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.

Founded in 1998, Openfind has been dedicated to helping businesses leverage communication and collaboration services. We offer a comprehensive range of solutions, including enterprise search engines, email, email protection, email archiving, auditing encryption, file sharing, as well as instant messaging and online collaboration. For Openfind's product line, we incorporated AI applications to offer customers a smoother and more secure user experience. To accelerate email processing efficiency, Openfind provides AI-powered features such as email summarization, writing assistance, and content rewriting. In email security and auditing, it can detect and prevent potential attacks and data leaks, while archiving all incoming and outgoing emails for future auditing purposes.

Civil IoT Taiwan is part of the government’s Forward-looking Infrastructure Development Program under the Digital Infrastructure category. With the collective effort of the National Science and Technology Council (NSTC), the Ministry of Transportation and Communications (MOTC), the Ministry of Economic Affairs (MOEA), the Ministry of the Interior (MOI), the Ministry of Environment (MOENV), the Ministry of Agriculture (MOA), the Ministry of Digital Affairs (MODA) and the Academia Sinica, the project aims to address the core needs of the public by prioritizing four key mission areas, namely air quality, earthquake, water resources, and disaster prevention and response. By leveraging AI and IoT technologies, the project strives to deliver well-rounded, smart living services to facilitate the government and the people to respond to the challenges in an ever-changing environment.

The rise of AI (Artificial Intelligence) and IoT (Internet of Things) in ICT technologies, has accelerated the development of many innovative applications in AIoT (Artificial Intelligence of Things), and that has completely revolutionized medical and healthcare industry’s existing operation process and business model. Our team of experts in ICT (Information and Communications Technology) has team up with the top medical industry partners in Taiwan across different industries, providing smart medical service with the latest AIOT applications. We aim to help hospitals and healthcare institutions to improve clinical care benefit and operation efficiency, while creating a more friendly, convenient, and comfortable medical environment to increase patient satisfaction. Chunghwa Telecom's smart healthcare solutions provide smart ward management system, smart vital signs station, smart broadcasting/ registering/ queuing information system, EPD electronic paper display application, robot solutions and smart building (such as communication, multiple payment, smart parking, energy saving, environment monitoring , access control and surveillance etc.), and other ICT application planning and construction.

【Smart Medical - Smart Cloud Rescue System】:Online pathology data helps emergency ambulance services and professional care in hospitals , it also break through geographical restrictions and share medical resources.

3. High-end line: full system is 307 or 316 stainless steel chassis. Model No.: AH6676D (316) - Successful Case: Installed at the perimeter of Taipower Plant, an offshore area. - Sony Starvis™ sensor with 2MP, 5MP resolution. - Different angle lens are available. IR LED range is up to 40 meter.

LanCore Intelligent Aquaculture Cloud System is a high-end product used in aquaculture fishery, with intelligent, high-efficiency and power-saving effects. Its main features are: (1) Integrate more advanced self-development software to achieve intelligent control, which can remotely control aerators, feeders, water pumps and other breeding equipment. (2) The intelligent scheduling control mode supports timing setting, numerical value setting, and dynamic operation adjustment. The power saving effect is quite significant, up to 60%. (3) Multi-scenario scheduling and dynamic operation adjustment, high-speed operation is used at night to increase the amount of dissolved oxygen. During the day, the aerator can be adjusted to run at low speed to activate water quality and create an excellent breeding environment. (4) The grouping control system is ideal for cross-field and large-scale fishery users. It is easy to build cloud control and realize energy saving.

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.

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.

Smart Traffic Control System: Traffic Congestion Improvement Project, AI Image Recognition and Management System

With the rapid growth of electric vehicles (EVs) in Taiwan, the demand for charging infrastructure is increasing. However, most developments focus on high-power DC fast charging systems, which face significant challenges. Complicated feeder application procedures and imbalances in urban power grids make it difficult to deploy medium and large-scale charging stations. While AC chargers (up to 22kW) are easier to install, they fail to meet the need for fast and efficient charging. To address these challenges, GREAT introduces the "Charging Silk Road" solution. This innovative system combines advanced energy storage systems (ESS) with fast charging equipment to enable independent power supply and reduce reliance on the public grid. By integrating renewable energy sources such as solar and wind power, the system maximizes energy efficiency and sustainability. Additionally, the solution features Vehicle-to-Grid (V2G) capability, allowing stored energy to be fed back to the grid during peak demand or emergencies, supporting grid stability. Through a distributed, multi-site deployment model based on independent microgrids, GREAT’s Charging Silk Road creates a flexible, resilient, and efficient green charging network, accelerating the transition to net-zero carbon emissions.

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.