Monitoring, early warning & emergency rescue system
Health monitoring:
Powered by an IoT logic engine and big data modeling, enabling 24/7 real-time monitoring of equipment operating conditions.Establishes a proactive early warning mechanism.Accurately predicts potential risks and prevents issues before they occur.Significantly reduces failure rates and safety risks, ensuring stable and reliable system operation.
Intelligent dispatch:
Integrates data across fault-response knowledge base, workforce database, and spare parts inventory.
Enables dynamic linkage across the three databases with intelligent decision-making recommendations.Automatically generates optimal response solutions.Improves response speed and operational efficiency, reduces maintenance costs, and maximizes resource utilization.
Intelligent comforting:
Through the full-process visualization of the rescue operation, real-time and efficient interaction with trapped personnel is achieved, significantly improving the calming effect and psychological guidance capabilities, enhancing the sense of security of the trapped personnel, and effectively increasing the success rate of the rescue and user satisfaction.
Installation Supervision System
End-to-End Closed-Loop Smart Management:
Powered by IoT, big data, and AI technologies, the system enables traceable installation workflows, real-time construction monitoring, safety and quality early warnings, and multi-party coordination, forming a closed-loop project management system that enhances efficiency and strengthens engineering quality and safety assurance.
One Device One File / One Code Traceability:
Digitally archives all lifecycle data including factory documentation, certificates, construction drawings, installation records, commissioning data, and acceptance reports, enabling full lifecycle traceability.
Mobile Lightweight Field Operations:
Supports mobile-based field operations via smartphones and tablets, including work reporting, image upload, inspection confirmation, and offline reporting, significantly improving on-site efficiency and breaking spatial and temporal constraints.
Maintenance & Retrofit System
Intelligent Full Lifecycle Services:
Driven by AI and big data, it achieves intelligent early warning of installation anomalies, precise maintenance on demand, intelligent recommendation for old equipment renovation, and builds a smart service system covering the entire lifecycle. This continuously reduces operation and maintenance costs and enhances equipment operational efficiency and asset value.
Diverse Co-governance:
Break down information barriers within and outside the enterprise, achieve real-time sharing, dynamic evaluation, and closed-loop feedback of project execution status, establish a bidirectional evaluation mechanism between employees and the enterprise, promote efficient collaboration among multiple parties, and comprehensively enhance management efficiency and service credibility.
Whole-process quality control:
Based on the three dimensions of personnel, equipment, and projects, we establish a refined supervision system for the entire process. By standardizing the process, we strengthen the foundation of quality, ensuring service quality from the source and enhancing customer satisfaction and core competitiveness.
Spare parts management system
Intelligent Spare Parts Recognition:
Combines AR and AI recognition to accurately identify spare parts and automatically provide detailed information and maintenance manuals, improving field efficiency and reducing operational errors.
Preventive & Predictive Management:
Uses historical data modeling for demand forecasting, lifecycle analysis, and failure prediction, enabling scientific inventory planning and reducing stockouts and overstock risks.
Multi-System Integration:
Integrates ERP, MES, EAM, finance, procurement, and warehouse systems into a unified data platform, eliminating information silos and improving supply chain coordination.
Full Industry Chain Quality Management System
Covers all scenarios including construction site quality management, factory process quality control, defective product recall, lifecycle component traceability, BI analytics, and deep quality analysis.
Through full-domain data mining and professional reporting, it builds a closed-loop quality system spanning production to after-sales, significantly reducing quality costs, recall risks, and maintenance losses, while providing precise and actionable decision support for management. This enables a shift from reactive handling to proactive prevention.
Intelligent learning system
Full coverage: mobile-based training with ranking mechanisms to increase engagement and replace entertainment usage time.
Advanced technologies: VR training, AR/MR-assisted learning, and EEG-based evaluation.
Cost reduction: 47% improvement in training efficiency and 65% reduction in training cost.
