HeatSense: Early Crop Stress Detector with Thermal Vision

HeatSense is an IoT-based agricultural innovation that detects crop water stress before visible wilting occurs. Using thermal imaging combined with ambient sensors, this system identifies subtle canopy temperature rises that signal plant stress. Farmers receive early alerts, allowing them to optimize irrigation and save water while protecting yield.

Why This Project Stands Out

• Smart Thermal Vision: Integrates IR thermal cameras with humidity and temperature sensors to detect genuine stress, not just heat.

• Edge AI Integration: A lightweight ML model runs on ESP32, learning the field’s baseline and flagging anomalies in real time.

• Precision Irrigation: Generates stress maps and zone-wise irrigation recommendations for efficient water use.

• Industry Relevance: Aligned with modern smart farming and sustainability goals, making it perfect for academic submissions and placements.

How It Works

1. Thermal Capture: The IR camera monitors canopy temperature.

2. Environmental Fusion: Data from temperature, humidity, and leaf wetness sensors filter false positives.

3. ML Model: Classifies crop stress levels (Normal, Mild, Severe).

4. Cloud Dashboard: Sends data via Wi-Fi or LoRa to a web dashboard with heatmaps and irrigation logs.

5. Automated Action: Optional relay or valve control enables automated precision irrigation.

Hardware Used

• ESP32/ESP32-S3 microcontroller

• MLX90640 or Lepton 3.5 thermal sensor

• SHT31/SHT41 humidity & temperature sensor

• LoRa module for long-range communication

• Solar-powered unit with battery backup

Applications

• Smart irrigation systems

• Greenhouse monitoring

• Precision agriculture research

• Crop yield optimization