• Data is collected manually from individual sensors, making real-time monitoring difficult
• Only simple visual and sound alarms are provided, with no remote alarm function
• Lacks data visualization functions and has inefficient UI/UX
• Can only integrate with specific brand equipment, limiting system scalability
• Provides only basic data storage functions, with no AI-based analysis
• Requires manual inspection for each device and does not support remote maintenance
• Operates only in specific environments, difficult to apply globally, and lacks multilingual support
• Improved data accessibility through real-time automatic data collection and cloud integration
• Added remote alarm functions via mobile push notifications, email, SMS, etc.
• Applied intuitive UI/UX design with dashboard customization support
• Strengthened integration with various IoT devices and MES, ERP systems
• Added AI and machine learning-based analysis functions for prediction and anomaly detection
• Introduced remote maintenance and automatic diagnostic functions for quick issue resolution
• Enhanced global applicability and multilingual support through cloud-based architecture
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