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Ken Cameron
Ken Cameron

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Using AWS Lambda as data processing for any IoT project.

#python #mqtt #aws #beginners

To start something, proper planning and preparation is needed. This idea came to me when I had an elective called Internet of Things. It wasn't taught well😄 but it gave me this idea. A simple moisture checker can update you when you need to water your plants.🪴 Using Aws Lambda, we could use their server instead of using laptops and keeping it on for a long time when it could be used for something else.

Why AWS Lambda?

  1. Costs: It's fairly cheap and it has an option where the first interactions are free. So, for someone who wants to start but is tight on money, AWS Lambda is a good option.

  2. Real Time Processing: With servers that are always on, it can process data in real time, do actions based on the received data, and send notifications.

  3. Scalability: In time, if you want to increase this project, AWS Lambda can scale well into anything that you need.

  4. Integration with other AWS Services: Since AWS provides a lot of services, it acts as a one-stop shop for your needs. No need to look anywhere else if the services you're looking for is already here.

The IoT Use Case: Temperature Monitoring 🌡️

Let’s imagine a moisture monitoring system. Sensors periodically send data to AWS IoT Core, which triggers a set-up AWS Lambda function to process and store the data in DynamoDB. The Lambda function also sends notifications to users.

Step-by-Step Guide to Deploy Your IoT Project 🚀

1) Set Up AWS IoT Core 🛠️

  • Create an IoT Thing: Navigate to the AWS IoT Core Console and define your IoT device.
  • Generate Certificates: Download the device certificate and keys for secure communication.
  • Attach Policies: Grant your IoT device permission to publish and subscribe to topics.

2) Write the Lambda Function 💻
Create a Python function to process incoming IoT data:

import json import boto3 def lambda_handler(event, context): # Parse the incoming event payload = json.loads(event['body']) temperature = payload['temperature'] device_id = payload['device_id'] # Store in DynamoDB dynamodb = boto3.client('dynamodb') dynamodb.put_item( TableName='TemperatureReadings', Item={ 'DeviceID': {'S': device_id}, 'Temperature': {'N': str(temperature)}, } ) # Send an alert if temperature exceeds threshold if temperature > 30: print(f"ALERT! High temperature: {temperature}°C") return { 'statusCode': 200, 'body': json.dumps('Data processed successfully!') }
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3) Connect IoT Core to Lambda 🔗

  • Create a Rule: In AWS IoT Core, create a rule to trigger your Lambda function.
  • Define the Topic: Specify the MQTT topic your device publishes to (e.g., sensors/temperature).
  • Add the Action: Link the rule to your Lambda function.

4) Deploy the Lambda Function 🚀

  • Upload your code as a .zip file or use the inline code editor in the AWS Management Console.
  • Set the necessary environment variables and configure a trigger from IoT Core.

5) Test Your Setup 🧪
Publish a test message to the MQTT topic from your IoT device:

mosquitto_pub -h <Your IoT Core Endpoint> -t "sensors/temperature" -m '{"device_id": "sensor1", "temperature": 35}'
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Final Thoughts 🌟

Deploying an IoT project with AWS Lambda is a game-changer for developers, offering scalability, cost-effectiveness, and a serverless experience. By combining IoT Core and Lambda, you can build responsive and intelligent systems that grow with your needs.

Happy Holidays! ☃︎🎅🎄❄️☃️🎁🦌

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