One of the great things at Splunk is that there are so many devices you can collect data from and make something meaningful out of. We often hear from our (very smart) customers that they are figuring out cool use cases – but we also hire new data geeks like Udo Götzen from the EMEA Technical Services Team, too. He joined Splunk a few weeks ago with a deep security background and has already started to Splunk his postbox (mailbox for the American readers) and the rest of his smart home.
1. Yes you heard right – his postbox!
How does it work? He has built an infrared photo sensor into the postbox that gets activated if someone drops in a letter. This sensor sends a signal to his HomeMatic server and from there he can collect the data via RestAPI easily into Splunk for reporting. However it’s not just reporting on what days and times he gets post. Thanks to the Splunk Mobile App he can access those dashboards on his iPad and iPhone when he’s traveling.
2. Apple Push Notifications
He has set up an alert if a letter drops into the postbox, and the Splunk Alert is pushed directly via the Splunk App to his screen. That push notification is also displayed on his iWatch. So in case you want to bother Udo – just drive by his house and randomly put something in his postbox 😉 He will get a notification every time and the house will play an announcement.
3. Your Smart Home on one dashboard
Udo is also monitoring his heating system, warm water solar system and measuring the energy consumption of his house.
He has even calculated how much oil is used per day for heating if the sun does not shine enough. To do this he overcame the challenge that his oil burner does not provide information about how much oil it uses. But he does know how long the oil burner is on for and with a nice formula he combined the running time with the oil consumption per minute. The trick is just an eval command:
source=”ccu2″ DiplayName=”Wireless Sensor Burner” state=”*” | transaction startswith=state=”false” endswith=state=”true” | stats sum(duration) as runtime | eval consumption(Liter)=runtime/60/60*1.95*1.17 | fields – runtime
The house is almost self-sufficient: Lights switch on and off if you walk through the rooms, the shutters open and close automatically based on the time of the day and even the washing machine announces when it’s finished. If you want to learn how to say “the washing machine has finished” in German – you can practice here:
I hope this inspires you to Splunk your home too. You can start immediately and in most cases the free version should be more than enough to get started (500MB new data / day). Feel free to share your awesome story!
Jens Ihnow’s Blog – Sunshine and Heating System Monitoring with Splunk
David Greenwood on Building a Weather Forecasting with a RaspberryPo and Splunk