IoT+AI Services: Unlock Value from Industrial Equipment Data, Predictive Maintenance Reduces Unplanned Downtime by 40%–70%
Predictive maintenance can reduce unplanned downtime by 40%–70% and maintenance costs by 25%–35%. IoT+AI services enable industrial sites to achieve equipment data collection, predictive maintenance, energy optimization, and quality alerts, with deployment per production line completed in 6–10 weeks.
Book a Free AssessmentCore Capabilities
From data acquisition to AI decision-making, end-to-end industrial intelligent solutions
Device Data Acquisition
Full protocol access for PLCs, sensors, gateways, MES, supporting industrial protocols like Modbus, OPC-UA, MQTT.
Edge Anomaly Detection
Real-time inference at the edge with millisecond-level anomaly detection, reducing cloud latency and bandwidth costs.
Predictive Maintenance
Based on time-series data such as vibration, temperature, and current, provide 48-hour advance warning of equipment failure.
Energy Consumption Optimization
AI model identifies energy consumption anomalies and optimization opportunities, average energy saving of 15%-30%.
Intelligent Alert Linkage
Multi-source alert aggregation, root cause analysis, and automatic work order dispatch, reducing alert response time by 80%.
Quality Early Warning
Real-time monitoring of process parameters and quality prediction, reducing defect rate by over 50%.
Edge-Cloud Collaborative Architecture
Adopting a 'Device-Edge-Platform-Application' four-layer architecture, edge handles real-time inference and data sync on network recovery, cloud handles model training and global optimization, balancing real-time performance and intelligence.
- Full protocol coverage: Modbus / OPC-UA / MQTT
- Edge AI inference, millisecond response
- Data sync on network recovery, zero data loss
- Digital twin visualization
Implementation Process
From site survey to continuous iteration, professional team support at every step
Site Survey
Understand device models, communication protocols, and current data acquisition status, formulate integration plan.
Data Acquisition Deployment
Install gateways, configure protocol adaptation, achieve real-time device data upload.
AI Model Training
Train predictive models with historical data, cross-validate to ensure accuracy.
System Integration and Go-live
Deploy monitoring dashboards, alert rules, and work order linkage, go live after phased verification.
Continuous Iteration
Online model learning, new device integration, continuous feature optimization.
Industry Scenarios
AIoT solutions validated across multiple industries
Manufacturing Plant
Scenario：Predictive maintenance for production line equipment
Unplanned downtime reduced by 70%, annual maintenance cost savings over 2 million
Energy Management
Scenario：Intelligent optimization of factory energy consumption
Comprehensive energy consumption reduced by 22%, carbon emissions reduced by 18%
Safety Production
Scenario：Real-time monitoring of hazardous chemical areas
Leak risk identified 30 minutes in advance, zero safety incidents
Unlock the value of your device data
Book a free diagnostic, and our IoT+AI experts will evaluate the value of your device data on site.
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