Pi 5 Edge TFLite Crop Disease Kit with Raspberry Pi 5 + Camera
Classify Crop Diseases at the Edge with Raspberry Pi 5 AI HAT+ Kit
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
Point the Pi Camera Module 3 at a leaf and watch the display show whether it carries early blight, late blight, or a healthy leaf — all processed on-device with a MobileNetV2 model running on the Raspberry Pi AI HAT+. This kit equips you to build a plant disease classifier that works offline in the field, ideal for final-year projects or Smart India Hackathon prototypes where internet connectivity may be unreliable.
What You'll Build
You'll build a standalone edge AI device that captures leaf images and classifies crop diseases in under a second using a TensorFlow Lite model accelerated by the AI HAT+. The system outputs disease name and confidence score on the Pi’s display or a connected monitor, ready for real-world agriculture demonstrations.
What You'll Learn
- Deploying a quantized MobileNetV2 classification model on Raspberry Pi 5 with AI HAT+ using TensorFlow Lite
- Capturing and preprocessing camera frames with the Pi Camera Module 3 for inference
- Integrating GPIO-driven LED indicators to signal healthy/diseased results
- Running real-time inference at the edge without cloud dependency, a critical skill for IoT-based smart farming
Kit Contents
| Component | Quantity |
|---|---|
| Raspberry Pi 5 4GB | 1 |
| Raspberry Pi AI HAT+ | 1 |
| Pi Camera Module 3 | 1 |
| 5mm LED | 3 |
| 220Ω Resistors | 5 |
| M-F Wires | 10 |
| MicroSD Card 32GB | 1 |
| USB-C PSU | 1 |
Why Buy This Kit Instead of Sourcing Parts Separately
| Factor | Sourcing Separately | Compoden Kit |
|---|---|---|
| Compatibility checks | You verify every part | Pre-tested as a system |
| Build support | Forums and scattered tutorials | AI companion trained on this exact project |
| Time to first working build | Days of debugging | Hours, with step-by-step guidance |
| Shipping coordination | Multiple sellers, multiple delays | One shipment from Bengaluru in 3-5 days |
Who This Kit Is For
This kit is designed for B.Tech ECE/EEE final-year students building smart agriculture projects, Smart India Hackathon teams needing a ready-to-deploy edge AI system, and ATL Tinkering Lab mentors guiding advanced Raspberry Pi modules. Also fits IIT, NIT, VIT, and BITS Pilani students tackling crop disease detection for academic competitions.
Built and Backed by Compoden
Every Compoden kit ships with an AI build companion trained on this exact project — accessible via a QR code on the box, with WhatsApp and email backup. We've spent 10 years building projects for makers, schools, and institutions across India. If a part fails because of a manufacturing defect, replace it free within 7 days.
What if I get stuck during the build?
Scan the QR code on the box to chat with our AI build companion trained on this exact kit, or reach out over WhatsApp for human support from our team in Bengaluru.
Can I use a different model like ResNet or custom crops?
Yes, the AI HAT+ supports any TFLite model. You can train your own on custom crop datasets and deploy using the same workflow.
Does this kit work without internet in the field?
Absolutely. Inference runs entirely on the edge hardware. No cloud connection needed — only for initial model training and support.
Is the AI HAT+ pre-loaded with the model?
The SD card includes sample TFLite model files and setup scripts. You’ll flash it, then transfer the MobileNetV2 model as part of the guided build.
Pi 5 AI HAT+ runs MobileNetV2 crop disease classifier. Camera captures leaf and shows disease type.
What's in this kit
- Raspberry Pi 5 4GB
- Raspberry Pi AI HAT+
- Pi Camera Module 3
- 5mm LED x3
- 220Ω Resistors x5
- M-F Wires x10
- MicroSD Card 32GB
- USB-C PSU
Other projects you can build
Shipping Information
- Prepaid Orders: ₹75 for orders up to ₹999, FREE shipping above ₹999
- COD Orders: ₹125 shipping + ₹50 COD fee = ₹175 total
- Delivery Timeline: Dispatch in 1-2 days, delivery in 2-7 days depending on location
Returns & Warranty
- 7-Day Return: Manufacturing defects only (approval required)
- Warranty: 7 days from delivery
- Non-Returnable: Batteries, consumables, cut wires, clearance items