Also crashes for me with 0.2.1
Also crashes for me with 0.2.1
Found this comment with some links. Couldn’t find anything from an admin during my short search.
The exact same problem arose for Voyager users in March when Voyager dropped support for Lemmy 0.18.
For some people logging out and back in has helped but I’ve seen multiple beehaw users state that this doesn’t work for them.
This seems to be because beehaw is intentionally staying on an old Lemmy version.
Not sure how the Dev wants to handle this since they’ve got enough work on their hands and this issue should resolve itself once beehaw upgrades.
For now your best bet is to try re-logging and if that doesn’t work to roll back to a previous version of Eternity.
This person had the same issue and they’ve just logged out and in again
Always mocking Dr. Daniel Jackson. Poor guy
Additional information regarding Home Assistant:
The sun component (which should be enabled by default) already computes the sun position for you.
Elevation and azimuth are available as standalone sensors sensor.sun_solar_azimuth
(might be disabled by default) or as attributes on the sun.sun
entity.
Not an expert but these systems are fairly self-contained and robust. A few things that can be checked easily is that the fan spins, the radiator is free of debris and some compressors might have a sight glass for the oil level.
Any other checks regarding performance of the system, leaks and refrigerant level require you to perform a full refrigerant discharge and recharge. That takes special equipment and some time so no one in their right mind would do that for free, unless they can then force/guide you into some kind of upsell situation.
Larger systems might have some kind of oil filter/catch-can that you might be able to check easily but I’m not too sure on that.
After all heat pumps are just plain old A/C units with a reversible cycle.
I don’t have any experience with it but this might do something along those lines(?):
https://esphome.io/components/binary_sensor/ble_presence.html
Seems like you can just add it to one or more of your existing esphome devices.
Cushy is an experimental Graphical User Interface (GUI) crate for the Rust programming language. It features a reactive data model and aims to enable easily creating responsive, efficient user interfaces. To enable easy cross-platform development, Cushy uses its own collection of consistently-styled Widgets.
Und an dem Punkt könnte man die Routen und Fahrzeiten dieser Fahrzeugverbände zentral steuern, damit sie immer grüne Welle haben.
Dieses Werk könnte man zB ein Stell-Center nennen.
The 44.1% battery failure figure is regarding the “starter” battery (12V) and is combined from all vehicles in the study (EV and ICE).
The HV Battery for the traction drive is grouped together with any kind of motor failure and comes in at 22.8 %. But this figure also includes ICE vehicles ejecting piston rods etc.
The only EV vs ICE numbers stated directly are the total breakdowns per 1000 vehicles at 1.9 (EV) and 3.6 (ICE).
I’d be really interested in a chart showing the failure categories separated by EV and ICE.
Dr. med. Maurice Cabanis (einer der Experten) ist schon ein bisschen sus
Dann lieber auf das Kreuz:
Auch Mischformen, bei denen die Wurst anstelle von Jesus direkt ans Kreuz genagelt wird oder bei denen zwei gekreuzte Würste ein Kruzifix (sog. Wurstifix) bilden, sind erlaubt.
Out of curiosity I’ve let it rate Low<-Tech Magazine, a website run on an ARM SBC powered exclusively with off-grid solar power, and that only achieves 87% / A.
Can’t exactly remember which car it was but some of the early and smaller EVs didn’t necessarily come with a navigation system. Think along the lines of Chevy Bolt or Nissan Leaf.
Not OSM or Open Source but “A Better Route Planner” (ABRP) was one of the first good EV routing apps and got pretty popular.
Especially early on it was often smarter than the built-in routing systems if the car even had one.
Also available as a website: ABRP
And don’t forget about ESPHome which is part of the Home Assistant Project and allows you to easily get your microcontrollers up and running.
If you have such a system up and running already you could try to modify it before ripping it out and starting from scratch.
Borrowing an idea from the machine learning approach you could additionally take the difference in average outside temperature yesterday and the average forecasted outside temperature today. Then multiply that by a weight (the machine learning approach would find this value for you but a single weight can also be found by hand) and subtract it from the target temperature before the division step discussed previously. Effectively saying “you don’t need to heat as much today since it will be a little warmer”.
I fear that’s about all you can do with this approach without massively overcomplicating things.
Why not set up backups for the Proxmox VM and be done with it?
Also makes it easy to add offsite backups via the Proxmox Backup Server in the future.