-)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.

Five Features 1. Remote Monitoring and Visualization 2. KPI and analytics of solar power & Comparison of equipment power generation: Check the health and aging of the power station.Display equipment power generation trend and equipment status. 3. Works Management System and Report of Works Statistics: Planned maintenance management, system dispatch, automatic scheduling, and analysis of maintenance deficiencies to improve and optimize. Analyze the data and give feedback to the maintenance team to improve the system availability and optimize personnel allocation. 4. Fault Detection & Customized Reports: With data processing and AI arithmetic, this system spontaneous alert, and detailed PV array condition monitoring. Regularly inspect the power generation and income of the power station. 5. Value Added Services: PV forecast in power dispatching and revenue estimation. Assess the power generation of the sites to assist financial analysis.

Focusing on developing and enhancing green competitiveness, we aim to provide three key ESG digital transformation solutions for traditional manufacturing industries: a carbon inventory system, machine predictive maintenance, and electrical safety monitoring. By integrating Taiwan's 5G networking industry, IoT-related sectors, and information technology companies, we are collaboratively developing a 5G smart manufacturing AI-enhanced energy efficiency platform. Using real-world case studies, we aim to initiate innovative vertical application model cases for 5G and AIoT industrial safety. With an open and collaborative technology platform, this initiative seeks to establish a representative example of 5G and AIoT industry integration and clustering in Taiwan

Vehicle Classification enables transportation authorities to automatically identify and classify vehicles according to their visual attributes. This technology finds widespread application in traffic management systems, toll collection, parking facilities, and security setups. FETCi leverages AI algorithms and machine learning methodologies to analyze video data collected through LiDAR technology. With an extensive database and repository, FETCi's AI AVC proficiently sorts vehicles into distinct categories, including cars, trucks, motorcycles, buses, and more. By integrating LiDAR technology with AI-powered image recognition, FETCi establishes a vehicle recognition system equipped with self-enhancement and deep learning capabilities.

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.

The Autonomous AI Surveillance Drone is a major innovation in drone technology, combining multirotor and fixed-wing capabilities. Utilizing white noise principles to enhance lift and efficiency, it enables high-speed flight and wide-area coverage, making it ideal for disaster response, border patrol, and other critical missions. Its core AI algorithm ensures reliability through real-time error detection. If anomalies are detected, the drone activates a safety mode, automatically returning or landing to minimize risks and maintain mission continuity. The flight control system integrates AI chips and edge AI technology, enhancing processing speed while reducing energy consumption for extended, efficient operation. These advancements enable stable autonomous flight even in complex environments.

Taichung City has deployed 1,220 air quality sensors, utilizing IoT and AI learning, along with a geographic information system to visually present real-time sensor monitoring data.By leveraging big data analysis, pollution hotspots and peak pollution periods are identified to assist environmental agencies in smart law enforcement. Additionally, cross-department collaboration is implemented for environmental governance, employing intelligent technology management for air quality control. The integration of unmanned aerial vehicles (UAVs) further enhances pollutant sampling efficiency.

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".

This project establishes a 5G private network in rural Tainan schools, introducing AR/VR gamified English teaching. Students engage in scenario-based games, simulating English conversations in virtual reality, fostering entertaining and interactive learning. The curriculum incorporates famous global landmarks and utilizes AR technology for checkpoint missions, enhancing student interest. Beyond English education, the initiative collaborates with the National Palace Museum, integrating AR/VR historical artifacts. Using 5G streaming, historical content is seamlessly integrated into campus teaching. The project not only enhances learning outcomes in rural junior high schools, reducing the urban-rural digital gap, but also has the potential for nationwide expansion. Through cross-disciplinary collaboration, it drives the development of both horizontal and vertical industry chains.

Key Features: 1. First-Line Local Security Protection and Control - Equipped with a trusted edge computing platform, meeting industry needs for an IoT operating environment. 2. Quality of Service (QoS) Maintenance in Emergencies - Ensures system and service operation during unexpected network interruptions. 3. Trusted and Secure OTA Update Mechanism - Guarantees stability of device updates and prevents malicious software attacks on IoT devices. 4. Secure IoT Operating Environment Meeting Industry Needs - Industrial computer-grade hardware and software integrated system, resistant to extreme working environments, stable and reliable, compatible with OCPP 2.0 industry standards.

NCREE has developed a Hybrid earthquake early warning system (EEWS) by integrating on-site EEWS from NCREE and regional EEWS from Central Weather Administration (CWA). Within a 10 to 100-kilometer radius from the earthquake epicenter in the local region, this system can provide 3 to 15 seconds of warning time. To achieve effective alerts with the available warning time, the utilization of a Hybrid EEWS cloud platform is crucial. This platform facilitates the transmission of alerts and the affected administrative regions to various industries. Industries, in turn, leverage these alerts to develop warning systems and automated control devices tailored to meet the specific requirements of different environments. This approach aims to minimize secondary damages resulting from earthquakes, transforming EEWS beyond being notifications received Presidential Alert on mobile phones. Instead, it offers a multi-faceted alerting and disaster reduction application system tailored to different environmental settings.

This project uses the 阡陌(QianMo) System, which drawing the road profiles, markings, signs, and signals based on the road geography data as a universal base map, to integrate cross-domain digital applications. Besides, 阡陌(QianMo) System has developed an application on mobile phone, through this application, user can complete the case opening, drawing, conversation recording, and photo-taking operations on-site, and convert the accident cases into collision elements in accordance with time, vehicle type, direction, collision type, and number of casualties. On the other hands, when handling improvements for accident-prone intersections, 阡陌(QianMo) System can overlay the elements to implement the collision composition analysis serves as a scientific proof and visualization tool for researching traffic improvement measures and explaining accident risk hotspots. Besides, after the subsequent engineering improvements, user can provide revision of road geography data as the feedback. Through this mechanism, which can achieve a digital governance cycle. Finally, through 阡陌(QianMo) System , this project integrates cross-domain applications related to police administration, transportation bureau, and engineering industry to improve driving environments and prevent traffic accidents.