Google Cloud IoT with Raspberry Pi: Getting Started

Google Cloud IoT provides a suite of managed services to connect, process, and analyse data from IoT devices at scale. When combined with the Raspberry Pi’s Linux-based flexibility, you get a complete IoT platform capable of handling everything from prototype to production. This guide covers the entire workflow for Indian developers.

Introduction to Google Cloud IoT

While Google Cloud IoT Core (the original device management service) was retired in August 2023, Google continues to offer powerful IoT capabilities through Pub/Sub, Cloud Functions, BigQuery, and partner integrations. The recommended approach now uses MQTT with Cloud Pub/Sub directly, giving you more flexibility and often lower costs.

Key services for IoT on Google Cloud:

• Cloud Pub/Sub: Managed message ingestion (first 10 GB/month free)
• Cloud Functions: Serverless event processing
• BigQuery: Petabyte-scale analytics (first 1 TB queries/month free)
• Looker Studio: Free dashboard and visualisation tool

Why Google Cloud for IoT in India

Google Cloud offers compelling advantages for Indian IoT deployments:

• Mumbai Region (asia-south1): Low-latency data processing within India
• Generous Free Tier: $300 credit for 90 days plus always-free tier for many services
• BigQuery: Unmatched for analysing large sensor datasets — query terabytes in seconds
• TensorFlow Integration: Train ML models on your IoT data using TPU infrastructure
• Firebase: Real-time database and mobile app integration for IoT dashboards

Setting Up Your Raspberry Pi

Prepare your Raspberry Pi for IoT development:

# Update system
sudo apt update && sudo apt upgrade -y

# Install Python dependencies
sudo apt install -y python3-pip python3-venv
python3 -m venv iot-env
source iot-env/bin/activate

# Install Google Cloud libraries
pip install google-cloud-pubsub google-auth paho-mqtt
pip install adafruit-circuitpython-dht adafruit-circuitpython-bme280

# Install gcloud CLI
curl -sSL https://sdk.cloud.google.com | bash
gcloud init

Configuring Google Cloud IoT Core

Set up your Google Cloud project for IoT:

1. Create a new project in Google Cloud Console
2. Enable the Cloud Pub/Sub API
3. Create a Pub/Sub topic named iot-telemetry
4. Create a subscription for consuming messages
5. Create a service account with Pub/Sub Publisher role
6. Download the JSON key file and transfer to your Raspberry Pi

Device Registration and Authentication

For secure device authentication, generate an RSA key pair on your Raspberry Pi:

# Generate RSA-256 key pair
openssl genpkey -algorithm RSA -out device_private.pem -pkeyopt rsa_keygen_bits:2048
openssl rsa -in device_private.pem -pubout -out device_public.pem

# Set proper permissions
chmod 600 device_private.pem

Sending Telemetry Data with Python

Here is a complete Python script that reads sensor data and publishes to Google Cloud Pub/Sub:

import json
import time
from datetime import datetime
from google.cloud import pubsub_v1
import board
import adafruit_dht

# Configuration
PROJECT_ID = "your-project-id"
TOPIC_ID = "iot-telemetry"
DEVICE_ID = "rpi-sensor-mumbai-01"

# Initialise sensor (DHT22 on GPIO4)
dht_sensor = adafruit_dht.DHT22(board.D4)

# Initialise Pub/Sub publisher
publisher = pubsub_v1.PublisherClient()
topic_path = publisher.topic_path(PROJECT_ID, TOPIC_ID)

def read_and_publish():
    try:
        temperature = dht_sensor.temperature
        humidity = dht_sensor.humidity

        if temperature is None or humidity is None:
            print("Sensor read failed, retrying...")
            return

        payload = {
            "device_id": DEVICE_ID,
            "temperature_c": round(temperature, 2),
            "humidity_pct": round(humidity, 2),
            "timestamp": datetime.utcnow().isoformat(),
            "location": "Mumbai, India"
        }

        data = json.dumps(payload).encode("utf-8")
        future = publisher.publish(topic_path, data)
        print(f"Published: {payload} [msg_id: {future.result()}]")

    except Exception as e:
        print(f"Error: {e}")

if __name__ == "__main__":
    print(f"Starting IoT telemetry for {DEVICE_ID}")
    while True:
        read_and_publish()
        time.sleep(60)  # Publish every 60 seconds

Visualising Data with BigQuery and Data Studio

Once data flows into Pub/Sub, route it to BigQuery for analysis:

1. Create a BigQuery dataset and table matching your JSON schema
2. Set up a Pub/Sub subscription that writes directly to BigQuery (no code needed)
3. Query your data: SELECT AVG(temperature_c), DATE(timestamp) FROM iot_data.telemetry GROUP BY 2
4. Connect Looker Studio to BigQuery and build real-time dashboards

The entire pipeline — from Raspberry Pi sensor to visual dashboard — can be set up within the free tier for small projects.

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