-- Leo's gemini proxy

-- Connecting to ew.srht.site:1965...

-- Connected

-- Sending request

-- Meta line: 20 text/gemini


Project HausBus: migrating old data

tags: data

Part 1: Progress on Project HausBus

Part 2

Yesterday I spend some time to survey the data I had collected with the existing setup. The collector script still dumps all data points into a simple sqlite database with one simple table. Since moving the viewing of these data sets into influxdb/grafana/web-browser, it seemed like a desirable thing to add the older data into the influx database as well.

sqlite data exists back until 2010-03-16

/slow/ sensors are read every 10 minutes, /fast/ ones every 2 minutes.

With /everything/ this amounts to 3.8 million points per year.

It had started out with about half that in the first year, so clearly there is a /data inflation/ going on here.

I could have tried to export the sqlite data into some format directly readable by influxdb. But I went the Perl Road again, because I had basically everything I needed. I had made sqlite database files per year and cleaned them a litte from experiments. Then I put together a few snippets already available:

from the old perl viewer the code to open and query said sqlite databases (usind DBI and the sqlite connector)

from the current collector the code to prepare a data set and sending it to MQTT.

This was rolling in a short time. However, since I put some "breaks" into the script due to fear to overload the little system collecting everything, this will take /forever/ (several hours per year). But slow is ok. Just now I watch the data points of 2020 rolling in and slowly appear on the grafana view. :)

If you live in your own or rented house, I strongly recommend to collect the readings of the meters for electricity, water, natural gas, or from the oil tank or whatever *once a month*, like in the evening before the first of the new month. I happened to start on 1st of October, which turned out to be good. And then create a graph "accumulated consumption over one year". Example (created with Rscript!):


The plot shows the consumption of natural gas over the course of the season, starting October 1st.

The values rise steeply over the winter and then go flat over summer (except first year).

The red line (year 2007/2008) shows the consumption in the first year, when we moved in and understood little.

The blue line (year 2008/2009) goes flat in summer --- we had added a solar heater. And we switched off the circulation pump, after realizing that it would basically spread heat in the basement for no good reason!

In the same year we replaced the windows to switch off the /natural/ air exchange with the neighborhood, also known as /neighborhood heating scheme/ :)

So in the following years consumption fell significantly due to different changes in ventilation and insulation of the building and mild winters (all green lines).

The black line (year 2019/2020) sees the lowest values so far, which at the very least reduces the bill.

Even if you produce a similar plot manually on a sheet of paper, it will tell you nicely, how you fare.




-- Response ended

-- Page fetched on Wed Oct 20 20:25:40 2021