SucculentPi [AWS Basel Meetup - Oct 2022].pdf

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SucculentPi
An IoT Panopticon
for a House Plant

© All rights reserved 2022
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Dead Plant + Boredom + Raspberry Pi
=
Internet-of-Things!
In The Beginning…

Because we usually can’t tell the stories from
our real, customer projects! ☹
But Why?

Part 1: The Thing Bit

The Hardware

The GrovePi+ software is years out of date, and uses an imperative deployment script!
I never managed to escape dependency hell with that outdated script
Did get it working just enough though!
Why, oh why, are we still using imperative deployment scripts in 2022 ?!?
Challenge 1: Imperative Deployment Woes

If you can engineer consistency into your data at the point
of generation/capture, you’ll save yourself a ton of hassle
down the line!
Plus I had nowhere to put to the IR camera
Solution: Hacking, of the IKEA variety!
So I built a rig to hold the plant in a consistent position
relative to the camera and other sensors
Challenge 2: Building in Consistency

The Awair device provides environmental and air quality data
for the room
It has a handy local network API…
… which seems to be in perpetual beta, and of very beta quality!
Randomly returns HTTP 200 with no data
Had to check actual content of the response on every API call,
instead of just checking the return code
Challenge 3: Beta APIs

From the Raspberry Pi Sensors:
1. Infrared image of the plant’s leaves
2. Visible light level
3. Ultraviolet light level
4. Infrared light level
5. Soil moisture level (top of pot)
6. Soil moisture level (middle of pot)
7. Soil moisture level (bottom of pot)
From the Awair Sensors:
1. Room air temperature
2. Dew point for the room
3. Relative humidity level
4. Absolute humidity level
5. Carbon Dioxide (CO2) level
6. Air Volatile Organic Compounds (VOC) level
7. Air hydrogen (H2) level
8. Air ethanol level
9. Airborne particulate matter (PM2.5) level
The Final Data Points
All collected on the following schedule:
*/5 * * * *

Part 2: The Internet Bit

The IR image is uploaded to an S3 bucket
A JSON payload is generated containing all the
sensor readings, plus the S3 URL of the associated
IR image
The payload is sent as a message to an MQTT topic
in AWS IoT Core
{
"timestamp": "2022-01-01-000000",
"plant": {
"pot": {
"soil": {
"moisture_top_a0": 87,
"moisture_middle_a1": 31,
"moisture_bottom_a2": 49
}
},
"env": {
"visible_light": 278,
"uv_light": 0.11,
"ir_light": 349
},
"images": {
"infrared": "https://bucket.s3.region.amazonaws.com/infrared/2022-01-01-000000.png"
}
},
"room": {
"env": {
"dew_point": 16.66,
"temp": 28.34,
"rel_humid": 49.17,
"abs_humid": 13.6,
"co2": 471,
"voc_total": 40,
"voc_h2": 26,
"voc_ethanol": 36,
"pm25": 8
}
}
}
Data Acquisition

An AWS IoT Core message routing rule routes the
payload’s contents to AWS Timestream
Message routing rules are just SQL
Here we ﬂatten the hierarchy in the JSON message,
To give a ﬂat structure in Timestream for ease of
future analytics
SELECT
plant.pot.soil.moisture_top_a0 AS plant_pot_soil_moisture_top,
plant.pot.soil.moisture_middle_a1 AS plant_pot_soil_moisture_middle,
plant.pot.soil.moisture_bottom_a2 AS plant_pot_soil_moisture_bottom,
plant.env.visible_light AS plant_env_visiblelight,
plant.env.uv_light AS plant_env_uvlight,
plant.env.ir_light AS plant_env_irlight,
plant.images.infrared AS plant_image_infrared,
room.env.dew_point AS room_env_dewpoint,
room.env.temp AS room_env_temperature,
room.env.rel_humid AS room_env_relativehumidity,
room.env.abs_humid AS room_env_absolutehumidty,
room.env.co2 AS room_env_co2,
room.env.voc_total AS room_env_voctotal,
room.env.voc_h2 AS room_env_voch2,
room.env.voc_ethanol AS room_env_vocethanol,
room.env.pm25 AS room_env_pm25
FROM
'succulentpi/readings'
MQTT Message Routing

Part 3: The Bit Where it all goes Wrong

The GrovePi+ board had crapped out… naturally,
right after I stopped manually checking the data ﬂow
regularly!
All the sensors returned data only intermittently, and
all of the readings were garbage - null, 0, or 65536
It took a hard reboot - physically removing power for
a while - to revive it!!!
So…
Beware Hobby IoT Hardware

So I need to physically disconnect the power regularly,
automatically, and reliably…
Sooo… robots?!?
I drastically over thought this for a while, until a light bulb
moment came…
Literally - a light bulb came on! I have an IKEA Smart Home
system, which has scheduled actions, and they sell a smart plug
So IKEA to the rescue!
Challenge 4: Automating Hard Power Cycles

I don’t want to loose weeks of data if this happens again, therefore I need monitoring!
Monitoring for successfully published MQTT messages won’t fully capture this situation
Instead; the actual values of the sensor readings committed to the Timestream table need to be checked for
sanity
Handily, AWS have a blog post on exactly how to do this with Lambda
I went with checking the one soil moisture sensor reading, as these sensors have a well documented deﬁnition
of valid readings:
Challenge 5: What if it Happens Again?
elif result > 0 and (int(response['Rows'][0]['Data'][4]['ScalarValue']) < 0 or
int(response['Rows'][0]['Data'][4]['ScalarValue']) > 950):
logger.info("Sending Data Out Of Range SNS Message...")
sns.publish(TopicArn=SNS_TOPIC, Message=f"ALERT: The SucculentPi sensor data is out of range", Subject="Alert:
Sensor Data Out of Range")

Keep an eye on the Cloudreach Tech Blog for more of the continuing SucculentPi adventures!
Deﬁnitely planning more for this project, once enough (non-garbage) data has been collected
Ideas for future parts include (in no particular order):
● Dashboarding and visualisation of the time-series data with AWS QuickSight
● Can we detect useful/interesting things in the IR images using computer vision ML with AWS
SageMaker and/or Rekognition?
● Can we forecast watering needs using AWS Forecast?
● Can we discover any interesting correlations between watering needs and environmental
factors using AWS Lookout and/or SageMaker?
Watch this Space…

Questions?
Perhaps Answers

Thank you
Cloudreach Tech Blog: https://www.cloudreach.com/en/technical-blog
Blog Part 1: https://bit.ly/3T7IFob
Blog Part 2: https://bit.ly/3TtazL0
Sample Code: https://github.com/binghamchris/succulentpi

SucculentPi [AWS Basel Meetup - Oct 2022].pdf

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