Pi 5 Smart Irrigation Predictor: LSTM Water-Saving AI IoT Kit
Pi 5 Smart Irrigation Predictor: Train LSTM Models to Cut Water Waste by 30%
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
Water scarcity hits farms and urban gardens hard across India, especially with monsoon uncertainty. This kit turns a Raspberry Pi 5 into an edge AI engine that trains a Long Short-Term Memory (LSTM) network on historical soil moisture, temperature, humidity, and pressure data - then predicts exact irrigation demand for the next 48 hours. You skip guesswork, stop over-watering, and build a portfolio project that directly addresses a real climate resilience challenge.
What You'll Build
You assemble a multi-sensor field station that captures real-time environmental readings every 15 minutes and stores them on a high-speed NVMe SSD. The Pi 5 runs a TensorFlow Lite LSTM model to forecast soil drying trends, generating a daily irrigation schedule you can view on any browser. By the end, you have a fully functional precision irrigation controller that can save up to 30% water compared to timer-based systems.
What You'll Learn
- Train and quantize an LSTM on- device using historical weather and soil data
- Interface three soil moisture sensors, two DHT22s, and a BMP280 over I2C simultaneously
- Engineer time-series features from temperature, humidity, and pressure to improve prediction accuracy
- Build a lightweight web dashboard using Flask to display water demand forecasts
Kit Contents
| Component | Quantity |
|---|---|
| Raspberry Pi 5 4GB | 1 |
| Soil Moisture Sensor | 3 |
| DHT22 | 2 |
| BMP280 | 1 |
| NVMe SSD 128GB | 1 |
| Pi 5 M.2 HAT+ | 1 |
| USB-C PSU | 1 |
| M-M Wires | 20 |
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 intermediate kit is designed for B.Tech ECE and CSE students tackling AI for agriculture projects, Smart India Hackathon teams working on water conservation, CBSE Class 12 AI learners exploring edge computing, and ATL Tinkering Lab mentors guiding innovation in sustainable farming. If you have basic Python and Raspberry Pi experience and want to move from tutorials to a real prediction pipeline, this kit gets you there faster than assembling parts from five different vendors.
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 inside the box to open the AI build companion, which walks you through wiring, code deployment, and model training. If you need a human touch, message us on WhatsApp - our project engineers reply within an hour during India business hours.
Does this kit include a pre-trained LSTM model?
No, you train it yourself using a provided historical dataset and the guided Jupyter notebooks. The AI companion explains every epoch so you understand how the model learns moisture patterns, and you can later swap in your own farm or campus data.
Can I use the predictor for my college final year project?
Yes. Many students have submitted this as a major project for ECE, CSE, and agriculture engineering. The kit includes documentation suitable for project reports, and the AI companion helps you troubleshoot even during late-night build sessions.
How far apart can I place the soil moisture sensors?
The included wires let you spread sensors up to 2 meters from the Pi. For larger fields, you can extend them with standard jumper wires; the AI assistant shows how to calibrate readings based on wire length.
Historical weather and soil data trains LSTM on Pi 5 - predicts irrigation demand 48 hours ahead to optimise water use.
What's in this kit
- Raspberry Pi 5 4GB
- Soil Moisture Sensor x3
- DHT22 x2
- BMP280
- NVMe SSD 128GB
- Pi 5 M.2 HAT+
- USB-C PSU
- M-M Wires x20
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