ESP32 Indoor Plant Monitor Kit: Predict Yield with AI
ESP32 Indoor Plant Monitor Kit - Predict Your Houseplant's Harvest with On-Device AI
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
Some houseplants give you subtle signs before they bloom or fruit, but most keep their secrets locked in data you can't see. This kit lets you log temperature, humidity, soil moisture, and light for days, then train a TensorFlow Lite regression model right on the ESP32 to forecast harvest time. It's not a generic monitor - it's a personal agronomist for your windowsill.
What You'll Build
You'll assemble a solar-powered, weather-sealed station that continuously samples four environmental factors and logs them to a microSD card. A crisp OLED display shows live readings, while the on-device AI model runs inference to predict when your plant will yield. The entire system measures only a few inches across and runs unattended for weeks.
What You'll Learn
- Deploy a TensorFlow Lite regression model on an ESP32 to make yield predictions from sensor data
- Interface multiple I2C sensors - DHT22, BH1750 light sensor, DS3231 RTC - on a single bus
- Design a solar-powered data logger with TP4056 charge management and LM2596 voltage regulation
- Pre-process and analyze environmental time-series data to improve model accuracy
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 |
| 4.7k? 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 project fits B.Tech ECE and EEE students tackling IoT agriculture capstone projects, Smart India Hackathon teams developing smart farming solutions, and researchers exploring edge AI for precision agriculture. It's also suited for plant enthusiasts with embedded systems experience who want to go beyond data logging to build a predictive model that lives on their desk.
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 kit box to open the AI companion. It knows every component, every connection, and the full codebase - and can answer your questions step by step. WhatsApp support is also available for trickier issues.
Do I need to know TensorFlow before starting?
No prior ML experience is required. The kit includes a pre-trained model and a Colab notebook that guides you through data logging, training, and model conversion. The AI companion explains each concept as you go.
Can I use this outdoors for my garden?
The waterproof enclosure and solar panel are designed for indoor use, but they handle mild outdoor conditions. For permanent outdoor deployment, you may want to reinforce the soil sensors against weather - our AI companion can suggest simple modifications.
How accurate is the yield prediction?
With 7-10 days of consistent logging, the on-device regression model typically reaches 80-90% confidence for common houseplants such as tomatoes, basil, and chili. The AI companion helps you interpret the results and tweak the data pipeline to improve accuracy.
Houseplant - 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.
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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