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 Ministry of Economic Affairs, Industrial Technology Bureau, has commissioned the Smart Sensing and System Technology Center at the Industrial Technology Research Institute (ITRI) to develop a "Composite Water Quality Sensing System." This system enables simultaneous measurement and detection of parameters such as Chemical Oxygen Demand (COD), Suspended Solid Concentration (SS), Copper Ion (Cu2+) concentration, conductivity, pH value, temperature, and more. Employing UV light sterilization, it inhibits the attachment and growth of biological films on the sensing interface, preventing interference with sensor accuracy and extending the sensor cleaning cycle. With a design incorporating water sampling, optimized power management technology, and reduced reliance on frequent manual maintenance, the system achieves long-term operational efficiency. It has been successfully applied in various settings, including industrial zones, aquaculture, chemical plating lines, metal electroplating industries, and landfill sites. The system provides intelligent wastewater discharge management and real-time monitoring of processes, meeting the demands of low-carbon management and waste reduction.

Integrate dynamic (static) digital map data and network map services, also improve the efficiency of public construction review.

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.

Symbiosis of fishing and electricity is a new form of economic model that combines the creation of energy and the maintenance of industrial output combined with farming and green power generation. Optimize the land with "one-use, multi-use, farmland and agriculture". Use the bracket to raise the solar panel by several meters. In order not to change the breeding species, breeding operations and breeding activities, the development of solar energy will assist the upgrade of breeding fisheries.

Laplace Intelligent Technology's "Akashic Smart Multimodal Report System" is specifically designed for enterprise digital transformation, utilizing cutting-edge AI technology to transform complex data into precise, professional business reports. The system automatically analyzes enterprise information, rapidly generates structured reports, significantly reduces manual writing time, while enhancing report quality and decision-making efficiency. Our solution integrates intelligent knowledge bases with automation technology, helping enterprises optimize operational processes and achieve data-driven precision decision-making in highly competitive markets.

In Taiwan, religious activities create tens of billions of business opportunities every year, and up to 200,000 metric tons of joss paper are burned every year, generating 300,000 metric tons of carbon emissions, leaving a large amount of joss paper ashes. In the past, they were randomly discarded, causing environmental pollution. Now Jinjing solves the joss paper ashes problem, gives the ashes innovative value, and achieves a circular economy. This project takes “LIUQIU”, which has the highest density of temples in Taiwan, as the starting point. we work hand in hand with local temples to promote environmental protection and cultural inheritance. We aim to become promoters of religion, environmental protection, and local culture, and create cultural and creative products that integrate religion, beauty, and practicality.

1. Integrating data of water quality and water consumption, the online system will automatically conduct continuous data monitoring, and can be applied for both clean water and sewage water measurement. 2. Real-time monitoring: Seize real-time water information to maintain the stability of water quality and instantly react when abnormal condition is detected, dramatically increasing management efficiency. 3. Smart Dosing Scenario: Integrating automatic dosing equipments with upper and lower alarm settings to ensure dynamic stability of water quality and decrease labor cost. 4. Data Analysis: Apply schedule planning to build up the trend of historical changes and to develop the situation management model. 5. Compliance with the regulations: Complete the full-time management mode, in compliance with the regulations of the competent authority and environmental protection standards. 6. The water quality sensor (specific model) is automatically cleaned without additional consumables and can be cleaned frequently.

Safe Swim utilizes advanced AI technology to provide safety solutions for various aquatic environments.With SAFE SWIM Guard and SAFE SWIM Zone, the system adapts to different aquatic environments, using algorithms to accurately recognize movements in and around the water.It ensures 24/7, comprehensive safety monitoring, enhancing water safety and protecting every user’s life.

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.

By applying environmental sensing IoT technology and mobile sensors, the coverage of sensing can be significantly enhanced. With the analysis through AI algorithms, it assists governments in identifying potential sources of pollution for regulatory actions and pollution reduction measures. Meanwhile, supplemented by generative AI innovation technology, it achieves smart environmental governance.