The Track Safety Management System is primarily aimed at addressing safety concerns along the track. It provides real-time monitoring, statistics, and detection-triggered alerts for trackside environments including stations, level crossings, along the track, and slope areas. The goal of this management system is to establish early warning alerts and prevent accidents from causing damage. Through the intelligent AIOT recognition monitoring system, it detects and analyzes station pedestrian traffic, tracks pedestrians at level crossings, identifies passing vehicles and traffic flow, detects foreign objects at level crossings and activates alarms, monitors personnel lingering and debris along the track, conducts rockfall monitoring on slopes with a rain gauge, monitors the environmental conditions in equipment boxes, and oversees the operation status of level crossing equipment. The monitoring data and image information are transmitted to the management system platform for integrated management via fiber-optic networks, NBIOT, or mobile communication. Additionally, it provides central management personnel with real-time interpretation and remote control in case of anomalies.

- Zero-Code AI Security Enable enterprise-grade protection via an OpenAI-compatible API—no code changes required. Instantly defend against Prompt Injection and PII leakage. - Flexible Enterprise Guardrails Supports Inline and Shadow modes with Prompt & Response Guardrails to detect and block risky interactions in real time. - Scalable AI Governance Built for scale with auto-scaling, multi-tenant management, and seamless SIEM/SOC integration via Alert APIs.

Live crowd movement information is crucial in busy public spaces. Manual checks and basic sensors often lack accuracy and fail to keep up with real-time changes. The People Counting System uses AI video analytics and multi-sensor fusion. It delivers accurate, real-time crowd data. The system automatically counts people, tracks direction, monitors density, and provides instant alerts and reports. Deep learning ensures accuracy in low-light or crowded conditions. Multi-target tracking prevents double-counting. Edge computing and cloud-based management enable on-site analysis and long-term monitoring. Integrating cameras, infrared, Wi-Fi, and Bluetooth data improves detection and increases coverage. The system generates real-time heat maps, flow analyses, and historical records. These support layout optimization, entry regulation, evacuation planning, and efficiency. The system serves malls, transit hubs, campuses, parks, and public buildings. It is vital for smart cities. It replaces manual counting with intelligent management for better safety, responsiveness, and adaptability.

1. Integrating data of water quality and water consumption, the online system will automatically conduct continuous data monitoring, and can be applied for both clean water and sewage water measurement. 2. Real-time monitoring: Seize real-time water information to maintain the stability of water quality and instantly react when abnormal condition is detected, dramatically increasing management efficiency. 3. Smart Dosing Scenario: Integrating automatic dosing equipments with upper and lower alarm settings to ensure dynamic stability of water quality and decrease labor cost. 4. Data Analysis: Apply schedule planning to build up the trend of historical changes and to develop the situation management model. 5. Compliance with the regulations: Complete the full-time management mode, in compliance with the regulations of the competent authority and environmental protection standards. 6. The water quality sensor (specific model) is automatically cleaned without additional consumables and can be cleaned frequently.

EdgeLink-X is an AI-driven heterogeneous edge-network platform built to provide resilient, low-latency connectivity for intelligent transportation and railway environments. The system forms a multi-layer architecture that unifies field communications, sensing, video capture, and edge analytics into a reliable and adaptive communication framework. At the field level, IP110H and IP503H Lite IP radios deliver instant voice communication and group coordination for frontline personnel. Sensors and cameras are connected through the AG260 AIoT Gateway, while the AS710 Wi-Fi 7 indoor access point provides high-quality Wi-Fi coverage in stations, platforms, and passenger areas to enhance traveler connectivity. Long-range, time-synchronized backhaul is supported by the SP250 Series, ensuring stable, high-throughput wireless links across trackside and outdoor environments. At the core, the zMEC edge-computing platform performs real-time AI video analytics, abnormal-event detection, and rapid data distribution to minimize latency and support mission-critical responses. By integrating Wi-Fi, LTE, 5G, PTP wireless backhaul, and AIoT devices into a single cohesive system, EdgeLink-X enables applications such as slope monitoring, intersection intrusion detection, pantograph spark/wear monitoring, and onboard operational visibility—forming a robust foundation for next-generation safe and intelligent mobility.

The Sustainability Performance Management Platform assists enterprises in extending their management perspective from direct emissions to the entire value chain, ensuring the precise implementation of supplier sustainability performance management. The system features a comprehensive digital survey and data management platform, covering everything from questionnaire design, distribution, and response collection to multi-level approval and statistical analysis, enabling companies to integrate supply chain data with maximum efficiency. With flexible template design and year-over-year comparison tools, enterprises can track trends in key issues in real-time. The system supports diverse data entry methods and automated chart generation, while also offering seamless integration with sustainability reporting systems to enable automatic data updates. By leveraging this digital system, companies can establish a highly traceable data management process and significantly strengthen supply chain resilience. Core System Features: 1. Supplier and Stakeholder Performance Assessment: Digitally collect and audit various ESG indicators. 2. Automated Statistical Analysis and Comparison: Generate real-time visual reports to track annual performance trends. 3. Data Integration and Report Linking: Streamline data aggregation to accelerate the production of sustainability reports.

Under the theme “Economy Next,” the Ministry of Economic Affairs presents dual pavilions on AI and net zero, illustrating Taiwan’s vision for dual transformation. The Net Zero Pavilion showcases resilient green energy systems and low-carbon supply chains, while the Industries AI Pavilion highlights advanced technologies and smart applications that delivers concrete solutions across industries in hope of fostering collaboration opportunities with global partners.

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.

With 5G private network system integration provided by Wave-In Communication, Inventec is transforming its Taoyuan Factory into a 5G smart factory, creating highly intelligent and automated production lines with AI and IoT capabilities.

Prof. Ming-Yen Lin’s Team – A Prediction Model for Type 2 Diabetes Complications Our research group develops a decision-support prediction model for type 2 diabetes complications using data from over 163,000 Taiwanese patients. Integrating age, HbA1c, and other dynamic factors, the model estimates long-term risks of major complications and mortality, visualizes future trends, and supports personalized care planning to improve disease management and outcomes.

C.ai: Conversational service platform is recommended as the best autonomous solution for enterprises to implement LLM intelligent assistants and related applications. It features easy editing with No-Code/Low-Code, easy integration with internal and external systems, and a complete service interface. With LLM application compliance and governance, enterprises can choose to integrate various suitable language models to enhance AI implementation capabilities. It supports various communication software and browsers, completing design and launch in one stop.

Fire notification + Emergency notification video device Taiwan Secom Technology Group launched a combination of 119 fire notification device and emergency notification image system, integrated anti-robbery, disaster prevention,and video, through real – timeimage monitoring and recording the scene, to grasp abnormal conditions; 24-hour control service center Line, monitor the signal for abnormality at any time ; if there is any abnormal information, it is immediately transmitted to the 119 and 110 service centers to reduce disaster expansion; the communication host has automatic detection function, and the control service center immediately dispatches personnel to overhaul when there is a failure; a test button , At any time to check whether the system is normal, and automatically fax back to the test status.