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.

Self-developed wireless low-power high-capacity communication protocol, suitable for motion trajectory IoT devices that pursue high battery life and low latency, and can connect 2,000 devices at the same time

P-Waver Inc. is the global leader of AI on-site earthquake early warning system and structural safety monitoring system, providing earthquake early warning before earthquake, intelligent disaster mitigation measures, and structural safety monitoring after earthquake.

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.

Key Features & Highlights Intelligent Monitoring: Advanced sensors and AI record real-time exercise data, providing actionable insights for precision and safety. Data-Driven Training: Generates personalized plans and dynamically adjusts based on performance. Medical-Grade Reporting: Offers reports with exercise scores, stability evaluations, and improvement recommendations. Smart IoT Connectivity: Enables remote monitoring and data synchronization for smart healthcare solutions. Patented Technologies Eccentric Training Technology (Patent No: I840182): Reduces strain while improving muscle strength, ideal for rehabilitation and sarcopenia users. Maximum Strength Curve Measurement (Patent No: I838256): Dynamically adjusts resistance, enhancing safety and training efficiency. AI-Driven Training Plans: Creates tailored plans in seconds, ensuring personalized and effective workouts. Applications Medical Centers: Assists physicians in improving patient rehabilitation outcomes. Smart Gyms: Provides data-driven, personalized training experiences. Urban Health Systems: Supports public health initiatives through integrated smart solutions.

ASUS Ultrasound Imaging System is a software based ultrasound solution enabling qualified and trained healthcare professionals to visualize anatomical structures and fluid. Easy-to use interface and handheld availability meet requirements of use in clinical purposes and home/ community healthcare environment. (1)Imaging Modes:B mode, M mode, Color Flow, Power Doppler, PW Doppler. (2)Probes: Linear, Convex, MicroConvex, Phased Array, Endocavity. (3)Battery continuously operating time up to 4 hours.

Smart Safety Solution (During earthquake) P-WAVER works with partner to provide safety escape solution for people at home or at office through coordinated IOT device to deal with earthquake smartly in timely manner -Smart light guiding system -Smart broadcasting system -Elevator urgent stop system -Gas auto shutdown system These are already in service in some community, hospitals, arena, station, buildings.

As solar generation applications continue to evolve, ensuring stable equipment operation and maximizing generation efficiency have been a main concern for owners. The platform integrates AI-driven O&M technology with precise data analysis to provide comprehensive equipment monitoring, real-time anomaly detection, and intelligent maintenance recommendations. This reduces operational costs and significantly enhances overall power generation efficiency.

The Ministry of Economic Affairs, Department of Industrial Technology has commissioned the Industrial Technology Research Institute's Center for Smart Sensing and System Technology to develop a "Composite Long-Term Air Quality Sensor." This sensor is capable of simultaneously measuring particulate matter (PM2.5), ozone (O3), carbon monoxide (CO), volatile organic compounds (VOC), and other air quality monitoring parameters. The sensor utilizes optical detection methods to detect concentrations of suspended particulate matter (PM2.5) and ozone (O3) in the air. Innovative key technologies, including dual-channel micro-particle sieving, micro-particle signal feature recognition, LED dynamic light source stability, and multi-environmental factor compensation, are employed to enhance the sensor's lifespan and accuracy. Furthermore, semiconductor and micro-electromechanical (MEMS) technologies are utilized to create a micro-heating chip. This chip, combined with gas nano-sensing materials and a single-chip sensing control circuit, converts the detected gas sensing resistance changes into carbon monoxide concentration values for the detection of carbon monoxide (CO), total volatile organic compounds (TVOC), and other harmful and odorous gas concentrations.

The EUP Fleet Management System integrates ESG management, providing visualized reports and big data analysis to accelerate communication between the supply chain and transporters, ensuring effective ESG management and achieving carbon reduction goals. Through AI big data analysis, it automatically provides green ratings and compares carbon emissions with industry peers, enhancing market competitiveness and brand image. Additionally, cloud-based, digital, and automated management enables enterprises to easily monitor fleet emissions and develop carbon reduction strategies.

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”.

By leveraging AI digital twin models, we predict KPI performance to support decision-making for backup machine selection, enabling energy savings and operational efficiency. Explainable AI is used to analyze the parameters influencing KPI, revealing that air compressor efficiency is strongly correlated with its shaft bearings, highlighting the importance of predictive maintenance for these components. Additionally, an intuitive dashboard visualizes the relationship between demand and supply data, facilitating real-time decision-making and responsiveness. With the integration of LLM Agents, users can communicate seamlessly with digital twins through natural language, enhancing usability and interaction efficiency.