FET Energy Management System(EMS) is able to generate electricity consumption analysis and gives advice on electricity saving with electricity meter and environmental sensors. It can be expanded and integrated with electromechanical control or renewable energy facilities to automatically save electricity. FET EMS can be used in buildings, chain stores, factories and also campus. Features * Easy to compare the power consumption trends by MoM / YoY / Dist. / building * Support TaiPower Open ADR protocols, enable utilities to cost-effectively manage growing energy demand & decentralized energy production

LanCore Intelligent High-efficiency Aerator is used in aquaculture and has smart control and energy-saving functions. Its features are: (1) adopting Brushless DC motor or PMSM, and comes with a FRP reducer. (2) it is suitable for high-speed operation and able to support long-distance wiring (300 meters). (3) It is of high quality and has obtained 2020 energy-saving certification, which can save 40–45% of total energy consumption. (4) Smart fish farming, users can monitor and control remotely through a mobile phone to manage operation status and set schedules. (5) General fish farmers can easily import this product to achieve intelligent control and energy-saving benefits.

AI air-conditioning energy-saving technology controls existing systems to achieve an energy-saving rate of 10%-30%. It can be applied to energy-saving solutions for air-conditioning systems, heat pump hot water systems, and information room systems. This service has been used in Taipower Building, Taipei Post Office, and the two national agencies, and has achieved 25%-60% air conditioning energy saving rate. This service has the characteristics of "smart", "low cost" and "immediate effectiveness". It does not rely on the energy-saving strategy of "hardware replacement “, but focuses on "software implement" to achieve "rapid deployment" and "short payback period". ”, “effective energy saving”.

C.ai Chatbot Service Platform is recommended as the best autonomous solution for enterprises to implement LLM intelligent assistants and related applications. It features easy editing with No-Code/Low-Code, easy integration with internal and external systems, and a complete service interface. With LLM application compliance and governance, enterprises can choose to integrate various suitable language models to enhance AI implementation capabilities. It supports various communication software and browsers, completing design and launch in one stop.

The cleaner the sorting of recyclables in the resource circulation process, the higher their reusable value. We leverage the most advanced AI vision recognition technology to introduce innovative applications into existing production lines. Our systems automatically inspect the targets to ensure the purity of sorting, thereby increasing the reusable value and maximizing profits for the factories. By collecting and training with actual production line image data, we continuously update the dataset to handle various compositions of recyclables. Our vision recognition equipment features low-power hardware that can be easily and simply installed onto existing production lines. Additionally, we can create diverse labeling data for various recyclables.

Taiwan's first domestically developed 5G O-RAN system integrates with Oceanic & Meteorological Applications to collect environmental data related to oceans and geology. Through the analysis of this environmental data, the system anticipates the overall conditions of offshore wind power fields, facilitating operations in offshore wind power. This integration aids in minimizing the needs of offshore patrols and contributes to the establishment of data system for Taiwan's marine energy environment, serving as a foundation for sustainable environmental development.

Civil IoT Taiwan is part of the government’s Forward-looking Infrastructure Development Program under the Digital Construction initiative. With the collaborative efforts of the National Science Council, Ministry of Environment, Ministry of Economic Affairs, Ministry of Agriculture, Ministry of Transportation, Ministry of the Interior, Ministry of Digital Affairs, and Academia Sinica, the project is jointly executed across departments, prioritizing four key areas: air quality, water resources, earthquakes, and disaster prevention and response. By leveraging artificial intelligence and IoT technologies, various smart living services are developed to assist the government and the public in jointly addressing the challenges brought by environmental changes. By combining the innovative power of industry, academia, and research, the project aims to develop the IoT industry ecosystem and export solutions internationally.

The diagnosis of ADHD is based on the core symptoms appearing in DSM-IV or V criteria. In addition to the criteria, some physicians use checklists to assist the diagnosis of ADHD. However, either symptoms or checklists are subjective, which leads to diagnostic problem. In this product, data from the gyroscope and accelerometer in a smart watch were used to analyze the movements of children with ADHD. The children with ADHD and controls wore the watches on their hands simultaneously in class and compared the data from recorders for analysis. This method can help us to establish a objective tool for diagnosis and evaluation of ADHD.

WeatherRisk provides tailored energy forecasting solutions for the energy industry, including: 1. High-resolution, bankable historical data (metocean, solar irradiation) 2. Weather forecasting systems for O&M (offshore wind farms, solar assets) 3. Solar power forecasting (solar assets and grids) 4. Wind power forecasting (wind farms and grids) 5. Load forecasting Energy forecasting has a wide range of applications in the energy industry: • For FTM (front-of-the-meter) power dispatch, ancillary services, asset evaluation, and PV-Storage. • For BTM (behind-the-meter) virtual power plants, microgrids, renewable energy trading, as well as strategic support for energy market operations.

1. Directly driving fans with a motor increases transmission efficiency and highlights the superiority of direct drive systems over traditional transmission systems, especially when combined with a variable-speed control mechanism and at lower rotating speeds. 2. The absence of mechanical components in a direct drive system eliminates the need for regular maintenance of the reducer, gearbox, and transmission shaft, as well as reduces the risk of oil leaks. This results in lower maintenance costs, longer product life, and reduced operating costs for customers. 3. Installation of TECO's proprietary inverter for cooling tower can reduce operating noise, buffer activation, and lower mechanical impact. 4. A 30 kW motor in constant-frequency operation can reduce total operating costs by up to 18% over a five-year period.

Delta's smart city solutions are based on three main axes: smart park management, smart light poles, and community security monitoring: smart park management uses a cross-system city information integration platform that handles a wide range of data transmission, aggregation, visualisation, and analysis to help achieve the goals of smart city governance. Intelligent light poles provide low-carbon lighting services in the parks, and at the same time serve as information collection and transmission nodes for the intelligent Internet of Things, while security surveillance protects people and assets in the parks and the city from infringement. Delta's smart city solutions help customers achieve a better smart city with both technology and humanity.

Our AI server features several advanced patented functionalities: • Ensure the Privacy of Local Data: Patented trusted computing protection mechanisms ensure data security and privacy. • Protect Local AI Models from Theft: Prevents locally deployed AI models from being stolen, safeguarding corporate intellectual property. • Specialized LLM Compression Technology: Efficiently processes large AI models, enhancing performance and reducing resource requirements. Enables the use of NVIDIA A-series GPUs in place of H-series GPUs, significantly reducing hardware costs. • Reduce Enterprise Deployment Costs and Energy Consumption: For example, when training a 13B model, GPU requirements can be reduced from 7 H100 GPUs to 2 A6000 GPUs, significantly lowering costs and energy consumption. Our solution not only ensures the security and privacy of corporate data and AI models but also reduces the costs and energy consumption associated with AI deployment, making it an ideal choice for enterprise users.