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.

Our platform, TradeTioh (Taiwanese for “found it”), focuses on the local Taiwanese market. Through customized matchmaking services and technological innovation, we offer two-way matching features, real-time communication tools, and data-driven optimization algorithms to help buyers and suppliers quickly establish cooperative relationships. Looking ahead, we will continue to enhance our platform technologies and expand into international markets, aiming to bring long-term value to Taiwan’s manufacturing industry. On the TradeTioh platform, buyers can submit their procurement needs, and our core AI-driven technology will analyze the requirements and process them through our big data backend. The system then recommends the most suitable supplier candidates. Buyers can use the built-in messaging tool to directly contact the selected suppliers. The entire process takes only a few minutes—powered by TradeTioh’s core technology—making it far more efficient than traditional methods such as browsing websites, flipping through directories, or relying on referrals.

The system developed by this project provides a smart solution for station including digital fence system, platform pedestrian flow analysis, animal tracking expelled system, track water situation analysis system and platform digital information signage. The platform comprehensively analyses the image of around the station, train coordinates, passenger entry and exit, and water depth etc. Which can be used for follow up review and improvement of abnormal events such as track intrusion, crowd congestion and road flooding to achieve optimal train operation configuration and class spacing control. And provide abnormal event warning and troubleshooting and passenger intelligence information services. After the integration of multiple subsystem through the IOC platform, the system will automatically alert an alarm to the traffic control center and announce the train near the area to remind the driver to pay attention to the situation and enhance the safety of the train and the people or cars in the area when the detection system alarms.

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.

The Ministry of Environment has promoted the deployment and application of the Internet of Things for empty product sensing since 2017, and has deployed approximately 10,000 sensors to make up for the deficiencies in time and spatial resolution of standard monitoring stations. Among them, in 2022, it expanded from the Taiwan island to Lienchiang County on the outlying Island. Its unique geographical location is more conducive to early warning of transboundary pollutants and reminds people to take precautions in advance.

Z-COM has invested in heterogeneous network integration R&D for years. Through partnership with global leading Telco operators, we’ve accumulated abundant experience in telecom system integration with Wi-Fi- extended broadband network, to offload traffic from 3G/4G mobile networks as well as providing mobile network coverage with less cost. Over the years, Z-COM’s carrier grade solutions are used to deploy massive scale of Wi-Fi hotspots and various applications for smart city. The new Z-COM carrier-grade wireless network solution introduces Software Defined Network (SDN) architecture, with Edge Computing concepts for Artificial Intelligence of Things (AIoT) applications. The solution offers higher wireless bandwidth, separates control and data plane for edge computing, that provides customized products equipments and software with compatibility, stability, scalability, and security for mobile network operators. Z-COM solutions offer best cost/performance value, with rapid deployment and easy management tools that help telecom operators reduce capital investments and operating expenses, accelerate cost recovery and increase profits.

Robotiive is an AI Computer Vision powered Industrial automation (RPA) solution that builds the foundation of your smart factory. By automating manufacturing processes and workflows, upgrading your legacy equipment, and reducing human workload, it builds upon your existing systems and ensures nothing is left behind in the age of digital transformation.

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.

The imbalance of agricultural production, sales and labor shortage have always been a huge challenge for farmers. The independent 5G private network with O-RAN effectively introduces affordable smart agricultural system through a leasing model, combining AI, unmanned vehicles, image recognition and other field information to upgrade smart farm production management system and increase the revenue.

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.

Traffic approach warning system is the combination of smart detectors and LED warning signs. The intersection is divided into detection lanes and warning lanes. Smart detectors are installed on the detection lanes. When a vehicle enters the detection area, the signal is transmitted to activate the LED signs on the warning lane to warn drivers to slow down in advance.

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”.