It’s been a slow couple months between the holidays, travelling, and work. I did manage to accomplish a few things with the Home Dashboard project, though. I redesigned the UI to move away from an exclusively mobile interface as the amount of data and type of data I’m including in the project now simply don’t all make sense to squeeze into a mobile UI. Sometime in early January, the system broke the 2 millionth record milestone — I’m unsure what I’ll do with some of the data I’m collecting at this point but I’ve learned a lot through collecting it and I’m sure I’ll learn more analyzing it at some point in the future.
This brings the list of events I’m collecting to:
Indoor temperature and humidity
Amazon Echo music events
DirecTV program and DVR information
Cell phone location and status details
Local fire and police emergency events
Home lights and other Wink hub events
…and now home network information
Analyzing home network information
The biggest change was the addition of network event logging. After seeing that a foreign IP was accessing my LAN, I started logging each request to or from my home network until I was sure I had fixed the vulnerability. After that, I found the information interesting so I just kept logging it. For example, I was able to discover that an app on my phone was making repeated calls (~2,000 per day) to an app monitoring service (New Relic) which wasn’t doing my phone’s battery life any favors.
Collecting additional phone data
After launching Location to HTTP, I’ve been tinkering with additional data collection from my cellphone such as Bluetooth, WiFi, GPS, battery, and screen status. After collecting this information for a month or so, here are some useless data points from the most recent 30 days:
I’ve actively used my phone for 104.5 hours (3.5hrs per day – I need to cut back on the work email…)
Average battery level: 61%
Average free memory: 516MB (12.6%)
Average location accuracy: +/-31FT
Average altitude: 154FT
Average speed: 1MPH
Average uptime: 153.3HRs
Maximum uptime: 437.4HRs
I also improved the location history mapping to show different color map markers depending on the age of the record and phone details at the time the record was made:
Improved home climate visuals
I added some simple graphs of MoM temperature and humidity and also updated the heat-mappings for the daily climate information. These are a bit easier to read that those I had in the previous UI. It’s interesting to see the effectiveness of thermostat automation and our daily routines.
More detailed emergency event
Lastly, I expanded on the emergency event information to surface the top event types and the total number of events by type:
Seattle has a pretty awesome approach to data availability and transparency through data.Seattle.gov. The city has thousands of data sets available (from in-car police video records to land zoning to real-time emergency feeds) and Socrata, a Seattle-based company, has worked with the city (and many other cities) to allow developers to engage this data however they like. I spent some time playing around with some of the data sets and decided it’d be nice to know when police and fire events occurred near my apartment.
I setup a script to pull the fire and police calls for events occurring within 500 meters of my apartment and started storing them into a local database (Socrata makes it so simple – amazing work by that team). While reading it from the API, I check the proximity of the event to my address and also the type of event (burglary, suspicious person, traffic stop, etc) and trigger emails for the ones I really want to know about (such as a near by rape, burglary, shooting, vehicle theft, etc). I decided to store all events, even traffic stops, just because. I may find a use for it later – who knows…
After I’ve scrubbed through and sent any notifications for events I care about, I display the data in a simple table in my existing home dashboard and highlight red any rows for events which are within certain square area of my apartment.
To add a nice visual, I also plot the most recent events on a map using the Google Maps API. Police events are noted with blue pins, fire events are noted with red pins:
Clicking the pins will give us some details about the event:
All told, it was a pretty simple project which helped me gain some experience with the Google Maps API and also poke around with some of the data the city provides. I’m sure I’ll be doing a bit more of that in the future. These two projects have been integrated back into my home automation dashboard so I can continue to build on them in the future.
As mentioned previously, my goal wasn’t to just create a home controller/dashboard but to also collect as much data as possible while doing so. So tonight, I started playing around with a few different visualizations of the data I’ve collected thus far. It took a few hours but I’m satisfied with the current state.
I’m doing simple dumps of the most recent music played by my Amazon Echo; most recent programming watched via DirecTv; visualizing the daily average, minimum, and maximum temperature and humidity levels in my apartment; visualizing by hour of day the average, min, and max temperature for the current month vs the previous month; breaking down the amount of time I spend at home by day of week (and telling on myself that I like to leave work early on Fridays :)); and visualizing my TV watching habits by hour of day and day of week.
I recorded a video of this all and also included the DirecTv control demo at the end.
The original design wasn’t “clean” feeling and didn’t function too well on mobile or even tablet displays. I changed that up a bit and the new design has a lot of transparent divs, bokeh background images, and some jquery to make actions a bit smoother.
Wink Integration Improvements
The initial integration of the Wink API wasn’t that great. I was using PHP to trigger shell scripts which would then make the API call – quite messy and had several opportunities for failure. This method also made a new request for a bearer token each time an action was taken so if I turned on three lights, I requested three unique tokens from the API. I’ve since cleaned that up and now use a single token per session and the API calls are all made in a single PHP file. This still isn’t the cleanest or safest way to do this but it works for my usecase.
While doing this, I also added the ability to dim some lights (such as the kitchen light which we leave on during the night). The next step is to fetch the current state of the lights so that we can eliminate the on/off option and simply toggle it. The problem with that is that the Wink Hub struggles to maintain accurate states for its devices.
I integrated TheMovieDB.org‘s API to pull images of the movies or shows that are currently on. This currently works very well for movies but it often fails to find images for shows so I’ll loop back to fix that at some point in the future. I also added in a link to view the title on IMDB for easy access. An alarm was added to trigger a notification if the DVR is nearly full.
Mapping GPS Coordinates
Out of sheer curiosity, I decided to push my phone’s GPS coordinates to my server and plot them on a map. I’m using the SendLocation app to push the coordinates to a script I have setup to listen to the app. This may, perhaps, help me locate my phone one day if I ever lose it. For now, though, it’s merely something for me to play with. I’m also capturing things like speed so I can view when I’m in transit. Essentially, this traces my steps.
MQ2 Sensor (Gas/Smoke)
I added an MQ2 sensor to the PI and set it up to store the current state as well as send me a text message and email if it detects something. Overall, the setup is pretty simple and certainly isn’t life-saving but does serve the goal of being able to monitor home while away.
Here’s my Python file I use which I simply schedule a cron job to ensure it’s monitoring frequently enough to be useful (note the loop of 20 and sleep of 3 seconds so it runs for the entire minute before the cron fires again):
I’ve changed the interior camera to disable itself if anyone is home. There’s no need for it to run if during that time and it also ensures an additional layer of security/privacy.
The date formats were updated to provide “friendlier” outputs. I also added a time of day greeting for the active user – “Good morning/afternoon/evening/night”…
My favorite Google News RSS feeds were added to the left and a weather forecast link was added. I also included a calendar with the eventual goal of integrating the Google Calendar API (I use Google Calendar quite heavily). These are hidden by default in order to maintain the “clean” UI I’m going for.
Let’s just get it out of the way now — there’s no true practical purpose or value in doing this. I took this on as an experiment and opportunity to learn something new.
What is it?
Using a Raspberry Pi, some sensors, and a lot of Googling with trial and error, I took my first step into custom home automation (Wikipedia). I can control lights, DirecTv receivers, some appliances, measure indoor temperature and humidity, determine who is home, and view indoor/outdoor webcams through a single UI.
Each tailed light uses a GE Link bulb which is connected to a Wink hub. This allows for on/off control, dimming control, on/off scheduling, and dimming scheduling (such as gradual increases in brightness in the mornings). Wink comes with a nice app but I opted to use their API so I could incorporate it into the custom UI/dashboard along with everything else. Cameras
I’m using an old D-Link camera to gain outdoor views and the RPI camera for inside the apartment, I setup scripts to take snapshots once every minute and dump them into a MySQL db running on the Pi and also update the snapshot to include in the UI. Weather Reporting
Outdoor weather (temperature, “feels like” temperature, humidity, pressure, and windspeed) is pulled from Yahoo! XML weather feeds.
Indoor temperature and humidity is polled every minute using a DHT11 sensor attached to the RPi. Historicals for all of these are stored in a MySQL database with the intention of graphing these some time in the future. I’d like to incorporate a Nest-style thermostat for indoor climate control but, alas, I’m a renter and don’t want to deal with that. Who’s Home?
Using a Bluetooth dongle attached to the RPi, I poll for cell phones to determine who is home and who is away. Every minute, I log the status of all detected Bluetooth devices so we can see who’s around. This is also stored in a MySQL db so I can go back in time. DirecTV Control
Using the DirecTV SHEF API, I currently poll the current program title, the channel number, the station ID (ie NBC or HBO), the program rating, whether or not the DVR is recording. The API allows you to take full control of the receiver and do all actions you can with the remote but I don’t see much value in that as I can’t watch it while I’m away so why have the functionality… Appliance Control
Using WEMO plugs, I can power on/off appliances. This came in handy at Christmas when the outlet was located directly behind the Christmas tree. At this point, though, there aren’t many appliances I want to control with the Wemo so I have a few of these sitting idle.
Automation and Availability
Amazon Echo Integration
All of these devices have been integrated with the Amazon Echo device either via Echo skills or via IFTT integration. This allows all of the functionality above to be controlled via voice recognition. There’s some trial and error getting these setup correctly but I think that’s mostly with the Echo’s voice recognition quality. IFTT
With integration of IFFT, I can do any number of things if desired. One of the more useful IFFT setups I’ve found is simply turning on the bedroom lamp ~8 minutes after my alarm goes off and gradually increasing the bulb’s brightness every minute. Another possible option is to turn some lights on when the Pi’s bluetooth dongle detects that I’m nearby. Web Server
In order to make this valuable, I installed Apache on the Pi and used ngrok to tunnel to localhost so that I don’t have to worry about the vulnerabilities of port forwarding on my router. I have this forwarded over to a domain name I wasn’t using and added some .htaccess protection (among other things) to keep it private.
Living in a small apartment limits the value and the opportunities of home automation. Things like adding reed switches to windows and door don’t make sense in my scenario as I doubt anyone will be climbing through my 7th floor window or trying to break into my door. Some more practical things I’ll be doing, though, is adding a gas, CO2, and smoke sensor to the Pi so that I’m alerted via text message and push notification if the Pi detects any of those levels becoming elevated…better than waiting on the neighbors to call the fire department, no? I’d also like to add a PIR motion detector to trigger the Pi Cam to start capturing video instead of still snapshots if motion is detected during hours that I’m normally away from home. I’ve had some troubles getting the motion detector to work but I’ll loop back to that eventually.