Humanβwildlife conflict is a serious issue in many forest and village-border areas. Leopard attacks often happen because people do not get timely alerts. This project solves that problem using AI Vision + ESP32.
In this project, we build an AIβPowered Leopard Alert System that detects leopards in real time using a YOLO-based machine learning model and instantly triggers alerts (buzzer, LED, mobile notification, or cloud dashboard).
The system uses a camera to monitor the area, runs AI detection (locally or on edge/cloud), and sends alerts using ESP32 when a leopard is detected.
π― Key Featuresβ Real-time leopard detection using YOLO AI model
- β Real-time leopard detection using YOLO AI model
β ESP32-based alert system (low power & low cost)
- β ESP32-based alert system (low power & low cost)
β Works day & night (with IR camera support)
- β Works day & night (with IR camera support)
β Buzzer / LED / Mobile alert support
- β Buzzer / LED / Mobile alert support
β Scalable for forests, farms, and villages
- β Scalable for forests, farms, and villages
β Edge AI + IoT based solution
- β Edge AI + IoT based solution
Camera continuously captures live video
- Camera continuously captures live video
Video frames are processed using YOLO AI model
- Video frames are processed using YOLO AI model
AI model detects leopard (confidence-based)
- AI model detects leopard (confidence-based)
Detection signal sent to ESP32
- Detection signal sent to ESP32
ESP32 triggers:
π Buzzer / Siren
- π Buzzer / Siren
π¨ LED Alert
- π¨ LED Alert
π² Mobile / Cloud Notification
- π² Mobile / Cloud Notification
- ESP32 triggers:π Buzzer / Sirenπ¨ LED Alertπ² Mobile / Cloud Notification
Component
Description
ESP32 Dev Board
Main microcontroller with WiβFi & BLE
ESP32βCAM (Optional)
Camera module (OV2640)
USB Camera / IP Camera
For AI vision input
Buzzer / Siren
Sound alert
High Power LED
Visual alert
IR Camera (Optional)
Night detection
Power Supply
5V Adapter / Solar + Battery
Jumper Wires
Connections
Enclosure Box
Outdoor protection
π» Software & Tools UsedπΉ AI / Machine LearningYOLOv5 / YOLOv8 (Custom trained)
- YOLOv5 / YOLOv8 (Custom trained)
Python
- Python
OpenCV
- OpenCV
PyTorch
- PyTorch
LabelImg (Dataset labeling)
- LabelImg (Dataset labeling)
Arduino IDE
- Arduino IDE
ESP32 Board Package
- ESP32 Board Package
Firebase / ThingsBoard / Blynk
- Firebase / ThingsBoard / Blynk
MQTT / HTTP API
- MQTT / HTTP API
Windows / Linux
- Windows / Linux
Collect leopard images/videos
- Collect leopard images/videos
Extract frames using OpenCV
- Extract frames using OpenCV
Label images using LabelImg
- Label images using LabelImg
Convert annotations to YOLO format
- Convert annotations to YOLO format
Split dataset:
70% Training
- 70% Training
20% Validation
- 20% Validation
10% Testing
- 10% Testing
- Split dataset:70% Training20% Validation10% Testing
# Clone YOLO repo
git clone https://github.com/ultralytics/yolov5
cd yolov5
# Install requirements
pip install -r requirements.txt
# Train model
python train.py --img 640 --batch 16 --epochs 100 --data leopard.yaml --weights yolov5s.ptAfter training, export model:
python export.py --weights best.pt --include onnxπ₯ Real-Time Detection Script (Python)import cv2
from ultralytics import YOLO
model = YOLO('best.pt')
cap = cv2.VideoCapture(0)
while True:
ret, frame = cap.read()
results = model(frame)
for r in results:
for box in r.boxes:
conf = box.conf[0]
if conf > 0.7:
print("Leopard Detected")
# Send signal to ESP32
cv2.imshow('Leopard Detection', frame)
if cv2.waitKey(1) & 0xFF == 27:
breakπ‘ ESP32 Alert System Code (Arduino)#define BUZZER 12
#define LED 13
void setup() {
pinMode(BUZZER, OUTPUT);
pinMode(LED, OUTPUT);
Serial.begin(9600);
}
void loop() {
if (Serial.available()) {
char data = Serial.read();
if (data == '1') {
digitalWrite(BUZZER, HIGH);
digitalWrite(LED, HIGH);
delay(5000);
digitalWrite(BUZZER, LOW);
digitalWrite(LED, LOW);
}
}
}π² Mobile / Cloud Alert (Optional)Push notification using Firebase
- Push notification using Firebase
SMS alert using Twilio
- SMS alert using Twilio
MQTT dashboard
- MQTT dashboard
5V DC Adapter
- 5V DC Adapter
Solar panel + Liβion battery
- Solar panel + Liβion battery
Deep sleep mode for ESP32
- Deep sleep mode for ESP32
Forest boundaries
- Forest boundaries
Village border areas
- Village border areas
Farms near wildlife zones
- Farms near wildlife zones
Wildlife research projects
- Wildlife research projects
Smart forest monitoring
- Smart forest monitoring
Multi-animal detection
- Multi-animal detection
Night vision thermal camera
- Night vision thermal camera
Edge AI on ESP32βS3
- Edge AI on ESP32βS3
GSM module for SMS alerts
- GSM module for SMS alerts
AI confidence optimization
- AI confidence optimization
Circuit diagram
- Circuit diagram
Detection demo video
- Detection demo video
Real forest test images
- Real forest test images
If you face any issue while building this project, feel free to contact:
Tech Gyan Setπ₯ YouTube: Tech Gyan Set
π Project StoryWildlife aur human safety ke beech conflict aaj ke time me ek bahut badi problem ban chuki hai, especially un areas me jo forest boundary ya wildlife zones ke paas hain. Raat ke time ya early morning me leopard jaise wild animals villages, farms aur roads ke paas aa jate hain. Kyunki logon ko time par alert nahi mil pata, is wajah se accidents aur attacks ka risk badh jata hai.
Isi real-world problem ko solve karne ke liye AI-Powered Leopard Alert System Using ESP32 & YOLO design kiya gaya hai. Ye project Artificial Intelligence + IoT ka practical use dikhata hai jisse real-time me leopard detect karke turant warning di ja sake.
Is system me ek camera continuously area monitor karta hai. Camera se aane wali live video feed ko YOLO AI model ke through analyze kiya jata hai. Jaise hi system ko leopard detect hota hai (confidence threshold ke saath), turant ek signal ESP32 microcontroller ko send hota hai. ESP32 us signal ke base par buzzer, LED, siren aur mobile/cloud alert trigger kar deta hai.
Is project ki sabse badi strength hai iska low cost aur easy deployment. Hardware components easily available hain aur software openβsource tools par based hai. Isliye students, beginners, researchers aur realβworld field deployment ke liye ye project bahut useful hai.
Agar aap khud ye project banana chahte hain lekin:
AI / YOLO samajh nahi aa raha
- AI / YOLO samajh nahi aa raha
ESP32 programming me problem aa rahi hai
- ESP32 programming me problem aa rahi hai
Ya aap chahte hain ki ye system aapke area ke hisaab se customized ho
- Ya aap chahte hain ki ye system aapke area ke hisaab se customized ho
toh main personally aapki help karunga.
π Build Support & ContactAgar aap chahte ho ki:
β Main aapke liye ye project complete build karke doon
- β Main aapke liye ye project complete build karke doon
β ESP32 + YOLO ka full working code provide karun
- β ESP32 + YOLO ka full working code provide karun
β Bilkul low cost me customized solution banaya jaye
- β Bilkul low cost me customized solution banaya jaye
β Stepβbyβstep guidance mile (online / offline)
- β Stepβbyβstep guidance mile (online / offline)
Toh aap directly contact kar sakte ho:
π± Phone / WhatsApp: +91 9336183481π₯ YouTube: Tech Gyan Set
Main aapko complete project support, working demo, aur tested code provide karunga β wo bhi bilkul low cost me.
β ConclusionThis AIβPowered Leopard Alert System is a practical, lowβcost, and scalable solution to reduce wildlifeβhuman conflict using ESP32 + YOLO AI Vision. The project is suitable for students, researchers, and real-world deployment.
If you like this project, donβt forget to appreciate and share! π









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