Our primary goal is to collect IOT data from various sources and provide a customizable dashboard to visualize the progress in cloud.
We are using AWS Device Shadowing to control IoT devices using Mobile application which helps us to set the required state even if the device is in offline state. Once IoT topic collects the data via MQTT protocol, it sends the data to AWS Lambda for processing inputs and communicate with other devices via different Topic.
Incoming data from the Firehose delivery stream is fed into an Analytics application that provides an easy way to process the data in real time using standard SQL queries.
Analytics allows writing standard SQL queries to extract specific components from the incoming data stream and perform real-time ETL on it which is loaded in Amazon QuickSight to create a monitoring dashboard and check if the devices are over-heating or cooling down during use
Redirecting all IoT related data to S3 and doing analytics using Apache Spark via AWS Elastic MapReduce. This approach gives us a channel to do analysis of millions of records in an effective way.
It creates an avenue to do ML.