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.

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.

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.

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.

The system developed by this project provides a smart solution for station including digital fence system, platform pedestrian flow analysis, animal tracking expelled system, track water situation analysis system and platform digital information signage. The platform comprehensively analyses the image of around the station, train coordinates, passenger entry and exit, and water depth etc. Which can be used for follow up review and improvement of abnormal events such as track intrusion, crowd congestion and road flooding to achieve optimal train operation configuration and class spacing control. And provide abnormal event warning and troubleshooting and passenger intelligence information services. After the integration of multiple subsystem through the IOC platform, the system will automatically alert an alarm to the traffic control center and announce the train near the area to remind the driver to pay attention to the situation and enhance the safety of the train and the people or cars in the area when the detection system alarms.

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.

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.

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.

Nearly one-third of the population in Yunlin County are first-tier industrial workers, mainly agricultural planting and fishery breeding. Through the inventory of various key program modules of scientific and technological agriculture and through service and product design, the six-tier digital system has been completed. It has been effectively improving the first-tier Industrial productivity and filling the gap in production instability, and receiving a solution for the lack of labor and the approval of the National Development Council Plan. This will also make Yunlin a place where cases of digital transformation and creation blooming. This service is introduced into multiple towns and villages in Yunlin County and 350 jobs have been created and about 320 million production value have been increased.The project won the 2022 “Smart City Innovation Application Awards".

eLAND specializes in intelligent data enriched with AI analysis, offering solutions through a Software as a Service (SaaS) model. Our product series are as listed below. Cloud Services, including OpView—the largest social listening platform offering business insights in Taiwan; PeopleView—describing the target market with AI while enhancing value of the customer database; and ECView, which monitors products in real-time across global e-commerce websites. For Intelligent Data Solutions, we tailor AI to diverse business needs. This includes AI Search for EC, the next-generation search engine and tagging system specifically designed for e-commerce, and AI Search for KM, which Integrates generative AI, search engine, and NLP technologies to deliver knowledge search and knowledge QA services. Within the Search Engine and NLP, our in-house technology excels in processing billions of unstructured data while maintaining exceptional efficiency, to fulfill customer's needs in digital era.

Through matchmaking of public and private forests, enterprises can acquire forest-related data through hosting mechanisms. This includes metrics such as survival rate, tree height, carbon sequestration, and corresponding SDGs (Sustainable Development Goals) indicators. Leveraging deep learning and image processing technology, CoCoTree transforms trees and forest landscapes into data, providing customers with highly accurate forest information. This includes metrics such as carbon emissions, tree growth status, and changes in the ecosystem.

Knowledge management solution receives another level! Integrating Generative AI, Search Engine, and NLP technologies, AI Search for KM produces precise and customized responses, offering users a better experience in knowledge search and QA services. We integrate Generative AI and intelligent Search Engine for knowledge management, assisting in the digital transformation of enterprises and enhancing productivity. Solving pain points encountered by technicians and aligning with user application needs.