1.Integrate smart water meters, wireless communication interfaces, and online management system to supply a comprehensive solution. 2.Suitable for management of water supply in cities and water consumption in areas like schools, and shopping malls, etc. 3.Real-time monitoring: Integrating GIS information, the system can help users to seize instant water data. 4.Data Analysis: Integrating comparison of water consumption in multiple durations and water balance application to improve leakage and decrease Non Revenue Water(NRW). 5.Abnormal Alarm: With configurable setting of upper and lower limits for water consumption, the system will send a warning message to users when the amount exceeds the acceptable range. 6.Individual Billing: For shopping malls and dorm rooms, the solution can assist managers to independently calculate consumption amount for each vender and household, making billing fair and reasonable.

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.

Handling abnormal complaints requires extensive experience and expertise. However, the resignation or retirement of senior employees often leads to knowledge loss, impacting organizational efficiency and competitiveness. Through vector models, Morale AI transforms unstructured data (such as emails, PDFs, and Word documents) into structured data and integrates it into databases, enhancing data usability. Multi-modal models combine diverse data types, including text and images, to systematically record and preserve experience. By leveraging Retrieval-Augmented Generation (RAG) technology and similarity search, the model can accurately categorize issues, identify the root causes, and recommend relevant cases, significantly reducing manual processing time and error rates. This systematic approach not only enhances response efficiency and enables real-time analysis and resolution of customer issues but also reduces repetitive work for employees, improving overall productivity and customer satisfaction.

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.

MIRDC’s continuously Rotating Wind Turbine UAV Inspection System can effectively inspect the working wind turbine without interference. It takes 5 minutes to complete the inspection of a single blade to effectively detect 4mm small cracks. The system will not lose power generation by turning off the wind turbine, further observes the actual movement status of running blade structure and pillars to grasp the defects beforehand.

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.

The "Dosage Evaluation Method" applies AI technology to assess dosages for high-risk medications, using Vancomycin as an example. This method addresses limitations in clinical practice, where dosages are typically determined by physician experience or population pharmacokinetic parameters, which may not account for individual patient variability. Although several AI-based prediction models for dosage evaluation currently exist, most of these models directly suggest dosages, often without fully considering physician expertise. The innovation of this method lies in its approach to validating only the physician-selected dosage, providing reference feedback without influencing the physician’s final decision. This design not only respects the physician’s professional judgment but also enhances the safety of medication administration.

Introducing LIVA smart charger, which complies with ISO/IEC 15118 and supports Plug-n-Charge. It simplifies the charging procedure and makes a joyful charging experience. Forget about cash or cards and charge your EV that easy!

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 project uses the 阡陌(QianMo) System, which drawing the road profiles, markings, signs, and signals based on the road geography data as a universal base map, to integrate cross-domain digital applications. Besides, 阡陌(QianMo) System has developed an application on mobile phone, through this application, user can complete the case opening, drawing, conversation recording, and photo-taking operations on-site, and convert the accident cases into collision elements in accordance with time, vehicle type, direction, collision type, and number of casualties. On the other hands, when handling improvements for accident-prone intersections, 阡陌(QianMo) System can overlay the elements to implement the collision composition analysis serves as a scientific proof and visualization tool for researching traffic improvement measures and explaining accident risk hotspots. Besides, after the subsequent engineering improvements, user can provide revision of road geography data as the feedback. Through this mechanism, which can achieve a digital governance cycle. Finally, through 阡陌(QianMo) System , this project integrates cross-domain applications related to police administration, transportation bureau, and engineering industry to improve driving environments and prevent traffic accidents.

Huijia Health's nFOPT® non-invasive optical fiber physiological monitoring technology and new generative AI smart care system provide 24-hour safety and health management solutions for all ages from infants to the elderly. nFOPT® technology utilizes the total reflection principle of optical fiber data transmission, has no electromagnetic wave interference, and has high sensitivity and high precision physiological sensing capabilities. Combined with the generative AI system, it can actively and intelligently monitor various physiological indicators, including respiration, heart rate, pulse, sleep status, cough frequency, blood pressure, etc., and can be applied to smart cushions (such as clothing, pillows, mattresses, cushions), Smart assistive devices, smart care systems, smart driving and other scenarios.

The Autonomous AI Surveillance Drone is a major innovation in drone technology, combining multirotor and fixed-wing capabilities. Utilizing white noise principles to enhance lift and efficiency, it enables high-speed flight and wide-area coverage, making it ideal for disaster response, border patrol, and other critical missions. Its core AI algorithm ensures reliability through real-time error detection. If anomalies are detected, the drone activates a safety mode, automatically returning or landing to minimize risks and maintain mission continuity. The flight control system integrates AI chips and edge AI technology, enhancing processing speed while reducing energy consumption for extended, efficient operation. These advancements enable stable autonomous flight even in complex environments.