Companies spend 10s to 100s of thousands of dollars to ensure that critical failures in components don’t cause downtime with highly redundant systems. If a system could be designed that would, through various external signals that would not be dependent on system functionality, predict that parts were near to their end-of-life or in need of repair, the system could solve maintenance issues before they happen. This would provide the uptime of a redundant system, without being redundant, saving huge costs. Predictive maintenance is an emerging field, and this project aims to use field programmable gate arrays (FPGAs) to collect high resolution external signals, and run inference on the data highly efficiently, to predict HVAC system failures before disaster.

Administrators can review fleet health, coordinate work across teams, and keep everyone focused on the assets that matter most. This product is designed for business readiness and operational clarity across your enterprise.

Team members can quickly see their assigned devices, understand current status, and stay informed without navigating complex maintenance tools or device-specific dashboards.

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