The smartest sensor knows when to sleep.
EdgeWake is an ultra-low-power forest surveillance node. It remains in deep sleep 99.9% of the time, awakening only to verify and capture real threats using Edge AI.
Project Parameters
Severe power constraints in remote environments.
Forests lack grid infrastructure. Deploying standard AI cameras requires massive solar arrays and cellular uplinks. EdgeWake was required to solve this by creating a device that runs entirely on a single 18650 battery cell for over two years, while still providing high-accuracy visual evidence of fires or illegal logging.
Balancing AI latency with power consumption.
Running a Convolutional Neural Network (CNN) continuously drains batteries in hours. The challenge was architecting a mechanical "tripwire" (Flame/Vibration sensors) that uses near-zero power to wake the AI, solving the continuous-listening problem.
Prototype deployed and validated.
The current hardware stack (ESP32-CAM, INMP441, SW-420, KY-026) is fully available and costs under $15 per node. The firmware is open-source and the Telegram integration allows immediate global deployment without server hosting.
What can be added to the project.
Future development aims to incorporate LoRaWAN for extremely remote areas without WiFi coverage, adding solar-trickle charging for infinite theoretical battery life, and expanding the TinyML model to classify specific animal poacher signatures (gunshots/vehicles).
The 5-Tier Architecture
Parth Arsid
Full-Stack Developer & Entrepreneur. Expertise spans WordPress, Firebase, Flutter, Java, and hardware edge AI. Integrating LLM APIs (Gemini, OpenAI) and n8n workflows to build highly profitable, active ventures rather than basic test designs.