Use Case
Convert raw sensor measurements into standardized units and formats before storage.
Example
Convert Celsius readings to Fahrenheit and store them in DynamoDB.
Use Case
Route data to different storage solutions based on device type or region.
Example
Send data from industrial sensors to Kinesis and from home sensors to S3.
Use Case
Aggregate data from multiple devices to compute averages, totals, or other metrics.
Example
Calculate the average humidity across all sensors in a greenhouse.
Use Case
Clean and normalize incoming data to ensure consistency.
Example
Remove outliers from temperature data before forwarding to analytics.
Use Case
Initiate batch processing jobs when enough data is collected.
Example
Once a day, trigger a Glue ETL job after accumulating a certain number of sensor logs.
Use Case
Update and synchronize IoT device states in their corresponding AWS IoT shadows.
Example
Update a device's reported state after receiving a new temperature reading.
Use Case
Periodically issue commands or requests to IoT devices.
Example
Instruct devices to run a self-test every 24 hours.
Use Case
Automatically create certificates and assign policies for new IoT devices.
Example
When a new device comes online, generate security credentials and register it with IoT Core.
Use Case
Assign devices to groups or fleets when they first connect.
Example
Tag new temperature sensors and add them to a 'Coolers' fleet automatically.
Use Case
Send commands to gracefully shut down devices under specific conditions.
Example
If a device overheats repeatedly, send a shutdown command to prevent damage.
Use Case
Distribute updated configuration parameters to devices.
Example
When a new device config is deployed, update all connected sensors.
Use Case
Detect patterns indicating potential device failures or maintenance needs.
Example
Trigger a maintenance ticket if vibration levels stay above a certain threshold for a week.
Use Case
Use a trained ML model to classify or detect anomalies in incoming IoT data.
Example
Send sensor readings to a SageMaker endpoint to identify temperature anomalies.
Use Case
Enrich and forward device data to AWS IoT Analytics channels for deeper insights.
Example
Add metadata (location, device type) before sending data to IoT Analytics.
Use Case
Aggregate periodic reports for compliance or operational metrics.
Example
Generate a daily report of average temperatures and upload it to S3.
Use Case
Kick off analytics workflows when certain events occur.
Example
Start a data analytics pipeline in Athena when a specified volume of data is reached.
Use Case
Trigger alerts when sensor values exceed certain thresholds.
Example
Send an SNS notification if temperature surpasses 80°F.
Use Case
Take actions based on the physical location of devices.
Example
If a shipment's sensor goes outside a designated region, send a location alert.
Use Case
Apply custom business logic policies to incoming messages.
Example
If a sensor reports data outside a set business rule, log the event and notify a manager.
Use Case
Secure or mask sensitive data before storage.
Example
Encrypt sensitive device IDs before saving to a data lake.
Use Case
Move older data to cheaper storage or delete it after a certain retention period.
Example
After data is 30 days old, trigger a workflow to archive or remove it.
Use Case
Trigger AWS IoT Events to handle complex event states.
Example
If multiple temperature spikes occur in a row, switch a state machine to a 'Fault Detected' state.
Use Case
Forward specific IoT data to external services or platforms.
Example
Send temperature alerts to a company's external incident management system.
Use Case
Distribute incoming data to different streams or shards for parallel processing.
Example
Route sensor data to multiple Kinesis shards based on device ID ranges.
Use Case
Register incoming IoT data schemas and metadata automatically.
Example
When new fields appear in sensor data, update the Glue Data Catalog accordingly.