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IoT Data
Data Transformation |
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Having an excellent IoT solution with near-perfect hardware, communication and
even display capabilities is no insurance against poorly stored or poorly handled data.
Getting the data right can be the most difficult task of all.
Indeed, there are IoT solutions that were good but failed miserably because the data
was either not easily presented, understood, or incomplete.
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The struggle comes when you consider the type of data being generated (sensor data)
and how that data is interpreted. We begin with a review of what the Rat-Bait-Station's
sensor data (as shown above) can do and the strategies for making sense of the data, that is,
to gain knowledge from the data.
Making Sense of the Rat-Bait-Station DataWhat Is Being Observed?
The first thing to consider is
what we are observing. Don't focus on the data that the sensor is producing
(which is also important), but knowing what I am observing will allow me to plan
for how the data will be used.
Using the Rat-Bait-Station, I make a list of possible pests entering it and consider how
I would use that observation. The objective of the station is to detect a rat entering it
for the poison bait. But how do I know it's a rat entering the station and not other pests?
What Type of Data Does the Sensor Produce?
The next thing to consider is the type of data that the sensor is producing.
It is possible the data type of the data from the sensor could be quite different
from what we are observing.
Sensor data can come in several forms. The touch sensors can produce numeric data consisting of an integer.
Some sensors produce more complex information that is grouped together. For example, the
ultrasonic sensors produced values that had to be converted to distance to be meaningful.
Knowing how to interpret the values read is often the hardest part of using a sensor.
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My IoT Data Solution
Follow the data trail below in making sense of the Rat-Bait-Station's data to MySQL Server.
On entry : Rat
Triggers the Touch Sensor
Triggers the Ultrasonic Sensor
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