K430 is the new addition to ARBOR’s rugged handheld lineup, this Android based handheld device has keypad with numeric keys, built-in 1D/2D barcode scanner, and is equipped with a large 4850mAh battery, that will easily last for the entire working shift, suitable for warehousing, inventory, delivery and more.

Wearable laser therapy device combines with BLE and cell app to become the world’s first AIOT laser therapy device. Due to it is compact and easy to carry, cell phone app can text the users to use the protocol on time based on his using habits at any time and anywhere, which becomes a new helper of rehab in home-based medical programs and precision health.

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.

The technical solution of Foxtron Electric Bus combines domestic and international resources, each contributing its strengths： 1. It adopts Foxtron's self-developed VCU software, integrates and develops the EEA architecture for electric buses, and utilizes motors, batteries, and chassis suspension systems from international major manufacturers. In collaboration with domestic manufacturers, Foxtron designs and develops dedicated low-floor bus frames for chassis cooperation. 2. In the product design of electric buses, Foxtron identifies pain points in traditional buses and improves upon them. For example, traditional buses often have issues with rollover protection and numerous blind spots, as well as differential wheel rotation caused by wheelbase, leading to frequent traffic accidents due to visibility problems. To address these issues, Foxtron employs Computer-Aided Engineering (CAE) and NVH (Noise, Vibration, and Harshness) analysis to verify the design of various systems and components. This ensures the overall strength of the vehicle body and chassis, enhances passenger safety, and incorporates features such as panoramic image display and an electronic wide-angle rearview mirror with a blind spot detection system to solve driver blind spot issues. Additionally, to alert pedestrians and other road users to the risk of differential wheel rotation, Model T projects prominent light beams onto the ground during turns, marking the danger zone.

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

Integrate dynamic (static) digital map data and network map services, also improve the efficiency of public construction review.

We offer comprehensive ODM services for integrated AIoT elevator applications, supporting clients from design to mass production in creating customized smart elevator solutions. Our services include hardware design, software development, and third-party system integration to meet diverse application requirements. With our ODM expertise, clients can launch innovative products quickly, reduce R&D costs, and enhance market competitiveness.

AI on-site Earthquake Early Warning System A highly optimized system setting and design to sense earthquake P-Wave within 3 sec and through AI model to predict PGA and PGV immediately and send information to customer for further application Product Advantage -Customization by customer demand -Professional team to optimize system set up to avoid environmental noise and interference -Multiple system design to enhance system stability and efficiency -Close loop design for information security -AI model with best system set up for best performance in speed and accuracy -Evolving AI model with more data collection

The application of digital twin technology in building smart cities is becoming increasingly clear, serving as a crucial engine for driving urban transformation. In the development of smart cities in recent years, citizens can view the growth and development of the entire city, including population growth, new construction, and other major activities, in a 3D format, gradually emphasizing the concept of a virtual city. Digital twin technology can simulate disaster scenarios, including weather events and traffic accidents, assisting disaster response personnel in rapidly understanding the situation and optimizing the efficiency of disaster response. In recent years, with the advancement of aerial photography, simulation technology, and computing resources, The National Science and Technology Center for Disaster Reduction has leveraged advanced technology to create a mountainous flood inundation model system. This system enhances disaster warning and impact analysis, providing a comprehensive view of vulnerable settlements. It utilizes dynamic models and virtual-real integration, presenting alert information and disaster impacts through visual elements, contributing to informed decision-making in disaster situations.

TextileGPT is an AI platform specifically designed for the textile industry, combining TNet's historical expertise and professional knowledge to accelerate product launches, reduce development costs, and strengthen knowledge transfer. Built on the TNet knowledge base, it provides intelligent dialogue capabilities enriched with industry-specific knowledge to address various challenges. The platform supports processing multiple data formats, including PDF, PPT, DOC, XLS, and web content, and features a user-friendly interface for quick adoption. TextileGPT aims to tackle issues like talent gaps and difficulties in knowledge inheritance, driving innovation and efficiency to enhance competitiveness, making it a key enabler for the textile industry's future development.

Through Sensor Node, including water level sensor, rain gauge, data recorder and LPWAN transmission module, the system provides the information factors including water level , rainfall, inundation height inside and outside the water gate. Then transmit data to the back end system. The members in emergency center could do the best practices based on these crucial information

The Central Weather Administration (CWA) is the government agency responsible for earthquake monitoring and reporting in Taiwan. In order to reduce fatalities and property losses caused by earthquakes, a high-density real-time seismic network and the advanced earthquake early warning (EEW) system have been implemented and in operation. Currently, the CWA EEW system can issue the warning message in about 10 seconds after a strong earthquake occurring in or very near Taiwan. Starting from 2021, in order to further enhance the benefit of EEW to the practical earthquake hazard mitigation, the CWA has begun to develop the customized urban EEW system. By means of introducing the on-site earthquake early warning methods, and developing the artificial intelligence models. The systems, particularly for the big urban shallow earthquake, aim to further shorten the time of EEW to 7 seconds. That means it can give warning to the areas about 25 km away from the epicenter, and more people could be alerted before the destructive shaking.