🔴 ALERT: This repository is no longer maintained. Please see current version: https://github.com/cpitzak/room-weather
This is a live demo of the weather of my room. Page updates without needing to refresh.
https://weather-clintpitzak.rhcloud.com
Architecture of Demo: This demo uses an instance of mongodb hosted on mlab.com (free acount with 500 mb of space). Status: http://status.mlab.com/
And uses https://www.openshift.com/ to host my weatherWeb website (free account for up to 3 instances of an application. They changed their policy on free accounts but mine and other people who are already registered stay the same). And my raspberry pi runs the weatherService and DHTService I wrote to updated mongodb with the hourly outdoor and real-time indoor weather. You can see the architecture for the demo was designed to have this run for free :)
This is a website I made to see the current and hourly temperature and humidity of my room compared to outside. This website also displays the current temperature feel and cloud cover via an image. The predicted hourly outside forecast is known from 12:00 AM to 11:00 PM for the day (forecast updated every 15 mins from wunderground, see my other project weatherService). The room temperature is updated every 5 seconds via a DHT22 sensor that is connected to a raspberry pi (see my other project dht22Service). This website updates dynamically (no need to refresh the webpage).
I have this website start when my raspberry pi is loaded. My raspberry pi is always on and this website is accessable to me on my LAN via http://private_pi_domain_name:3000
This website is to be used with my other two projects dht22Service and weatherService.
I made this website to be able to know what the temperature will be like for my room during the hot summer days so I can plan accordingly. The main motivation was the heat of the summer however it will be useful for the cold winters and regular days. The first phase is what you see below. This has been useful to know the optimal time to open the windows and when it would be good to be out of the house.
The next phase, after gathering several days/hours of temperature data, is to add machine learning to predict what my hourly room temperature will be for the hours of the day.
You need to have the following installed:
Install and run via Docker (Weather Web Docker Repository):
$ docker pull cpitzak/weather-web:1.0.0
$ docker run -e "WEATHER_WEB_MONGO_URL=mongodb://your_mongo_url/weatherdb" \
-e "WEATHER_WEB_TZ=your_time_zone_default_is_PST" \
-p 3000:3000 \
cpitzak/weather-web:1.0.0
Or Build a docker image and run
$ docker build -t cpitzak/weather-web .
$ docker run -e "WEATHER_WEB_MONGO_URL=mongodb://your_mongo_url/weatherdb" \
-e "WEATHER_WEB_TZ=your_time_zone_default_is_PST" \
-p 3000:3000 \
cpitzak/weather-web
Or to setup Manually
$ sudo mkdir /apps
$ sudo chown pi /apps
$ cd /apps
$ git clone https://github.com/cpitzak/weatherWeb.git
$ cd weatherWeb
$ sudo cp init.d/weatherWeb /etc/init.d/
$ sudo chmod 755 /etc/init.d/weatherWeb
$ sudo update-rc.d weatherWeb defaults
$ sudo update-rc.d weatherWeb enable
$ sudo systemctl daemon-reload
$ npm install -g bower-npm-resolver
$ npm install
$ bower install
$ sudo service weatherWeb start
Screen shot taken around 9:30 pm at night.
