OpView is the largest Social Listening platform in Taiwan, offering a comprehensive data analysis tool that enables real-time public opinion monitoring. Leveraging cutting-edge AI-powered Semantic Analysis and Search Engine technologies, OpView delves into a vast pool of 10 billion Chinese characters collected daily to extract meaningful social insights. Our platform excels at capturing trends and community dynamics, delivering enterprises with valuable information to stay ahead of the curve.

This service provides integrated solutions for drilling-related equipment, consumables, and materials, assisting clients in selecting and configuring resources according to project requirements to ensure material quality and engineering compatibility. Through a streamlined supply approach and project experience, procurement and operational risks are reduced, enhancing overall project execution efficiency. The service can be flexibly adjusted based on project scale and technical needs, supporting practical requirements from pre-drilling preparations through the execution phase.

Live crowd movement information is crucial in busy public spaces. Manual checks and basic sensors often lack accuracy and fail to keep up with real-time changes. The People Counting System uses AI video analytics and multi-sensor fusion. It delivers accurate, real-time crowd data. The system automatically counts people, tracks direction, monitors density, and provides instant alerts and reports. Deep learning ensures accuracy in low-light or crowded conditions. Multi-target tracking prevents double-counting. Edge computing and cloud-based management enable on-site analysis and long-term monitoring. Integrating cameras, infrared, Wi-Fi, and Bluetooth data improves detection and increases coverage. The system generates real-time heat maps, flow analyses, and historical records. These support layout optimization, entry regulation, evacuation planning, and efficiency. The system serves malls, transit hubs, campuses, parks, and public buildings. It is vital for smart cities. It replaces manual counting with intelligent management for better safety, responsiveness, and adaptability.

Far EasTone Telecommunications (FET) is committed to corporate sustainability and net-zero transformation. By integrating telecommunications with digital technologies, FET helps industries and society reduce carbon emissions. In the public building sector, FET is developing integrated solutions for “Net-Zero and Disaster-Resilient Energy Storage.” Combining net-zero strategies with Energy Management Systems (EMS), FET deploys renewable energy, energy storage, and smart energy-saving mechanisms. This approach balances carbon reduction with power resilience, supporting the public sector in enhancing sustainability and disaster preparedness. A key achievement is the National Taiwan Ocean University (NTOU) Gymnasium project, where FET implemented an advanced energy management platform integrating power monitoring, smart HVAC control, and renewable energy with storage systems. These efforts improved energy efficiency, provided a model for transitioning public buildings to net-zero, and earned the client Level 1+ Green Building certification. Looking ahead, FET will continue investing in net-zero buildings, energy storage, and resilient energy systems. Through collaboration with government, academia, and industry partners, FET aims to accelerate Taiwan’s progress toward sustainable development goals, advancing both net-zero emissions and disaster prevention.

"EUP Fleet Management System" can easily manage the core needs of vehicle dynamics, task progress, emergency response, and utilize AI to analyze driving behavior, fuel consumption, and effectively control costs. In addition, EUP provides comprehensive safety driving checks, tracks driver driving habits and physiological monitoring, significantly improving driving safety, and assisting companies in building a safe, efficient, and low-carbon transportation fleet.

-)Mainframe monitoring system, maximally supporting one million spots in real time. -)Smart loading balanbe for AOS -)Remote backup for AOS -)Adjudge amount of AOS as required, based on flexible structure. -)Central security management.

Capable of helping customers complete ISO-14064 greenhouse gas inventory rapidly and correctly, the platform offers boasts provision of real-time greenhouse gas emission data, production of lists and tables, and carbon emission forecast, , thereby assisting enterprises in planning carbon-abatement investments, attaining emission reduction according to timeline, and optimizing emission management flow.

To meet the high-speed operational demands of modern businesses, we offer stable dedicated enterprise circuits. Enterprise customers can flexibly choose transmission bandwidth according to their actual needs, with specifications ranging from 100M to 1G, and supporting ultra-fast transmission speeds up to 10G, ensuring uninterrupted flow of business information.  

Dr. Hung-Lung Lin’s Team – An Auxiliary Assessment System for Coronary Heart Disease Identification In response to population aging and the younger onset of coronary heart disease (CHD), this study develops an AI-based auxiliary CHD screening system integrated into a mobile app. Grounded in traditional Chinese medicine tongue–heart theory, the system analyzes sublingual vascular images using reflection removal, image segmentation, and a multi-head attention deep learning model. Users can obtain accurate, reproducible screening results and health recommendations within 7–20 seconds using only a smartphone, enabling convenient and cost-effective preliminary CHD assessment.

With our fiber sDAS, Wave-In effectively reduce mobile signal dead spots caused by insufficient base station coverage, buildings or electromagnetic signal interference. Due to the pandemic, Taiwanese Engineers weren’t able to assist with on-site installation and coverage testing, to solve this problem and improve efficiency, Wave-In utilized Mixed Reality for collaboration and remote assistance.

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.

- Zero-Code AI Security Enable enterprise-grade protection via an OpenAI-compatible API—no code changes required. Instantly defend against Prompt Injection and PII leakage. - Flexible Enterprise Guardrails Supports Inline and Shadow modes with Prompt & Response Guardrails to detect and block risky interactions in real time. - Scalable AI Governance Built for scale with auto-scaling, multi-tenant management, and seamless SIEM/SOC integration via Alert APIs.