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AWS... I-O-Mr-T

Nothing signals tough, action-ready, adventurous tech like a wholly opportunistic reference to an iconic 80s TV show which is only remembered for one - and only one - character.  So we're pleased to announce our brand new blog series curiously entitled I-O-Mr-T, in which we continue to expand our eclectic repertoire of intrepid, outdoor IoT experiments by shamelessly drawing parallels with the one and only B. A. Baracus.

Moreover, there has been quite a bit of interest generated in our previous series - I-O-Tea - in which we clumsily navigated around the AWS IoT portfolio by magically concocting use cases that bordered on the absurd (think: avocados on fire, tracking empty margarine tubs and catching bin-raiding animals in the act).  Yet, we somewhat surprisingly managed to demonstrate everything from AWS IoT Core to IoT Analytics, and from IoT Greengrass to IoT Events.  And all those random bits in between.

In other words, rather unexpectedly, we discovered an audience for our eccentric brand of IoT curiosity-making centred around AWS IoT.  A hobby, which is about to be juxtaposed big time with our other love; of the outdoors.

So let's heed the great bard's advice, and take this bewildering show on tour across the British countryside.

Let's go outside (let's go outside)
In the sunshine
I know you want to, but you can't say yes

1Gold fillingGoing offline for a while? No problem. Use a local SQLite database to cache sensor data, and dispatch them to AWS IoT Core when next connected to the Wild Wild Web.
2Castle Track-a-lotUse our old friend DynamoDB to house metadata about surrounding locations. And use it to make our re-enactment of the Arthurian legend against the backdrop of the Somerset countryside more interactive. Using location-based services, of course.
3Chariots of WireStrap up some IMUs. Then, run like some EMUs. Use an ESP32 together with an accelerometer and a gyroscope to record what your legs are doing. Because, why not?
4Athlete's FootnoteStore some IMU readings in InfluxDB. And use them to analyse the anatomy of a 2-minute toilet break using Grafana, Pandas and Matplotlib.
5SD:S3 The Untold Love StoryStory of how Harry the SD card met Ally the S3 bucket. Store sensor readings on a SD card before zooming them up to AWS S3 using IoT Core and Greengrass.
6Rage:MKRWe're going to interrogate our AWS IoT Analytics data using QuickSight and Jupyter Notebooks, then poorly execute a bit of machine learning on our helpless IoT data with the help of Scikit-learn.


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