Add static sensor charts

content/Sensors.md

@@ -1,17 +1,63 @@
 Title: Sensors
 Date: 2022-05-24
 Category: Notes
-Summary: A dashboard for various sensors around my house.
+Summary: Graphs of various sensors around my house.
 Short: d
 
-I wrote a custom [dashboard](https://sensors.dns.t0.vc/) to visualize data from various sensors around my house. I'm a huge fan of sensors because they're at the intersection of what I love: electronics, home automation, and data hoarding.
+## Graphs
+
+These graphs are live and updated once per minute, assuming the script works:
+
+![a graph](https://sensor-pics.dns.t0.vc/Solar_Power.png)
+
+Black: power (W), green: energy (kWh)
+
+![a graph](https://sensor-pics.dns.t0.vc/Living_Room_Air.png)
+
+Black: PM10 (ug/m³), red: PM2.5 (ug/m³), blue: CO₂ (ppm), green: VOC / 500
+
+![a graph](https://sensor-pics.dns.t0.vc/Outside_Temperature.png)
+
+Black: temperature (°C)
+
+![a graph](https://sensor-pics.dns.t0.vc/Bedroom_Temperature.png)
+
+Black: temperature (°C), green: humidity (%)
+
+![a graph](https://sensor-pics.dns.t0.vc/Nook_Temperature.png)
+
+Black: temperature (°C), green: humidity (%)
+
+![a graph](https://sensor-pics.dns.t0.vc/Misc_Temperature.png)
+
+Black: temperature (°C), green: humidity (%)
+
+![a graph](https://sensor-pics.dns.t0.vc/Nook_Thermostat.png)
+
+Black: temperature (°C), red: setpoint (°C), green: state (off / heating / cooling)
+
+![a graph](https://sensor-pics.dns.t0.vc/Gas_Usage.png)
+
+Black: total (MJ), green: delta (MJ)
+
+![a graph](https://sensor-pics.dns.t0.vc/Water_Usage.png)
+
+Black: total (L), green: delta (L)
+
+![a graph](https://sensor-pics.dns.t0.vc/Living_Room_Lux.png)
+
+Black: light (lx)
+
+## Live Dashboard
+
+A live interactive version can be found on this [dashboard](https://sensors.dns.t0.vc/).
 
 You can find the [source code](https://git.tannercollin.com/tanner/sensors) on my Gitea.
 
-![[sensors1.png]]
+## Data Capture
 
 Most of the data is captured by two cheap RTL-SDRs (software-defined radios) that are set to listen to 433 MHz and 915 MHz radio frequencies. I use the open-source project [rtl_433](https://github.com/merbanan/rtl_433) to automatically decode the signals and forward them to an MQTT broker, which is a messaging server that services can publish and subscribe to. Other sensors run an MQTT client directly or expose their data through other means like a web interface that I poll.
 
 The data gets collected by a central Python script that process and stores it in an InfluxDB database for "efficient" storage. The script also runs a web server that queries the database and exposes the data over an API to the dashboard at various dates and ranges. The dashboard is written in JavaScript / React using a simple chart library.
 
-My biggest regret was using InfluxDB. It's a stupid database and I wouldn't recommend it to anyone. The documentation is confusing and I ran into timezone issues with `group by time()`. It also assumes the column data type is an integer if your sensor happens to send it a whole number at first and it won't let you change that. Just stick to Postgres / SQLite.
+My biggest regret was using InfluxDB. It's a stupid database and I wouldn't recommend it to anyone. The documentation is confusing and I ran into timezone issues with `group by time()`. It also assumes the column data type is an integer if your sensor happens to send it a whole number at first and it won't let you change that. Just stick to Postgres / SQLite.