ESGP (Enterprise Sustainability Governance Platform): This platform aids businesses in conducting automated carbon footprinting, utilizes AI technology to generate sustainability reports, effectively manage ESG information, and produce various reports tailored for different stakeholders.

Empower your business across critical domains—operations, HR, legal, finance, customer service, recommendations, health education, and equipment management. By integrating Generative AI with advanced knowledge management, we transform how enterprises manage real-time monitoring, dynamic insights, intelligent Q&A, data visualization, text recognition, and content creation. Our solution reduces human error, eliminates redundant tasks, and streamlines complex processes—paving the way for true business process reengineering. Experience faster decisions, smarter workflows, and a future-ready enterprise.

With 5G private network system integration provided by Wave-In Communication, Inventec is transforming its Taoyuan Factory into a 5G smart factory, creating highly intelligent and automated production lines with AI and IoT capabilities.

With the emergence of technologies such as 5G, the Internet of Things, Artificial Intelligence and Cloud Computing in recent years, the server industry has experienced explosive growth. In line with the two major trends of "software definition" and "open standards," private industry and governments are collaborating to promote numerous high-tech research projects and the development of critical technologies. As the cloud industry chain continues to evolve, the annual power consumption of data centers, which are made up of numerous individual servers, increases greatly. Consequently, the effective thermal management of servers and data centers has become an increasingly crucial issue.

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.

This service focuses on energy development and subsurface structural research, providing comprehensive engineering planning from site assessment and well placement design to drilling execution and final well reporting. Through systematic preliminary analysis and engineering design, we assist clients in obtaining valuable subsurface data while ensuring construction safety, serving as a critical basis for subsequent development or evaluation. The service scope includes drilling path design, construction condition assessment, drilling process planning, and risk management, effectively reducing construction uncertainties and enhancing both operational efficiency and data reliability.

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.

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)

C.ai: Conversational service platform is recommended as the best autonomous solution for enterprises to implement LLM intelligent assistants and related applications. It features easy editing with No-Code/Low-Code, easy integration with internal and external systems, and a complete service interface. With LLM application compliance and governance, enterprises can choose to integrate various suitable language models to enhance AI implementation capabilities. It supports various communication software and browsers, completing design and launch in one stop.

MiTAC has leverage the RFID technology and integrated with related solutionsto modify the warehousing and production management system. MiTAC's RFID Smart Manufacturing Solution has been applied in various industry, such as IPC, LED, Semiconductor, and textile industry. MiTAC has provided complete RFID application solutions these years from the inventory to production management system. We sees RFID as a game changer. Besides the RFID technology, the integrated application system is also important. MiTAC also develope the application systems. For each different scenario. We’ve developed a different system to work out a more complete RFID solution. We've also used supervised learning AI modules to develop MiTAC’s MiAION SeeR, a failure detection solution. MiTAC's strong software development ability is the biggest advantage.

Far EasTone’s Traffic Signal UPS System ensures that intersections remain “lit and flowing” even during power outages. By integrating Far EasTone’s self-developed monitoring and management platform with smart batteries and signal controllers, the system can instantly track battery levels, utility power status, and device health. When an abnormality in the utility power occurs, the smart battery automatically takes over to keep the traffic lights operating normally. This enhances road and public safety while preventing sudden traffic disorder or additional carbon emissions caused by congestion. At the same time, battery and UPS data are sent back to the platform, allowing management units to detect abnormalities in real time and respond quickly—building truly stable and uninterrupted smart mobility for cities.

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.