Build a Raspberry Pi Vehicle Interior Monitor – Temperature Monitoring

Posted by Graham Smith on September 9, 2017No Comments (click here to comment)

In this blog series I'm documenting my maker journey as I build a Raspberry Pi-based vehicle interior monitor (PiVIM). This is the full list of posts in the series:

In this post I get to the main aim of the project which is to be able to monitor temperature. In so doing I'm entering the exciting world of physical computing with the Raspberry Pi by hooking up a temperature probe to the Pi's GPIO pins. I'm using the Dallas DS18B20 sensor which comes in two forms: one looks like a transistor and the other is packaged in to a probe with a long wire attached. I'm using both: the transistor format for prototyping and the probe version for the final version of PiVIM.

The big question that had been on my mind was how to get temperature measurements displayed on a mobile phone. In the previous post in this series I described how I'm giving my Raspberry Pi connectivity through a mobile broadband connection, but then what? There are probably multiple ways to do this but for now at least I've solved it using a data analytics service for IoT projects called Initial State.

Monitoring Temperature with the DS18B20 Sensor

Using the DS18B20 in conjunction with the Raspberry Pi is straightforward and there are a couple of handy tutorials that explain the process:

It's fairly straightforward and there's little point in repeating it in full here, however in summary the steps are:

  1. Build the circuit on a breadboard and connect the jumper wires to the Raspberry Pi header pins.
  2. Configure the Raspberry Pi to work with 1-wire devices (the DS18B20 is a 1-wire device).
  3. Write code (ie a Python script) to read the temperature from the 1-wire interface.

You can find the code which I adapted from the two tutorials listed above on my GitHub site as temperature.py. Outside of the PiVIM module I wrote a simple script called temperature_debug.py to ensure temperature.py was working.

Streaming Temperature Data to Initial State

Initial State is a cloud service that allows you to stream data to its portal and then analyse and display it in various formats. For Python users there is a supplied library that does all of the heavy lifting and it's surprisingly easy to get started. I recommend watching their "From Login to Live Data Stream in 2 Minutes" YouTube video:

Do be sure to create the example (explained in the video) as it's a great way to get a feel for how everything works. You can find their complete list of tutorial videos here.

For my project I created a Python module called data_portal.py which you can find on my GitHub site by following the link. The module is as follows:

The essence of Initial State is that you stream data to its portal as key-value pairs in to what Initial State terms buckets -- very simply containers for your data. A bucket is configured by instantiating the streamer object with the name of the bucket, the bucket's key (which must be unique in your account) and your personal access key. (If you are using a public code repository such as GitHub make sure to pass your access_key value in on the command line so you don't expose it to the world.) In the free version of Initial State data only persists for a day which is fine for me since I'm not interested in doing any historical analysis. I did want to create a new bucket every day so I could see the latest bucket to select in the web portal and achieved this by appending the current date to the bucket name and key. A bucket can receive multiple key-value pairs but in my case only one is needed—a key of T (for temperature) and the temperature value for each measurement.

In order to test the module I created a very simple data_portal_debug.py script, the key parts of which are as follows:

Note how the code is written to facilitate passing in the access_key in on the command line.

So how does this look in the Initial State portal? While there are several ways to view your data I prefer a simple tile displaying the latest temperature:

I created this myself by ensuring I'd selected my bucket and then clicking on the View Tiles App icon and then Edit Tiles. The screenshot below shows how to configure the settings to achieve the desired result:

So far so good, but I'm viewing this in a browser on my workstation and I need to be able to access it on my mobile phone. That's no problem of course because I can just access the Initial State portal on my phone. With Chrome on Android I can actually make this even slicker by using Chrome's Add to Home screen feature (when logged in to Initial State) to place an icon on my Home screen that gets me straight to Initial State's portal, making it feel as if it's an app even though it's not. This is what I see on my phone after selecting the desired bucket:

It's pretty neat considering it's free and on the portal side all I've had to do is a bit of quick configuration. Of course, if you want more features and / or want to store data for future analysis Initial State have paid-for subscriptions.

Cooling Down

That about wraps-up this part of my maker journey. I might revisit this section in the future and have a look at other options, since I would like to have the ability for advanced features such as my phone receiving an alert if the temperature reached a threshold level. This would likely require the development of a smartphone app as well as integration with a cloud service to host the data. A fun project, but not until I have a first version of PiVIM finished and working! Next time I'll be looking at options for powering PiVIM and also turning the Raspberry Pi off.

Cheers -- Graham