My Research
First, I researched into the topic of whether or not
temperature and humidity affect the infection rate of
the COVID-19. I looked at a few different scientific
publications and videos on this and found a loose
correlation that high temperature and high humidity
helps to reduce the spread rate the best while low
temperature and low humidity helps to promote the spread
rate the best. None of the research had concrete
evidence for this though and I was not satisfied with
this.
I moved onto looking into the effects of social
distancing and the effect it has on infectivity rate of
the COVID-19. The results are that the further away you
are the less likely you are to catch any of the aerosols
from other people talking, coughing or sneezing. All
sources gave a 2 metre guideline as a relatively safe
option, but said that a 2+ metre option is better. I
will be using this basis for designing my social
distancing system.
Currently there are COVID-19 tracker maps by Apple,
Google, and HSE, but all of these use either your
location data, which is a big issue of privacy, and/or
your Bluetooth, which is draining for many smartphones.
My response to the Brief
To safely maintain the 2 metre distance is the goal of
my project I wish to address. I am aiming my project
towards schools in the classroom setting. Maintaining
social distancing in schools can be achieved in many
ways, including:
1. Use ultrasonic distance sensors fixed to a person’s
chest to determine the distance to another person and
alert the user when the distance goes below 2 metres.
This method would be the most accurate but is only able
to detect in front of the person.
2. Use the Micro Bit’s built in radio to communicate
with other Micro Bits. It is able to sense the distance
each Micro Bit is from each other. This would allow the
sensing in all directions, but each person need to have
a Micro Bit with them.
3. Use humidity sensors to tell if another person
breathes too close by detecting the rise in humidity.
This is the least accurate method as even the user’s own
breath could be accidentally detected.
I chose to use method 2 as it gives a good combination
of both accuracy and the ability to build upon it after
the basic requirements are met.
