-)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.

The need of video surveillance has increased with the issues of campus, public places security and intelligent transportation. What’s more, high-resolution image, identification, analysis and AIoT applications are getting popular than before. People are strict in the performance of transmission and computing. Internet communication technology has entered a new era as well. To achieve intelligent service, zMEC ’s platform as service through Kubernetes-based architecture which can not only integrate with the third-party but also expand different AIoT software application modules, such as identification and analysis, electronic fence. Besides, the technology of edge computing can reduce the demand of video and audio data for cloud center computing access and network bandwidth resources, so as to make up for the problem of traditional cloud computing delay and unsafe transmission link. It meets the need of high frequency bandwidth and low latency, and to satisfy the needs of information security and privacy protection.

Enables real-time patient monitoring, personal big data analysis, and machine learning for future AI Medicine applications.

The "Dosage Evaluation Method" applies AI technology to assess dosages for high-risk medications, using Vancomycin as an example. This method addresses limitations in clinical practice, where dosages are typically determined by physician experience or population pharmacokinetic parameters, which may not account for individual patient variability. Although several AI-based prediction models for dosage evaluation currently exist, most of these models directly suggest dosages, often without fully considering physician expertise. The innovation of this method lies in its approach to validating only the physician-selected dosage, providing reference feedback without influencing the physician’s final decision. This design not only respects the physician’s professional judgment but also enhances the safety of medication administration.

The Supplier and Investment Management Module is an extension of Carbon Star, allowing enterprises to manage not only their own carbon emissions but also conduct inventory and management of carbon emissions from suppliers or investment companies. The module features complete functionalities for carbon emission data inventory, registration, and management. Additionally, it offers comprehensive education and training services for enterprises regarding suppliers and investment companies. This enables enterprises to view and integrate supply chain data within the platform, and allocate and calculate data according to relevant criteria. The Supplier and Investment Extension Module includes the following functionalities: 1. Supplier greenhouse gas inventory 2. Supplier education, training, and guidance 3. Integration and management of carbon data within the supply chain

• Features: With integrated AI-based image recognition, ultra-wideband (UWB) wireless positioning systems, warehouse management systems, and cloud platform services, the solution features automatically, real-time, and intelligent benefits to assist enterprises to achieve smart logistics and digital transformation with the enhancement of management efficiency and energy sustainability. • Functions: The solution includes AI-based image storage location identification, dynamic vehicle dispatching, automatic route planning, and display of available storage space. • Benefits: Higher management efficiency: Increases the inventory management efficiency by reducing the warehouse order pick up time by 12% on average. Energy sustainability: The system is estimated to save more than 6000 kg of annual carbon emissions for a single warehouse. Environmental benefits: Reduce 12% Warehouse order pick-up time, as well as an estimated annual carbon emission reduction of 6000 kg for a single warehouse.

With our fiber sDAS, Wave-In effectively reduce mobile signal dead spots caused by insufficient base station coverage, buildings or electromagnetic signal interference. Due to the pandemic, Taiwanese Engineers weren’t able to assist with on-site installation and coverage testing, to solve this problem and improve efficiency, Wave-In utilized Mixed Reality for collaboration and remote assistance.

Applying our technologies portfolio to IoT system, we expand the diverse solutions with hardware, software and cloud services to custom reliable and cost-effective applications to incubate smart parks.

“FiduciaEdge Medical Information Guard System” is designed for P2P secure transmission between medical institutions, achieving high levels of privacy, accuracy, security, and real-time medical information transmission. It aims to address the current inadequacy of real-time sharing of cloud-based medical data and accelerate real-time exchange of medical information in emergencies. Additionally, the patented "T-REE Technology" ensures the security and privacy of data during the exchange process. Through the FMIG system, all cross-hospital medical data exchanges are carried out in a dedicated secure environment, where de-identification, data encryption, special format packaging, and other security mechanisms are performed. The data is then transmitted securely to partner hospitals using a zero-trust model, allowing them to use and provide cross-hospital services without the risk of violating patient privacy.

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.

The Sonora Plan is a presidential-level initiative aimed at fostering the development of the Sonora region through a focus on four key areas: 1. Developing Solar Power Plants and Supplying Green Energy: The plan emphasizes the construction of large-scale solar power plants to harness the region's abundant sunlight. This initiative aims to position Sonora as a leader in clean energy production, reducing carbon emissions and supporting the transition to green energy. 2. Science Parks and Public Infrastructure: The development of science parks and enhancement of public infrastructure are central to the Sonora Plan. These efforts are designed to attract high-quality investments, foster innovation, and create a conducive environment for technological advancements. 3. Strategic Development and Application of Mineral Resources: Sonora's rich mineral resources, including copper, gold, and lithium, are crucial to its economic potential. The plan focuses on the strategic development and application of these resources, particularly in supporting industries such as semiconductors and electric vehicles. 4. Talent Development to Support Local Industries: The Sonora Plan includes initiatives to develop local talent through education and training programs. By investing in STEM education and creating opportunities for skill development, the plan aims to ensure a steady supply of skilled professionals to support the region's growing industries.

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.