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”.

Our team has built predictive models based on whole transcriptome data from patients with advanced metastatic prostate cancer, focusing on two different mechanisms of action: androgen receptor antagonists and androgen synthesis inhibitors. These two types of drugs essentially offer only one chance of selection, as resistance to one renders the other ineffective. Using weighted gene correlation network analysis, we identified several gene modules correlated to specific drug responses. Then, we combined several machine-learning algorithms and constructed classification models for different drug mechanisms. Our goal is to use detection services to determine the most effective drug for patients before administration.

AIGym is a retraining equipment supplier that provides AI intelligent technology and digital weight modules. Through intuitive exercise measurements to create personalized exercise models, scientific training programs can be easily completed by users, and data comparisons can be made to track the results. Provides eccentric, general and ageing training modules, suitable for gyms, corporations, rehabilitation units and community centers. Rental or purchase options are available, and the software modules meet different needs.

GSS's Vital NetZero is a cloud-based carbon management system that supports international standards, such as ISO 50001 Energy Management System, ISO 14064-1 Organizational GHG Inventory, and ISO 14067 Product Carbon Footprint. It helps enterprises navigate compliance requirements amidst pressures from domestic and international net-zero policies, carbon tariffs, and supply chain demands, enabling enterprises to tackle compliance requirements, achieve net-zero emissions, and practice sustainability.

Smart Chiller control system integrated“Chiller”,“ECM Air Handling Unit”,“Direct Drive PM Cooling Tower”,“Variable Flow chilled Water Pump”and other equipment in satisfy operation and monitor power consumption in optimal power contract capacity. Different from traditional air conditioning system which would suspend operation upon occurrence of abnormality, TECO's system boasts active management "optimal energy conservation manage ment mode," capable of active alarming and adjustment, rather than response after occurrence of problem, thereby attaining the dual missions of "system energy conservation" and "automatic diagnosis."

LiftMind is a non-invasive AIoT elevator add-on system that enables rapid upgrades to smart functionality without modifying existing elevator control systems. The system leverages advanced external sensors and AI technology to deliver features such as passenger flow monitoring, emergency incident alerts, user behavior analysis, elevator operation optimization, and enhanced, user-friendly riding experiences. Its open architecture seamlessly integrates with Building Management Systems (BMS) and other IoT devices, significantly improving elevator management efficiency and user satisfaction. LiftMind supports a wide range of elevator brands and models, offering flexible adaptability to various application scenarios, making it the ideal solution for smart building upgrades.

Leveraging on-site equipment, process steps, control settings, and product status, we enable abnormality detection, scheduling simulations, root cause analysis, troubleshooting, and actionable scheduling suggestions. Virtual measurement enhances MES data quality, boosting SPC alarm accuracy to 95%. By integrating MLOps and AutoML, we connect factory MES, SPC, WAT, and scheduling data to deliver precise abnormality predictions up to 8 hours in advance.

Slimca HERE boasts three world-first features: (1)Ultra-Thin USB-C Connector: Supports standard USB-C cables, environmentally friendly and waste-free. (2)0.9mm Thickness: The same size as a credit card, incredibly thin. (3)15-Degree Bendable Design: Durable and flexible, won’t break in your wallet.

The device incorporates cutting-edge Edge control technology and is compatible with various sensors. • Independent Operation The device can operate independently even when powered off or disconnected from the network, ensuring continuous operation and functionality. • Remote Firmware Update and Configuration It allows for remote updating of firmware and configuration settings over the network, enabling easy maintenance and optimization of the device. • Data Storage and Transmission The device is equipped with capabilities for storing and transmitting data, facilitating the collection and transfer of information as needed. • LED Indicators The device is equipped with LED indicators for power and communication status, providing visual feedback on its operational status. 1.Model No: AIOT-C01 Fog Detection Controller Application Scope: Mountain Roads, Railways, Highway, Airport, etc 2.Model No: AIOT-C02 Rainfall Detection Controller Application Scope: Mountainous Area Water Level and Rainfall.

PD470 is industrial-grade Android handheld device. The rugged handheld enables 1.5m drop resistance and IP67 sealing level rate. It has built-in barcode scanners and a physical trigger button. This mobile computing device features multiple worldwide communication modes and has a 4000mAh high-capacity battery. PD470 weighs 243g only. It is slim, rugged, and explosion proof certified, making PD470 suitable for inspection in petrochemical plants, equipment, and construction areas.

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.

This exhibition is an atmospheric physical-chemical grid model for prediction of changes in air quality, utilizing data from the U.S. NCEP global weather forecast and regional air pollutant emissions. Local scientific investigation data has been used to adjust and calibrate the model and thereby largely improve the accuracy of the air quality forecast over Taiwan. The system is capable of simulating the changes in air quality over the next three days (72 hours) in Taiwan, with a temporal resolution of 1 hour and a spatial resolution of 3 km. The simulated data can be integrated with air quality data from the Civil IoT Taiwan, informing regulatory authorities the changes in air quality for the near future, and key information for formulation of control strategies