Hydroponics Nutrient Monitor Kit with ESP32 + DHT22
Hydroponics Nutrient Monitor Kit – Build an AI-Powered Yield Predictor with ESP32
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
Transform your hydroponics setup into a data-driven growing system that not only measures temperature, humidity, light, and soil moisture daily but also predicts crop yield using an on-device TensorFlow Lite regression model. This kit brings the exact sensor suite and machine learning toolkit needed to build a solar-powered field station that runs inference directly on an ESP32, helping you correlate environmental conditions with actual harvest outcomes.
What You'll Build
You'll assemble a weatherproof monitoring station that reads dual DHT22 sensors for temperature/humidity, a BH1750 for ambient light, and three capacitive soil moisture sensors at different depths. Data is timestamped by a DS3231 RTC and stored on a microSD card. A pre-trained TensorFlow Lite model runs daily predictions of yield (e.g., grams per plant) based on these four factors, with results shown on the OLED display. The entire system runs off-grid on a solar-recharged 18650 battery pack, ready for continuous outdoor operation.
What You'll Learn
- Fusing data from multiple I2C and analog sensors on an ESP32 using a minimal power budget
- Building a real-time data logger with RTC timestamps and microSD storage for long-term analysis
- Designing a solar-powered circuit with buck converter, TP4056 charging module, and battery protection
- Training and deploying a TensorFlow Lite regression model to predict crop yield at the edge
Kit Contents
| Component | Quantity |
|---|---|
| ESP32 Dev Board | 1 |
| DHT22 | 2 |
| BH1750 | 1 |
| Soil Moisture Sensor | 3 |
| DS3231 RTC | 1 |
| MicroSD Module | 1 |
| LM2596 Buck Converter | 1 |
| 0.96in OLED | 1 |
| 4.7kΩ Resistors | 5 |
| 100nF Caps | 10 |
| PCB Prototype Board | 2 |
| Waterproof Enclosure | 1 |
| Solar Panel 6V 2W | 1 |
| TP4056 Module | 1 |
| 18650 Cell | 2 |
| Soldering Iron | 1 |
| Solder Wire | 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 advanced kit is built for final-year B.Tech ECE/EEE students at institutions like IIT, NIT, VIT, and BITS Pillani working on precision agriculture capstone projects. Smart India Hackathon teams tackling crop monitoring challenges will find all the sensor integration done for them. Agri-tech startups and research labs deploying field‑ready IoT prototypes can skip the sourcing headache and jump straight to model tuning and data collection.
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 to open the AI companion trained on your Hydroponics Monitor Kit. It walks you through every wiring step, code upload, and model calibration. If you need a human, message our WhatsApp support and we'll respond within hours.
Can this kit really predict my hydroponics yield?
The pre-trained TensorFlow Lite regression model was built on greenhouse lettuce and herb data. You'll calibrate it using a short data-collection phase with your own crop; the companion shows you how to retrain and improve accuracy over time.
Does the kit work outdoors in Indian weather?
Yes, the included waterproof IP65 enclosure protects the electronics, and the 6V solar panel with LM2596 buck converter and TP4056 module reliably charges the 18650 cells even through monsoon clouds. We recommend mounting the enclosure under a shade to extend sensor life.
I'm new to machine learning—will I be able to follow?
Absolutely. The AI companion covers the fundamentals of feature engineering and TensorFlow Lite conversion. No prior ML experience is needed; the model is trained for you, and the companion explains how environmental data translates into yield predictions.
Hydroponics — ESP32 samples temperature, humidity, soil moisture and light daily. TensorFlow Lite regression model predicts yield.
What's in this kit
Choose your assembly option:
- Soldering Kit — 25W soldering iron, 60/40 solder wire, flux, and small perfboard for permanent assembly.
- Breadboard Combo — 800-point full-size breadboard with 65-piece jumper wire pack for solderless prototyping.
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