Real-time vibration monitoring and failure detection for rotating assets using cutting-edge edge and cloud computing technology.
Research-driven innovation in industrial asset monitoring
CondiCloud originated from PhD research at the University of Auckland, focusing on scalable, low-cost condition monitoring solutions for rotating machinery. By combining semi-supervised machine learning with edge-cloud architecture, we developed a system that requires only 20 seconds of healthy baseline data to detect failures in real-time.
Our approach bridges the gap between academic innovation and industrial needs, providing actionable insights for predictive maintenance while reducing costs by up to 90% compared to traditional solutions. The technology has been validated across diverse industrial assets including bearings, gearboxes, and turbines.
Comprehensive monitoring solutions for every industrial need
Advanced vibration analysis for pumps, motors, compressors, and turbines with real-time health scoring.
Machine learning algorithms that predict failures before they happen, optimizing maintenance schedules.
Local processing power that ensures immediate response times and reduces bandwidth requirements.
Everything you need for comprehensive asset monitoring
Continuous vibration monitoring with millisecond precision
Early warning system for potential equipment failures
Monitor your assets from anywhere with mobile apps
Comprehensive data storage and historical analysis
Intelligent notifications based on asset conditions
Rich visualizations and customizable reports
Get answers to common questions about CondiCloud
CondiCloud specializes in rotating equipment including pumps, motors, compressors, turbines, fans, and gearboxes. Our system can monitor any asset that produces vibration signatures.
CondiCloud has been rigorously tested and validated across 32 independent assets from five major datasets: NASA/IMS bearings (8 bearings), XJTU-SY bearings (15 bearings), IEEE PHM 2012 bearings (7 bearings), wind turbine bearings (1 bearing), and UNSW Spur Gearbox (1 gearbox). This diverse validation ensures robust performance across different operating conditions and asset types.
Edge computing processes data locally at the source, reducing latency from seconds to milliseconds, enabling real-time alerts, and reducing bandwidth requirements by up to 90%. Our edge devices use Raspberry Pi with custom ADC hardware for cost-effective deployment.
CondiCloud requires only 20 seconds of healthy baseline data to tune itself and begin monitoring. This self-tuning capability eliminates the need for extensive historical data or complex setup procedures, making deployment quick and straightforward.
Installation is simple and non-invasive. Our sensors can be mounted on assets in minutes, and the edge device connects to your existing network infrastructure via MQTT and Cloudflare tunneling for secure remote access.
Yes, CondiCloud offers APIs and integrations with popular CMMS, SCADA, and ERP systems. We support MQTT, REST APIs, and custom integrations.
Our low-cost edge-cloud architecture can reduce monitoring costs by up to 90% compared to traditional solutions. Customers typically see ROI within 6-12 months through reduced downtime, optimized maintenance schedules, and prevented catastrophic failures.
Contact us to learn more about implementing CondiCloud for your operations