Business Problem
A U.S.-based wood stove manufacturer struggled to reliably detect when stove doors were open or closed. Their existing IR sensor system worked in normal conditions but failed in high heat — the adhesive holding the sensors weakened, causing them to shift and send incorrect data. The company needed a durable, low-maintenance, and privacy-friendly monitoring solution that could deliver accurate, real-time results even in extreme temperatures.
Technology Solution
IncubXperts engineered a computer vision–based edge AI system on Raspberry Pi 4, replacing heat-sensitive IR sensors with an on-device YOLOv8n model for accurate, real-time door status detection. Live PiCamera feeds are processed locally for low latency and full data privacy, with results synced instantly to Firebase. Wi-Fi enables remote updates, BLE supports secure local setup, and the modular design allows seamless integration with mobile apps and future IoT devices.
Technology Stack
Raspberry Pi 4, Python, YOLOv8n, PiCamera, Flask, Firebase Realtime Database, Wi-Fi, Bluetooth Low Energy
Benefits & Impacts
High Reliability
Maintains accuracy in extreme heat, eliminating sensor failures.
Enhanced User Experience
Provides real-time, trustworthy stove monitoring.
Lower Costs
Removes recurring hardware maintenance expenses.
Privacy First
Ensures sensitive video data stays on-device.
Scalable
Ready for broader smart device integrations.
TRUSTIMONIALS
Success Delivered, Trust Earned


