I Me Mine
Project due at 11:59pm Monday
to give people practice with writing an application
in processing and get
everyone ready to contribute to the group projects to come.
The project will
focus on looking at household utility data - which could either be
to decrease waste or to cyber-stalk someone.
Below you will find a link to a table
containing 11 years of data on:
temperature (according to the comed)
Gas Usage (therms / day)
- Water Usage
(gallons / day)
The data is available
In this case the data is already pre-processed to be an
appropriate size and in an easily readable form. That won't hold
for the later
typically billed once a month, but typically every other meter
an estimate. Water is typically billed every 2 to 3 months, and
gas every 1 to 2 months. This makes it harder to see short term
but longer term trends should still be visible.
data in the file comes from the electricity company. The data
reasonable but you might want to get temperature data from
another source, and probably in addition to the average also look
minimum and maximum.
You should start
by looking at data itself and do some simple plots in your
spreadsheet / plotting program. There will be some obvious
patterns such as air conditioning driving up electricity usage
dramatically in the summer and the furnace driving up natural gas
dramatically in the winter.
Your job is to
look beyond the cyclical patterns for longer term trends and
aberrations that are hiding there, and see what changes in the
world could have caused them. Some of these changes are related to
hot a summer was or how cold a winter was, others are related to
behavior. This is where the cyber-stalking / privacy issues part
project comes in. If you have access to this utility data and can
filter out the repeating patterns, and the general environmental
changes, can you find interesting events or trends that tell you
The goal here is to create an interactive visualization tool to
your analysis and to back up any conclusions you draw.
Here is some more data that will help you with this:
- The house
stayed basically the same throughout the 10 years of data
- The house uses
electricity to run the air conditioner for cooling, and to run the
blower on the furnace for heating
- The house uses
gas for heating and cooking, and drying laundry
I did some
roough measurements of my electricity usage recently:
gear (computers, TV, videogame consoles) 4.5 kwH / day
& Cleaning 3.5 kWh / day
fan (not counting air conditioning) 2 kWh / day
- Pond hardware
2 kWh / day
In a common
- taking a bath takes 50 gallons
- taking a shower takes 2 gallons per minute
- flushing a toilet takes 3 gallons
- a dishwaser uses 20 gallons
- a top loading clothes washing machine uses 60 gallons, a
loading machine uses 30 gallons
This data should
allow you to break up the daily usage of two people into
that can vary
over the months and years.
Here are some of
the dates things that might affect the utility usage
- April 2000
- Started an outdoor pond (400 gallons)
- June 2000
- Replaced the air conditioner
- April 2002
- Enlarged pond (total of 650 gallons), had major infection in
fish requiring many water changes
- July 2004
- Installed new programmable thermostat
- July 2006
- 2 week trip out of the country
- Fall 2006
- Started using mulch and less water in the garden
- 2007 -
Replaced incandescent bulbs with CF bulbs
- July 2008
- 2 visitors for a month
- March 2008
- Replaced top loading clothes washing machine with front
2009 - Doubled the insulation in the attic
2009 - New high-efficiency furnace and water heater
- June 2010
- 2 week trip out of the country
up some other reference material on the web about
water, gas, and electricity usage. I did. I also found that some
over-inflate the usage numbers by 50 to 100% compared to the
that I was able to measure. Those numbers also depend quite a bit
live and the size of your home. I would recommend looking at a few
different sites to get a better feeling about what good average
might be. Be sure to cite the websites that you use.
visualization and analysis tool should be written in processing.
Milk / Tea / Coffee example should give you a nice head start on
You should start by getting processing installed and doing some
tests to load in the data and start displaying it. You should then
start to draw some sketches of what the interface might look
and how you want to arrange and display the data. How are you
make use of the screen real-estate?
You can use other software to generate statistics about the data
find that useful. The data here is the kind of thing you would
typically see in a graph which is probably a good way to visualize
and this will give you a chance to write a set of graphing code
you can reuse in future assignments since graphs are so useful.
The application you create should help the user perform the
Task #1 -
document the repeating seasonal utility usage patterns and what
patterns (e.g. temperature)
Task #2 - given
the results from task #1, document the long term trends and short
variations in those patterns (e.g. given temperature readings you
should be able to work out expected values for
gas and electricity usage, and then any variation you see might
a human cause).
Task #3 - given
the results from task #2, try to see if the events listed above
obvious affect. Also look for other possible affects on the data.
other dates where interesting things happen?
Bonus Task #4 - predict
average daily electricity, natural gas, and water usage for the
months of the table. The table of data ends at July 2010.
values for the next four rows: August, September, October,
the end of the course we will see who was the best predictor.
you need ...
you need to add ...
- static well labelled graph or set of graphs which can be
- ability for the user to show electricity / water / gas on
time line together or individually with appropriate colours
- give general tabular statistics about utility usage
- you should check your visualization with a colour blindness
to see that its ok
- the graph should update quickly when the user interacts
you need to add ...
- labelling the important events listed above in the graph
- see outdoor temperature data superimposed on the utility
- display the data compared to its average (yearly / seasonaly
- compare the most recent month of data to the overall data
- interpolate changes in the graphs for smooth transitions
changes in the view
- dynamically zoom in on part of the timeline to see it in
- dynamically change the clustering of the data to see
amounts (eg per season, per year)
- find some
interesting things in the data and highlight them on your
through screen snapshots
create a web page that describes your work on
the project including an
embedded processing window (with a max size of 1280 by 700) and a
to a gzipped file containing the
source code and all other necessary files to make it run locally.
organized page should function as a README file and describe the
you implemented along with any special features that you added. It
should include screenshots of all the major features.
linking this web page to the course notes
so please send me a nice 1024 x 768 jpg image of your
should be named
Web pages like this can
be very helpful later on in helping you build up a portfolio of
work when you start looking for a job so please put some effort
We will take one class period to look through these visualizations
everyone can see a variety of solutions to the
problem, and a variety of implementations. You will be expected to
about your work.
- clarified due date and time