2025數位應用週 AI臺灣 創新無限

CIC is a fully automated camera inspection software capable of independently generating reports.
In addition to verifying whether each camera is functioning properly, it can also issue alerts based on image clarity. When a camera is affected by external forces—such as typhoons, earthquakes, or deliberate tampering—that cause abnormal positioning or angles, CIC immediately reflects these abnormalities in its reports and sends alerts.

CIC – Camera Integrity & Condition Monitoring System

Key Features

Automated Operation & Report Generation
The system runs fully automatically and regularly generates comprehensive reports, enabling managers to quickly understand equipment status without spending time manually reviewing footage.

Multiple Abnormality Detection Capabilities
CIC detects a wide range of issues including signal loss, black screens, image obstruction, camera movement, and more. It also manages seasonal occlusion problems—such as tree leaves gradually blocking the camera view after spring—by identifying when the percentage of obstructions in the image exceeds the defined threshold.

Simple One-Click Interface
Users can customize alert ranges and conditions based on their needs, ensuring immediate notification when issues arise. With just one click, the system performs updates and checks, offering fast and flexible operation.

By performing complete daily inspections, CIC significantly reduces manual patrol workload and automatically generates reports without human intervention. It identifies problematic cameras at the earliest moment, ensuring factory and environmental safety with no blind spots.

The Intelligent Workplace Safety System leverages AI-based video recognition, IoT sensing networks, and big-data analytics to establish a measurable, traceable, and auditable safety management framework. The system automatically detects personal protective equipment (PPE) compliance—such as safety helmets, reflective vests, and fall-protection gear—along with hazardous behaviors including crossing restricted areas, smoking, and unauthorized entry. It also identifies abnormal working postures and environmental risk factors, issuing alerts within milliseconds to significantly shorten emergency response times.

After implementation, enterprises can dramatically enhance workplace safety efficiency. A visualized backend dashboard provides real-time site video, historical violation statistics, risk-zone mapping, and trend analysis, enabling precise decision-making and continuous improvement. The system supports integration with existing surveillance devices and management platforms, offering flexible deployment that adapts to various industries and site requirements. This reduces operational costs while improving the consistency of safety oversight.

Intelligent workplace safety is more than a digital tool—it is a foundational infrastructure that strengthens occupational-safety governance, enhances audit transparency, and supports corporate compliance. It enables organizations to achieve higher standards of safety performance and regulatory adherence.

The AI Dressing Recognition Training System integrates AI-driven image analysis with SOP-based workflow modeling to automatically verify each step in the process of donning firefighting gear, safety protective clothing, and various PPE. The system accurately identifies equipment types, dressing sequences, buckle and fastening positions, and whether the gear is properly secured—effectively replacing manual inspection by supervisors and significantly reducing human error and inconsistencies in judgment.

During training, the system provides real-time feedback on dressing accuracy and generates a quantitative score upon completion. This allows employees to clearly understand their performance and improve their self-assessment capabilities. Managers can access backend data including training records, common error points, and proficiency distribution, making it a valuable tool for professional training and safety audits.

This system not only enhances the accuracy and efficiency of protective gear usage but also standardizes training procedures, strengthens safety culture, and helps organizations establish measurable, auditable, and traceable safety management standards—ultimately reducing operational risks across the board.

The Eri Technology Facial Recognition Training Module is built on an advanced deep-learning architecture and trained with large-scale, multi-scenario datasets. It can quickly and accurately identify facial features across diverse environments, maintaining high precision and stability even under strong lighting, backlighting, partial occlusion, or multi-person scenes. The module supports cross-platform integration, offering lightweight deployment and high-speed processing, enabling enterprises to adopt cutting-edge vision AI capabilities at minimal cost.

By adopting this module, businesses can immediately enhance operational efficiency and security. Automated identity recognition shortens manual verification processes, reduces error rates, and strengthens access control, attendance tracking, and customer flow analysis. More importantly, the system can be continuously optimized based on organizational needs, helping enterprises build a smarter, more efficient, and more reliable operational environment—laying a solid foundation for digital transformation.

Our License Plate Recognition (LPR) module is built on high-precision deep-learning technology, offering robust recognition capabilities across diverse scenarios and vehicle types. Whether it’s passenger cars, trucks, motorcycles, trailers, government vehicles, or even military, diplomatic, and other special-purpose vehicles, the system can accurately interpret various plate formats and numbering logic. It maintains stable performance in challenging environments such as rainy conditions, backlighting, nighttime, and high-speed motion, ensuring reliable operation across all deployment sites.

By integrating this module, enterprises can significantly improve access control and operational efficiency. From automated parking fee systems and gate control to logistics dispatching, traffic monitoring, and smart-city applications, automated license plate recognition reduces labor costs while increasing accuracy. The module supports flexible integration and can be rapidly deployed on existing systems, helping organizations build smarter, safer, and more reliable vehicle-management environments—and accelerating their digital transformation.