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IoT has become one of the hot topics of the tech industry. From dedicated sessions at Amazon’s re:Invent 2016 to the upcoming Consumer Electronics Show (CES) 2017, the term comes up everywhere. IoT refers to an interconnected network of smart devices sending data to the Internet. The list includes your washing machine, A/C thermostat, car, watch, TV and almost anything else that has a ‘chip.’ By some estimations, there will be 6.4 billion connected devices by the end of 2016, generating $1.4 Billion in revenue and growing [1]. With those revenue projections, it is no surprise that companies like Amazon have already launched their IoT platforms.
The Amazon eco-system offers services like Amazon Cognito, AWS Lambda, Amazon Kinesis, Amazon S3, Amazon Machine Learning, Amazon DynamoDB, Amazon CloudWatch, AWS CloudTrail, and Amazon Elasticsearch Service with built-in Kibana integration to build IoT applications that gather, process, analyze and act on data generated by connected devices, without having to manage any infrastructure [2]. Pricing for the US East and US West Regions are a flat $5 per one million messages [3].
A typical IoT deployment on Amazon starts with security. The smart devices need to either authenticate with the AWS IoT Platform or Amazon Cognito using SigV4 or X.509 certificates. Once a device has been authenticated it can use Message Queuing Telemetry Transport (MQTT) or HyperText Transport (HTTP) protocols to send and receive data from the AWS IoT Device Gateway, which aggregates the streams and pushes them into AWS IoT Rules Engine. The AWS IoT Rules Engine can parse and filter the data using a SQL-like structure and deliver it to any of the Amazon products including Amazon DynamoDB, Amazon Kinesis, Amazon Kinesis Firehose, AWS Lambda, Amazon S3, Amazon SES, Amazon SNS and Amazon SQS.
Let us look at a use case: A company called TSEN produces smart thermostats that learn from your behavior and automatically adjust the heating and cooling based on ambient conditions and whether you are home or not. Once on WiFi these Internet-enabled thermostats authenticate with TSEN’s IoT Device Gateway and transmit every data point they have. The rules engine filters the data and pushes into Kinesis which, in turn, sends it into DynamoDB and S3. Then batched Lambda processes run and create summaries and push the data into Redshift and Machine Learning can turn the temperature up and down as needed, remotely. Now the thermostat owner can log in to TSEN website and see everything about their home ambient conditions and manage the thermostats remotely plus any notifications can be pushed out to the thermostats or smartphones using SNS.
The AWS eco-system provides all the required tools for your next IoT project and, naturally, leads into AWS Big Data solutions as well; thus, it is no surprise that the Amazon Big Data Certification has lots of IoT scenario questions on it.
If you like this post and would like to know more, check out our AWS CSA courses if you haven’t already and stay tuned for our Amazon Big Data Certification course.


Image of Jeff
4 years ago

Great use case provided. I love this stuff…

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