platform utilizes the Internet of Things (IoT) to combine AI image recognition and sound sensing technologies for cross-domain big data analyses. KCPD established cross-platform data interfacing and integration, mainly through “data integration” and “network analyses” to collect with the municipal government’s transportation bureaus and social bureaus; and import existing data from the KCPD data platforms. The Platform will, through web service API, (a) retrieve data built by information systems, (b) conduct big data analysis, aggregate applicable intelligence data and present it in the form of dynamic information, (c) Integrate all information and display it as maps and topologies, improve case handling efficiency. According to KCPD employees’ query, they can adjust factor weights and relationships. Analyze the results based on rational mathematical models and professional case-handling concepts, so that intelligence analysis goes beyond the limitations of platform developers and allows criminal police to maximize their capabilities.

Integrating RPA, Generative AI, Machine Learning, and Process Management technologies, we provide manufacturing solutions to address supply chain communication, timely business delivery responses, on-site scheduling optimization, order insertion issues, new employee training, and corporate administrative problem-solving.

Taiwan AI Cloud AI Compute Foundry solution provides one-stop AI infrastructure services. Assist governments, enterprises, and the global GPU market in driving the development of sovereign AI. Empower enterprises to build customized AI compute centers with their own AI infrastructure, data governance, and model operation environments. We provide complete AIHPC deployment, integration, and maintenance services, supporting private, public, and hybrid cloud architectures.

AI Biodiversity Platform using CHTCityOS as essential architecture enables rapid implementation, scalable performance, and seamless cloud integration.By consolidating technologies and services into a single solution, Chunghwa Telecom helps customers simplify management, improve efficiency, and accelerate digital and sustainable initiatives. Chunghwa Telecom as a leading ICT solution provider, offers a fully integrated, one-stop service covering system design, platform deployment, and ongoing operations.

EZESG by Trade-Van Information Services Co. helps enterprises systematically complete organizational greenhouse gas (GHG) inventories in accordance with ISO 14064-1, strengthening carbon management and enhancing transparency in information disclosure. The system enables rapid establishment of an emissions source database by integrating data from energy consumption, raw materials, and operational activities. Through AI-powered OCR, it automatically identifies information from utility bills such as fuel, water, and electricity. It also incorporates Google Maps mileage calculations and taxi carbon emission models to estimate emissions from transportation activities. With built-in intelligent calculation models, the platform automatically consolidates Scope 1, Scope 2, and Scope 3 emissions data, reducing manual errors while improving data consistency and reliability. The system also supports one-click generation of GHG inventory reports and supporting documentation, simplifying procedures and shortening preparation time. Through digitalization and intelligent management, it helps enterprises respond to international regulatory requirements and steadily progress toward net-zero emissions and sustainability goals.

Leveraging its strong telecommunications and ICT integration expertise, Far EasTone delivers comprehensive smart building solutions for modern, data-driven environments. With a reliable fiber backbone, 4G/5G and Wi-Fi networks, and IoT technologies, Far EasTone seamlessly connects on-site sensors, surveillance, access control, and environmental systems to create a secure and resilient data infrastructure. By adopting open communication protocols, Far EasTone enables cross-system integration, consolidating previously fragmented power, fire safety, HVAC, and low-voltage systems into a unified building management platform. This ensures intelligent centralized monitoring and coordinated operations across all building systems. The platform offers real-time monitoring, data analytics, operations and maintenance management, and AI-powered Digital Twin visualization. It empowers building owners with full lifecycle visibility, reduces energy consumption, enhances operational efficiency, and delivers safer, smarter, and more sustainable buildings.

Prof. Ming-Chung Chou’s Team – Intelligent X-ray Imaging System Traditional X-ray imaging depends on experienced radiographers to balance image quality and radiation dose. Automatic exposure control may misjudge patients with poor positioning or metallic implants, increasing radiation by about 20%. This study develops an AI-based X-ray imaging system with non-contact body thickness measurement. By integrating patient height and weight, the system automatically determines optimal exposure parameters, ensuring stable image quality while reducing unnecessary radiation and cancer risk.

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.