Industrial IoT Fire Analysis Module
Neural guardian of industrial safety with 50ms response time.
Neural guardian of industrial safety with 50ms response time. Edge AI solution processing smoke and heat data in real-time, reducing false alarms to 0.01%.
Traditional fire detectors caused serious safety gaps in industrial environments due to high false alarm rates and slow response times.
We developed a custom TensorFlow Lite model running on STM32 microcontroller. The system processes smoke density, temperature change, and particle analysis data in real-time, making decisions in under 50ms.
The system provides wireless communication up to 2km+ with LoRaWAN protocol and is ATEX Zone 1 certified for safe use in explosive environments. The 4-layer PCB designed in Altium Designer ensures EMC compliance.
Challenge
Traditional detectors 15%+ false alarm rate and 5+ second response time created safety gaps in industrial facilities.
Solution
Edge AI with multi-sensor fusion algorithm. Real-time processing of smoke, heat and particle data. False alarm 0.01%, response time <50ms.
Technical Specifications
| MCU | STM32H743 480MHz |
| Memory | 1MB Flash, 1MB SRAM |
| AI Model | TFLite 128KB |
| Communication | LoRaWAN Class A |
| Battery | 3.6V 19Ah Li-SOCl2 |
| Protection | IP67, ATEX Zone 1 |
| Temperature | -40°C ~ +85°C |
| PCB | 4-layer, EMC Compliant |