Weekly Yield Forecasts via LoRa

Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.

Hydroponic growers can lose up to 30% of yield to unnoticed nutrient shifts. This kit builds a sensor station that measures temperature, humidity, soil moisture, NDVI, and rainfall, feeds data into an LSTM neural network, and sends weekly yield predictions over LoRa, letting you adjust nutrients before losses occur.

What You'll Build

A precision agriculture station tracking seven variables, running an LSTM model on-device, and wirelessly transmitting predictions up to 2 km. Ready for greenhouse, polyhouse, or rooftop hydroponics.

What You'll Learn

• Interface NDVI spectral sensor with ESP32 over I2C for plant health monitoring.
• Log time-series sensor data to MicroSD for model training.
• Train and deploy a TensorFlow Lite LSTM model on the edge.
• Set up LoRa communication between sensor node and gateway.

Kit Contents

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.