Hi everyone, I’m Thorsten, and I’m currently working on optimizing my smart home energy monitoring setup. I use a Tasmota-based infrared sensor head to pull data from my energy meter. To visualize this data, I’ve created a template sensor in Home Assistant, but I’m running into some challenges with data accuracy.
Here’s how my setup works: The sensor reads the energy consumption data, and I’ve added a conditional check to ensure only valid data is used. If the value is greater than 10, it’s considered valid, and I round it to four decimal places. Otherwise, it defaults to another sensor’s reading. This works most of the time, but occasionally, the sensor delivers incorrect or incomplete data, which messes up my energy statistics.
I’m curious if anyone has encountered similar issues and how they’ve tackled them. Are there smarter ways to filter out outliers or handle missing data? Maybe using rolling averages or implementing a more sophisticated validation process? I’d love to hear your thoughts and experiences!
If you’ve successfully implemented a robust data filtering system, please share your approach. I’m especially interested in methods that maintain data integrity while minimizing manual intervention. Let’s brainstorm together and make our energy monitoring setups more reliable!
Cheers,
Thorsten