Saving money with IoT at home!

Hello Splunkers,

I recently blogged about how Udo, a member of the EMEA technical services team, is monitoring his smart home. Inspired by his use case I started to investigate if I too could collect data from my heating system to do a similar sort of analysis.

In the following blog I will document and show you how, inspired by Udo, I received insights into my own heating system, saving money as well as reducing my environmental impact. You can download everything from Splunkbase. I created an ETA PelletUnit App for Splunk.

The “source device” – my PelletUnit


I recently installed in my house a brand new PelletsUnit from ETA – an Austrian manufacturer. It burns wood pellets to heat the boiler, providing warm water for the underfloor heating as well the radiators. It also houses the micro processing power to manage both these systems as well as the circulating pump and the solar heating system. The control panel is Linux based and I found that I could connect nicely via VNC for remote control. However, the system lags behind when it comes to reporting functionality. No data has been stored for useful historical analysis such as how many pellets are used over time, how the consumption compares to the outside temperature or how much energy/heat was produced by the solar heating system. As you can tell I had a lot of unanswered questions to address!

Through some basic internet research I found a software package that could provide me with basic reporting but it would cost over €500. It also didn’t seem to offer the flexibility I needed to change or add different values.

Collecting data via RESTful Webservices

Thankfully ETA (the manufacturers of the pellet machine) incorporated in their control panel several web services that allow for access to the internal CAN subsystem. They also provide fantastic documentation in the form of ETAtouch and RESTful Webservices, so in the end I used these tools and the Splunk REST Modular Input to collect the data.

For example by collecting the data from the url: http://192.168.178.XXX:8080/user/var/40/10021/0/0/12011

I found that 11 was the value in kilograms that is currently in my pellet container.


Insights into heating consumption

Having collected the initial data, I had some questions I wanted to investigate. So I carried out some further reporting to answer the following:

  • How many pellets do we need every day?
  • How much KWH do we use the full year?
  • How much CO2 do we produce every day?
  • How many Euro do we use on heating every day?

The outcomes were as follows:

Bildschirmfoto 2015-12-01 um 11.36.38


index = "eta" sourcetype="eta:pellet:total_consumption_pellet"| eval strValue= strValue-6448| timechart max(strValue) as "KG" | eval CO2=(KG*0.003) | eval KWH = (KG*4.8) | eval Euro = KG*0.22680 | delta Euro AS "Euro" |delta KG as "KG"

This resulted in the following calculations:

  • 1 KG pellets produces 0.003 KG CO2
  • 8 pellets produce 1 KWH
  • 1 KG Pellet is bought for 0.22680 Euro

When you compare these figures with the outside temperature sensor of the pellet heater, I saw some surprising results.

Outside vs Solar


Bildschirmfoto 2015-12-01 um 11.37.01

When you compare these figures with the outside temperature sensor of the pellet heater, I saw some surprising results.

Recent temperatures had been consistently around 0 degrees celsius outside, but pellet consumption continued to increase…

On one day we had €8 Euro of pellet consumption with an outside temperature of 0 degrees celsius. Originally I calculated that the cost for heating would be around €500-600 per year. This was based on the assumption that there would be 150 heating days on average a year, costing €1.2 Euro a day with extra-budget built-in if the winter was colder or longer than anticipated. Based on these calculations, the pellet consumption was clearly far too much.


Root cause analyses / Fixing 

To find the cause of this problem, I checked the underfloor heating controls and reviewed the settings such as temperature, but couldn’t find any obvious problem. We also have a central ventilation unit with heat recovery and EC-technology from Helios in our house. Just to be sure, I reviewed the configuration for this and found my answer. In the Summer I enjoyed the experience of having fresh air circulating throughout the house for several hours everyday at full fan speed. Having found that this remained the same in the winter, I adjusted the settings down to a level that should be enough to keep the house fresh, but without the need to open windows regularly in the cold weather.

Observing the change

Having changed the configuration I monitored the situation through the Splunk Dashboard I created over the following days. I used my iPAD to show the data through the Splunk app, allowing for a full view of the dashboard. Having made the adjustment to the ventilation system I saw that my pellet consumption was reduced by about half. And that’s all the result of making machine data accessible, available and usable for everyone!

iPAD Dashboard App


As you might recognize, I also made my calculations based on the KWH that the solar heating system produces, how many pellet’s I saved and how much that was in Euros.

When looking at how much this exercise saved me I worked out the following figures:

  • €600 in pellet costs
  • €530 in costs avoided by not purchasing legacy ETA pellet software

Thanks to the free Splunk Enterprise License, I now poll the data every 5 minutes using only 0.9% of the 500 MB available to me on a daily basis.

With the weather only set to get colder this winter, my costs would have continued to increase, meaning I would have had to fill my 10,000 KG storage of pellets a few years earlier than I had planned!

Happy Splunking,


Matthias Maier is Product Marketing Director at Splunk, as well as a technical evangelist in EMEA, responsible for communicating Splunk's go-to market strategy in the region. He works closely with customers to help them understand how machine data reveals new insights across application delivery, business analytics, IT operations, Internet of Things, and security and compliance. Matthias has a particular interest and expertise in security, and is the author of the Splunk App for IP Reputation. Previously, Matthias worked at TIBCO LogLogic and McAfee as a senior technical consultant. He is also a regular speaker at conferences on a range of enterprise technology topics.