AI components
Model: YOLOv8 (You Only Look Once, version 8) Why YOLOv8? Lightweight & fast → suitable for real-time detection. High accuracy in object detection tasks. Can be trained to specifically recognize elephants from images/videos. How it works: Sensors or camera capture frames. YOLOv8 runs on a connected device/server. Identifies if the detected object is an elephant (vs. human, cow, vehicle, etc.). Optimization: Quantization & pruning for smaller model size (to run on limited hardware).
IoT Hardware
- Microcontroller: ESP32 (low-cost, Wi-Fi + Bluetooth enabled).
- Role in system: Collects input from motion/thermal sensors or cameras. Sends data (alerts/frames) to the AI processing unit or cloud. Triggers alarms locally (siren, LED, speaker).
- Why ESP32? Low power consumption → suitable for solar or battery-powered setups. Built-in Wi-Fi → direct communication without extra modules. Supports integration with sensors & cloud IoT platforms.
Sensors and Communication Layer
- Sensors Used (Examples you can highlight) PIR Motion Sensor → detects movement near the road. Thermal/IR Sensor → identifies heat signatures at night. Camera Module (optional) → captures frames for YOLOv8 analysis. Acoustic Sensor → detects elephant trumpeting sounds.
- Communication Layer ESP32 sends data via: Wi-Fi (to local server/cloud). LoRa (long-range, low power — optional for rural areas). GSM/SMS (for mobile alerts — future upgrade).
Solution Overview
1. Alert System
Outputs:
Loudspeaker siren.
Flashing warning lights.
Roadside display board with “Elephant Detected – Danger Ahead”.
(Optional future) SMS/Push notification to villagers.
2.Power System
Solar panel + rechargeable battery for 24/7 uptime.
ESP32 designed for low-power sleep modes to save energy.
3. Dashboard
Shows detection logs, last alerts, and sensor status.
Could be hosted on a small server or cloud (ESP32 → Firebase / custom web app).