Weather Monitoring System Using IoT

Weather affects everything—from agriculture to urban infrastructure. But how do we move from outdated manual tracking to real-time, hyper-accurate monitoring? The answer: IoT. Let’s break down how to build a weather monitoring system using IoT, from hardware to cloud analytics.

Why IoT?

Traditional weather stations are clunky and static. IoT solves this with:

• Low-cost sensors (DHT22, BMP180, anemometers)
• Wireless protocols (LoRaWAN, MQTT, Wi-Fi)
• Scalable cloud dashboards (Node-RED, AWS IoT, ThingsBoard)

Hardware Stack

1. Sensors:

• Temperature/Humidity: DHT22
• Pressure: BMP180
• Rainfall: Tipping bucket rain gauge
• Wind: Ultrasonic anemometer

1. Microcontroller: ESP32 (Wi-Fi/BLE) or Raspberry Pi for edge processing.

2. Connectivity:
   

# Example: ESP32 sending data via MQTT  
import network, umqtt.simple  
def publish_sensor_data():  
    client = umqtt.simple.MQTTClient("esp32", "mqtt.broker.com")  
    client.connect()  
    client.publish("weather/temp", str(sensor.read_temp())) 

Software Side

• Data Pipeline: MQTT → Cloud (AWS IoT/ThingsBoard) → Database (InfluxDB)
• Visualization: Grafana for dashboards, or custom web apps with React + WebSocket.

Challenges & Fixes

• Power in remote areas? Use solar + LoRaWAN for low-energy transmission.
• Data accuracy? Calibrate sensors and apply moving averages in code.

Why Build This?

• Farmers: Predict irrigation needs.
• Smart Cities: Flood/storm alerts.
• You: A killer IoT portfolio project!

Ready to geek out? I wrote a full guide on a weather monitoring system using IoT, covering sensor specs, circuit diagrams, and analytics.

Read the full guide here: https://vayuyaan.com/blog/weather-monitoring-system-using-iot/