With the rapid growth of electric vehicles (EVs) in Taiwan, the demand for charging infrastructure is increasing. However, most developments focus on high-power DC fast charging systems, which face significant challenges. Complicated feeder application procedures and imbalances in urban power grids make it difficult to deploy medium and large-scale charging stations. While AC chargers (up to 22kW) are easier to install, they fail to meet the need for fast and efficient charging. To address these challenges, GREAT introduces the "Charging Silk Road" solution. This innovative system combines advanced energy storage systems (ESS) with fast charging equipment to enable independent power supply and reduce reliance on the public grid. By integrating renewable energy sources such as solar and wind power, the system maximizes energy efficiency and sustainability. Additionally, the solution features Vehicle-to-Grid (V2G) capability, allowing stored energy to be fed back to the grid during peak demand or emergencies, supporting grid stability. Through a distributed, multi-site deployment model based on independent microgrids, GREAT’s Charging Silk Road creates a flexible, resilient, and efficient green charging network, accelerating the transition to net-zero carbon emissions.

Real-time 3D precise positioning service (LBS) uses ultra-wideband (UWB) technology to track objects with precise positioning accuracy; this LSB also includes RTLS 3D back-end software, UWB anchors and UWB positioning tag products.

SONOBA COMET is a paperless conference system using tablet computers. Simple, no complicated operation or preparation required. Convenient, one-person operation, all participants can be expressed simultaneously. Information security, delete the information after the meeting. SONOBA COMET” is a product that has been positively received and implemented by a wide range of customers in different industries and business categories, such as banks and brokerages, IT companies and music-related companies, and public institutions like universities and hospitals. As a communication tool, it is performing well not only in meetings but also in various other scenes such as presentations for operating activities, training and seminars, and telemedicine.

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.

By the integration and utilization of IoT engineering information and sensor data about water resources management, air quality monitoring, disasters prevention and warnings…, we introduce end-to-end enterprise private networks to provide custom infrastructure systems and services for SMBs and public sectors.

MIRDC’s continuously Rotating Wind Turbine UAV Inspection System can effectively inspect the working wind turbine without interference. It takes 5 minutes to complete the inspection of a single blade to effectively detect 4mm small cracks. The system will not lose power generation by turning off the wind turbine, further observes the actual movement status of running blade structure and pillars to grasp the defects beforehand.

TextileGPT is an AI platform specifically designed for the textile industry, combining TNet's historical expertise and professional knowledge to accelerate product launches, reduce development costs, and strengthen knowledge transfer. Built on the TNet knowledge base, it provides intelligent dialogue capabilities enriched with industry-specific knowledge to address various challenges. The platform supports processing multiple data formats, including PDF, PPT, DOC, XLS, and web content, and features a user-friendly interface for quick adoption. TextileGPT aims to tackle issues like talent gaps and difficulties in knowledge inheritance, driving innovation and efficiency to enhance competitiveness, making it a key enabler for the textile industry's future development.

The application of digital twin technology in building smart cities is becoming increasingly clear, serving as a crucial engine for driving urban transformation. In the development of smart cities in recent years, citizens can view the growth and development of the entire city, including population growth, new construction, and other major activities, in a 3D format, gradually emphasizing the concept of a virtual city. Digital twin technology can simulate disaster scenarios, including weather events and traffic accidents, assisting disaster response personnel in rapidly understanding the situation and optimizing the efficiency of disaster response. In recent years, with the advancement of aerial photography, simulation technology, and computing resources, The National Science and Technology Center for Disaster Reduction has leveraged advanced technology to create a mountainous flood inundation model system. This system enhances disaster warning and impact analysis, providing a comprehensive view of vulnerable settlements. It utilizes dynamic models and virtual-real integration, presenting alert information and disaster impacts through visual elements, contributing to informed decision-making in disaster situations.

This exhibition is an atmospheric physical-chemical grid model for prediction of changes in air quality, utilizing data from the U.S. NCEP global weather forecast and regional air pollutant emissions. Local scientific investigation data has been used to adjust and calibrate the model and thereby largely improve the accuracy of the air quality forecast over Taiwan. The system is capable of simulating the changes in air quality over the next three days (72 hours) in Taiwan, with a temporal resolution of 1 hour and a spatial resolution of 3 km. The simulated data can be integrated with air quality data from the Civil IoT Taiwan, informing regulatory authorities the changes in air quality for the near future, and key information for formulation of control strategies

The award-winning service application: 【Smart Campus - Smart Library, Healthcare Management System】to realize the independent management of school library and health care, it also greatly reduces the load on the schools’ administration, achieve the goal of sharing library and healthcare resources between teachers and students, through the collection and analysis of the big data in the background system, it will be more accurate for students’ recording values, AI predictive models can also help the govermant authorities the effectively assess and make the timely decisions, so far, all schools have been deployed and put into operation, benefiting about 25,000 teachers and students from 125 schools, the system is also launched simultaneously in all the Digital Opportunity Center (DOC), implement community cultural construction and connection; In future, we will continue to improve our services as a core: friendship between teachers and students, feelings between parents".

Yunlin County Government is dedicated to establishing a human-centric smart agriculture, providing services for digital and green transformation to overcome industry challenges and climate change. People collaborate with machines, automation equipment, and computers to enhance industrial productivity by using information technology. Simultaneously, it promotes Intelligence Augmentation (IA), fostering the growth of industry personnel capabilities. To accelerate agricultural transformation, solutions are developed with experts in various fields of agriculture and livestock. Through sharing successful case studies, the aim is to guide industry stakeholders to embrace new knowledge and technologies. Additionally, counseling teams assist farmer groups in transitioning towards a smart agriculture concept that combines 'smart technology' and the 'net-zero emission' approach. The development focuses on creating a future agriculture model primarily based on automation and AI, striving for efficiency, quality, and Intelligent Automation (IA).The project won the 2024 Smart City Innovation Application Awards.