1) Automatic Notification System 1. Consolidate the IOT info from various sensors, as well as history of user behaviors 2. Big Data Analytics & AI-enabled recommendation engine: Send delivery notice or abnormal alert 3. Push mobile APP message to User and Operator 2) Electronic Ordering System (Customized) 1. Planed delivery schedule service, user confirmed the delivery time, system automatically plans routing and deliveryman 2. Delivery schedule: Push individual mobile APP message to each deliveryman 3) Cylinder Management System (Customized) 1. Cylinder barcode APP scanning, Deliveryman scan the barcode and upload to cloud system 2. Automatic notification mechanism for expired cylinder 3. Data Analytics & Statistical Report 4) Safety Reporting System 1. LPG safety sensors: Including gas detector, Solenoid Valve, pressure switch and UVIR Flame Detector 2. IOT-BOX showoff Solenoid Valve and reporting 3. Push mobile APP message to User and Operator for emergency response 5) Cloud ERP System (Customized) 1. Modular management system: Accounting, Administrative, Financial, Procurement, Human Resource, inventory, Customer Service and sales management 2. Data collection, Analytics & Statistical Report

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.

AI智慧辦公室文件助手: 使用最先進的AI文件識別技術, 建立自動化文件處理系統, AI小幫手可替需求人員搜尋或自動生成所需要的文件。

Vehicle Classification enables transportation authorities to automatically identify and classify vehicles according to their visual attributes. This technology finds widespread application in traffic management systems, toll collection, parking facilities, and security setups. FETCi leverages AI algorithms and machine learning methodologies to analyze video data collected through LiDAR technology. With an extensive database and repository, FETCi's AI AVC proficiently sorts vehicles into distinct categories, including cars, trucks, motorcycles, buses, and more. By integrating LiDAR technology with AI-powered image recognition, FETCi establishes a vehicle recognition system equipped with self-enhancement and deep learning capabilities.

Millilab provides smart automotive in-cabin solutions, including both hardware and software as well as total solutions for CPD (Child-Presence Detection) and DMS (Driver Monitoring System). With our proprietary algorithms, our radar modules can distinguish between adults and children, helping to prevent incidents where children are left unattended in vehicles.

Our energy management system can generate energy management data chart, display real-time 3D status display. Usage fields includes "Air conditioning system", "lighting control system", "charging pile management system", "energy storage management system", "power management system". It reduces the customer's risk of integrating different system interfaces and improve overall energy use Efficiency, the system regularly sends "Energy Verification Report", "System Efficiency Report", "Maintenance Notice" and other information to comply with the information required by the Energy Management Act, ISO14064-1, ISO50001, ISO14067 and other standards, reduce labor costs and consolidate data time, and can interface with traditional SCADA system information to upload to the cloud, solving the problem that traditional systems cannot be remotely monitored, allowing customers to get twice the result with half the effort on the path of ESG, energy conservation and carbon reduction.

By the integration and utilization of IoT engineering information and sensor data about water resources management, air quality monitoring, disasters prevention and warnings…, we introduce end-to-end enterprise private networks to provide custom infrastructure systems and services for SMBs and public sectors.

1.Special design of water metering structure for users of high-rise building and smart houses. 2.Multiple water meters are connected in series to share the construction cost, which is most in line with economic benefits. 3.Graphical presentation of water usage data helps users manage water consumption. 4.Combined with the alarms of abnormal conditions, if there is suspected water leakage or suspected reverse flow, the system will take the initiative to inform. 5.Assist in water and water conservation management, and help users formulate exclusive usage warning ranges.

By applying environmental sensing IoT technology and mobile sensors, the coverage of sensing can be significantly enhanced. With the analysis through AI algorithms, it assists governments in identifying potential sources of pollution for regulatory actions and pollution reduction measures. Meanwhile, supplemented by generative AI innovation technology, it achieves smart environmental governance.

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.

This exhibition is an atmospheric physical-chemical grid model for prediction of changes in air quality, utilizing data from the U.S. NCEP global weather forecast and regional air pollutant emissions. Local scientific investigation data has been used to adjust and calibrate the model and thereby largely improve the accuracy of the air quality forecast over Taiwan. The system is capable of simulating the changes in air quality over the next three days (72 hours) in Taiwan, with a temporal resolution of 1 hour and a spatial resolution of 3 km. The simulated data can be integrated with air quality data from the Civil IoT Taiwan, informing regulatory authorities the changes in air quality for the near future, and key information for formulation of control strategies

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