We have seemingly succeeded in stumbling through over 30 little experiments, with a couple of random "projects" to boot. Yet the holy grail of creating a paranoid android that forces Harrison Ford to become uncharacteristically philosophical about what it means to not(?!) be a replicant, seems even more far-fetched now than the plot of a typical Uwe Boll film.
But it hasn't all been in vain.
Because where we have landed is where most other avid tinkerers of microprocessors and electronics eventually end up... a strange (yet vibrant) place where the urge to interconnect sensors and devices far outweighs the actual need. Where it is essential to collect as much arbitrary sensor readings from around the family home as humanly possible, just in case we need to open them up in Excel at some point in the distant future to show the in-laws.
Welcome to a brand new series about IOT: an eclectic collection of curious posts in which we will attempt to do as much as humanly possible, with as little as humanly possible. Or more precisely, we will be leaving ESP8266 and ESP32 microcontrollers lying precariously around the house to the utter bemusement of the entire household, and get them (devices, not family members) to communicate with the mothership that is AWS IoT.
|1||Frozen Pi||Cold? How cold? Take DS18B20 temperature readings using a small army of ESP8266 devices, and dispatch them to AWS IoT Core and store them in DynamoDB.|
|2||Have-ocado||We will attempt to build a cluster using EEPROMs that binds 2 × ESP32 microprocessors in eternal wedlock - all in the name of monitoring some avocados. Then, we will deservedly spam ourselves with relentless notifications about node events and failures, using AWS Lambda and Simple Email Service (SES).|
|3||Green, green grass of /home||Do your avocados spontaneously combust? Be prepared, using a flame detector, temperature sensor and piezo buzzer. Connected to AWS IoT using ESP32, and Greengrass on Raspberry Pi.|
|4||Quantitative wheezing||Over-zealously collect data from multiple temperature, pressure and humidity sensors, and attempt to use AWS IoT Analytics to make sense of it all.|
|5||LoRa-Wan Kenobi||A long time ago in a galaxy far, far away... we connected an ESP32 running MicroPython to The Things Network LoRaWAN and AWS IoT Core. So ok, it may have actually been April 2019. And the galaxy was most likely the Milkybar Way.|
|6||Soreen seems to be the hardest word||Survive a post-apocalyptic landscape without cellular networks. Integrate a U-blox Neo-6 based GPS receiver module with MicroPython on ESP32, and update device coordinates in AWS IoT.|
|7||Ironed curtains||Setup a Raspberry Pi infra-red night-vision camera, and upload the results to AWS S3. To carry out rubbish bin surveillance, of course|
|8||20th entry fox||An Ironed Curtains sequel. Use AWS Rekognition to detect if the animal captured by the Raspberry Pi night-vision camera is of a cat, or a fox. Then, use AWS SES and S3 pre-signed URL to send out a notification.|
|9||Hard grapht||Use AWS Elasticsearch Service to store temperature, humidity, pressure and light readings collected by an ESP32. Then use Grafana or Kibana to visualise them.|
|10||Pear Force One||Use AWS IoT Events to monitor the status of Pear Force One. Because Harrison Ford is nowhere to be seen to save the world from certain disaster.|