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PropTech / Industrial Maintenance
EquiPulse — Predictive Maintenance Platform
EquiPulse is an IoT and SaaS predictive maintenance platform for equipment and machinery in facilities — pumps, compressors, HVAC, generators, and elevators — providing real-time health monitoring, failure prediction, and field-ready maintenance workflows.
Project overview
- Real-time health scores across all monitored assets in one dashboard
- Equipment health overview
- Anomaly detection identifies issues before breakdowns occur
- Predictive failure alerts
- 7-day trend lines reveal degradation patterns for proactive maintenance
- Health score trend
- Technicians receive alerts, view history, and start inspections from their device
- Field maintenance workflow
The challenge
Facility equipment failures are typically reactive — operators discover problems only after breakdowns occur, leading to costly downtime, emergency repairs, and safety hazards. Manual inspection cycles miss early warning signs like vibration anomalies, temperature spikes, and runtime degradation. Without centralized health visibility, maintenance teams cannot prioritize preventive work orders across multiple assets and sites.
The solution
EquiPulse combines ESP32-class edge controllers with vibration, temperature, and runtime sensors to continuously monitor equipment health. Data flows via MQTT to a secure backend, is stored in PostgreSQL, and surfaced through a React/Next.js web dashboard and a dedicated mobile field app. Predictive analytics detect anomalies — vibration spikes, overheat trends, runtime degradation — and generate proactive work orders before failures occur, giving maintenance teams actionable intelligence in the field.
Technologies used
- IoT
- ESP32
- MQTT
- Predictive Analytics
- React / Next.js
- Node.js
- PostgreSQL
- Field Operations
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