Greenhouse Pressure Monitor Kit v5
Greenhouse Pressure Monitor Kit — AI-Powered Leak Prediction 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.
Your greenhouse loses pressure gradually before a leak becomes visible to the eye. This kit teaches you to catch that invisible drop the moment it starts. By pairing a flow sensor and a pressure sensor with an ESP32, you will build a device that reads the subtle relationship between flow and pressure, runs a trained TensorFlow Lite model right on the microcontroller, and sends an MQTT alert when the probability of a leak crosses a defined threshold. Instead of reacting to plant stress, you predict the risk and act first.
What You'll Build
You will assemble a self-contained monitoring station that screws into a standard greenhouse irrigation or misting line. The OLED displays live flow rate, internal pressure, and a continuously updating leak probability score. When the TFLite model on the ESP32 determines the sensor pattern matches a pre-leak signature, the display flashes a warning and the board publishes an MQTT message over Wi-Fi. You can receive that alert on your phone via any MQTT client, giving you a real-time early warning system for pressure integrity.
What You'll Learn
- Fuse flow and pressure sensor data into a single feature vector for machine learning inference
- Convert a trained leak prediction model to TensorFlow Lite and deploy it on an ESP32 microcontroller
- Configure MQTT communication to send real-time alerts from an embedded device to a subscriber client
- Render multi-variable sensor readings and inference results on a 0.96-inch OLED display
- Calibrate sensor thresholds using live greenhouse data to distinguish normal fluctuation from fault signatures
Kit Contents
| Component | Quantity |
|---|---|
| ESP32 Dev Board | 1 |
| YF-S201 Flow Sensor | 1 |
| BMP280 Pressure | 1 |
| 0.96in OLED | 1 |
| MicroUSB Cable | 1 |
| M-M Wires | 15 |
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 fits CBSE Class 11-12 students exploring AI-integrated physics projects and B.Tech ECE/EEE undergraduates building edge computing prototypes. If your ATL Tinkering Lab needs a working demo that combines IoT sensor fusion with on-device machine learning, or your Smart India Hackathon team is tackling precision agriculture, the sensor pipeline and TFLite inference flow map directly to those use cases. The learning curve starts at wiring sensors and ends at deploying a trained model, making it accessible even if you have never worked with AI on a microcontroller before.
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 open the AI build companion trained on this exact kit. It will walk you through wiring, code upload, and model deployment step by step. You can also message us on WhatsApp for direct troubleshooting.
Do I need a real greenhouse to test the system?
No. You can simulate pressure changes by gently blowing into the flow sensor inlet or partially covering it to create pressure differentials. The model will learn to associate specific flow-pressure combinations with leak signatures, and you can test the alert threshold on your desk.
Is soldering required?
No soldering. The kit uses male-to-male jumper wires and breadboard-compatible breakout boards. You plug the sensors directly into the ESP32, making assembly and disassembly clean and repeatable.
Can I modify the TFLite model to detect other anomalies?
Yes. The AI companion includes a notebook that shows you how the leak probability model was trained. You can collect your own greenhouse data, retrain the model with a different fault signature like clogged drippers or pump cavitation, and redeploy the updated model to the ESP32 using the same workflow.
Greenhouse — Flow sensor and pressure sensor data on ESP32 predicts leak probability using trained TFLite model — MQTT alert on high probability.
What's in this kit
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