Risk AI: Predictive Industrial Hazard & Gas Monitor
Real-time IoT and predictive hazard dashboard analyzing rate-of-change atmospheric trends to detect toxic gas leaks prior to threshold breach.
01 // SYSTEM OVERVIEW
An industrial IoT safety monitoring system that couples hardware sensor arrays with real-time rate-of-change (slope) predictive algorithms to identify dangerous chemical surges (CO2, Acetone, combustible gases) well before hazardous saturation thresholds are crossed.
02 // PROBLEM SPECIFICATION
Conventional industrial gas alarms trigger only after gas concentrations exceed dangerous statutory thresholds, giving operators virtually zero reaction time to evacuate or initiate containment protocols.
03 // ENGINEERING SOLUTION
Developed an early-warning telemetry system utilizing ESP32 microcontrollers sampling at 2-second intervals. A backend slope analysis engine computes first-order derivative rates of gas concentration change, triggering predictive alerts while concentrations remain at non-toxic levels.
04 // SYSTEM ARCHITECTURE & DATA FLOW
ESP32 Multi-Sensor Cluster (MQ-Series, DHT, Optical) -> REST & WebSockets Telemetry Stream -> FastAPI Backend (Derivative Risk Engine & Anomaly Classifier) -> SQLite/PostgreSQL Time-Series Cache -> React Dashboard with Live Canvas Visualization.
05 // VERIFIED OUTCOMES
- [1]Predicted concentration threshold breaches minutes ahead of statutory limit alarms
- [2]Zero-latency visual emergency alert overlays dispatched instantaneously across active operator stations
06 // TECHNICAL CONSTRAINTS & CHALLENGES
- —Filtering out transient ambient temperature and humidity drift from chemical gas sensor readings
- —Achieving reliable sub-second WebSocket telemetry broadcasts under poor industrial wireless conditions
07 // ARCHITECTURAL TAKEAWAYS
- →Rate-of-change slope analysis is dramatically more informative for accident prevention than static threshold triggers
- →Sensor pre-heating cycles must be mathematically modeled and normalized to prevent false positive startup spikes