Our core product, AI-Stack, is a leading AI infrastructure management platform, essential for businesses adopting AI services. It integrates third-generation GPU partitioning, GPU aggregation, multi-node computing, a new user interface, multi-cloud management, open-source deep learning tools, and environment deployment features, helping enterprises tackle the challenges brought by fast-paced AI advancements.

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.

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.

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

The BSMX series of early warning modules for lithium battery thermal runaway, developed by Taiwan Intelligent Pollutant Sensing Co., Ltd., is a next-generation BMS upgrade solution that requires only simple installation to integrate with existing systems. The module is equipped with high-sensitivity sensors developed specifically for energy storage safety applications, with a rapid response time of as fast as three seconds. The module offers multiple signal output interfaces to choose from and features a proprietary smart algorithm that eliminates the need for calibration after installation. It is particularly suitable for energy storage systems that operate continuously for long periods and are difficult to maintain

In order to enhance the efficiency of irrigation water management in Hsinchu, the Irrigation Agency (IA) applies low-power sensors, remote control systems of water gates, and gate inspection systems to the irrigation management of the Zhudong Canal. The IA combines water gauges with the low-power NB IoT transmission module to monitor the real-time water level. Meanwhile, with the remote control systems of water gates, the real-time opening and closing of water gates can be operated through the "Platform of IA for Remote Monitoring and Management of Water Gates", making the operation of irrigation management more labor-saving and convenient. In addition, installing NFC tag cards allows to fill out the information and transmit the inspection results of water gates through an inspection APP, enhancing the efficiency of gate management.

The BSMX series of early warning modules for lithium battery thermal runaway, developed by Taiwan Intelligent Pollutant Sensing Co., Ltd., is a next-generation BMS upgrade solution that requires only simple installation to integrate with existing systems. The module is equipped with high-sensitivity sensors developed specifically for energy storage safety applications, with a rapid response time of as fast as three seconds. The module offers multiple signal output interfaces to choose from and features a proprietary smart algorithm that eliminates the need for calibration after installation. It is particularly suitable for energy storage systems that operate continuously for long periods and are difficult to maintain. E-bike version has a significant improvement in power consumption.

Using world-class 5G and new technologies, FET builds a "5G telemedicine platform" to provide mobile, zero-day telemedicine services.In this year, 5G telemedicine services spread across 12 counties and 33 districts. During the Covid-19 period, we have also assisted many hospitals to remote clinical services and smoothly carry out routine medical treatment. Features * Real-time Telemedicine service to empower remote area medical resource * Support medical IoT devices * Highly system integration characteristic to hospitals * Newly introduced patient function to meet the demand during the epidemic * AI intelligent analysis to assist physicians in diagnosis * Full-time video recording to ensure doctor-patient relationship and information security * Support virtual NHI card

Intelligent Positioning System can remotely track the paths, remotely set the access authority, and provide the access alarm and SOS alarm based on configured location Bluetooth sensors. There are three applications: [Guardian Wristband] Authority can know whether home quarantine people are at home. Through the beacon wristband connects with receiver. If home quarantine people are leaving home, the system will send notification to the authority. [Indoor Navigation] Locate users’ position via Bluetooth and precede indoor navigation to let users know their position and find the way in building. This service is applicable to large areas such as airports, stations, department stores, etc. [Intelligence on People Seeking] With smart positioning wristband, users can instantly know current location of their children or parents via App. It could avoid the common problem of missing family.

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.

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.

Currently, the prognosis of critically ill patients in the intensive care unit (ICU) is often assessed using the APACHE or SOFA scoring systems to predict mortality rates. However, these systems have been in use for over 20 years, and the data they are based on is outdated. Today, clinical data is more abundant and precise, and advancements in machine analysis capabilities have made traditional scoring systems insufficient for meeting the demands of accurate predictions and personalized medicine. To address this, our team has developed a survival prediction device for critically ill patients. Using an AI algorithm model, it utilizes clinical data such as physiological, laboratory, and examination results to predict the patient's survival rates for the next 30, 60, and 90 days, providing a more accurate reference for prognosis assessment and medical resource allocation.