IoT for Agriculture: Building a Smart Farm Monitoring System

IoT for Agriculture: Building a Smart Farm Monitoring System

Soil sensors, weather data, irrigation control, and crop analytics — how I designed a complete IoT system for smallholder farmers using affordable hardware and open-source software.

Why Agriculture Needs IoT

A smallholder farmer who knows the soil moisture level in each plot can irrigate precisely rather than wastefully. Real-time weather data triggers frost alerts that save crops. Automated irrigation runs at the right time rather than on a fixed schedule that ignores actual conditions.

The hardware is now cheap enough that cost is no longer the barrier. A complete field monitoring node costs under $15. The barrier is software expertise to build reliable, maintainable systems.

Sensor Selection for Agriculture

Soil moisture: Capacitive sensors (not resistive — they corrode). The STEMMA Soil Sensor (I2C) is reliable for shallow monitoring. For deeper soil, tensiometers measure actual soil water tension.

Soil temperature: DS18B20 waterproof probe (1-Wire protocol, excellent for burial in soil).

NPK sensors: RS-485 Modbus NPK sensors give actual nitrogen, phosphorus, and potassium readings. They require a MAX485 RS-485 to TTL adapter to connect to the ESP32.

Ambient: BME280 (I2C) gives temperature, humidity, and atmospheric pressure.

Irrigation control: 12V solenoid valves controlled by a relay module. YF-S201 flow sensor measures actual water usage.

Irrigation Decision Logic

MOISTURE_LOW  = 35   # irrigate below this %
MOISTURE_HIGH = 65   # stop irrigation at this %
MAX_DAILY_MIN = 60   # cap daily irrigation at 60 minutes

class IrrigationController:
def evaluate(self, field_id, reading):
moisture = reading'soil_moisture']
if moisture < MOISTURE_LOW and self.can_irrigate_today(field_id):
duration = self.calculate_duration(moisture)
self.start_irrigation(field_id, duration)

def calculate_duration(self, moisture):
deficit = MOISTURE_HIGH - moisture # how far below target