Mobile Science Lab

Here is my Mobile Science Lab. This is using a mobile phone as a computer and data collector that allows me to do ‘sciencey’ stuff on the go. It is a collection of phone apps, accessories, and general tools and items.

The current form of the Mobile Science Kit

The running commentary about the assembly and use is found elsewhere on the blog.

I have a working TODO list with reference links if you want to see the direction I am going and make suggestions.

The lasercut insert for the case is designed in OpenScad so it could be 3D printed instead of laser cut. I have the source files on github if anybody wanted to reuse some of my shapes and save some time on their own kit.


There are many phones out there that will work. I currently have experience with 2.

Samsung NoteEdge

This phone has some handy premium options as part of the S-Health package.

PulseOximiter will measure your heartbeat and your blood oxygen levels. This is handy if rarely used feature.

UV Light sensor tells you how likely you are to sunburn.

Nextbit Robin

The missing USB OTG (On The Go) capability limits this phone from using USB based sensors such as my thermal camera.


First lets start with some of the phone apps that can make this project possible.

Science Journal

Science Journal is a simple app from Google.  It is a simple data logger of the sensors built into the phone. My NoteEdge provides a good number of sensors.

  • Ambient Light
  • Sound Intensity
  • Accelerometer in X, Y, and Z
  • Barometric Pressure


You can get a good many electronic accessories for your phone that can assist in your scientific exploration of the world. These listed are just the ones I have.

Consumer Physics SCiO

I don’t have this one yet, but it’s going to be the flagship item in my kit.

A portion of light, called Near Infrared, has some interesting properties. First off, things that aren’t metallic (reflective) are rather transparent. Things look kinda like jello at these wavelengths, the light can see into them a ways. A couple of centimeters often times.

The Near Infrared has another interesting ability. Oils, fats, sugars, alcohols, and proteins absorb certain frequencies of light – they have colors (for lack of a better word) – in this range. Click here to Geek Out on Near Infrared. This means that a sensor that uses Near Infrared is very useful around the house. We can look at something, and judging by it’s ‘color’ in Near Infrared, we can make a good guess about what is made of, or at least major components of it. We can’t see near infrared, so we tend not to manipulate the colors in that range.

The SCiO is even cooler than the thermal camera. It’s small, and can tell you the interesting bits about your food like how many calories and of what type (fats, carbs, protein) are in it. You don’t have to guess at a restaurant if you are tracking your diet anymore.

This doesn’t work like a camera, it is instead a spectrograph. It doesn’t take a picture of stuff, it instead looks at all the colors that are present like how a prism works. You scan something with a SCiO and it breaks apart the intensities/brightness of different wavelengths of light (those would be the colors if this was visible light) and looks up what it sees against a database of stuff that it knows about and when it finds a match, tells you what it is looking at.

If we were to present only pure substances it would be able to tell us what things are easily. However, we don’t have much of anything that is truly pure. Table salt, sugar, baking soda, for the most part tap water are about all I can think of commonly around the house. Most of the stuff we interact with is made up of a variety of things.

This is where we get clever with the SCiO. Instead of needing to extract out the stuff into individual bits (imaging taking a baked cake and separate it back out to it’s flour, sugar, eggs, milk, water, etc) we just capture what a thing looks like in different bits of Near Infrared light and correlate it to things we’ve told the SCiO what they are previously.

The thing that makes this work is that we LIMIT THE DOMAIN of what things are so the SCiO has a chance at making a reasonable guess. For example, there are a lot of things that are Red. Lego, fancy cars, strawberries, some apples, etc. If we showed you a particular shade of red, and asked you what was that color, you can come up with a lot of wrong answers that are that exact shade of red. But if we said we have a berry that is this particular color, you would be able to tell very easily what it is most of the time. Especially if you can look back against other color samples and compare what you have now with what you have seen in the past.

So for the SCiO to work well, we need to train it. We get together a bunch of things that we want to tell apart if it’s not properly labeled. We then teach the SCiO this thing is X, that thing is Y. We can than ask SCiO what is this stuff, it’s something that belongs to this group that we trained it on.

An example could be clear liquids. Clean water, vodka, strong vodka, watered down vodka, rubbing alcohol, denatured alcohol, clear soda, vinegar. These things all look similar to our eyes. They will all look different from each other in Near Infrared. We can train the SCiO about all of these clear liquids, and when we find a glass of one and we don’t know what it is, we can check with the SCiO.


There are some ways in which the SCiO can fail.

  • Shiny mirror like surfaces tend to reflect all light, regardless of the wavelength. Metals for example. We also see this in Visible light as well as Deep Infrared.
  • Things that are black – they absorb light – tend to absorb all frequencies of light including Near Infrared. Things that have been colored black will likely be black to the SCiO as well, and it can’t get a good read on them.
  • Only the major components of something can be read by a SCiO. If there isn’t enough of something to make a strong ‘color’ influence, it simply can’t be read. A SCiO can ‘see’ stuff that is more than 1% or so of the overall item.

Seek Thermal Camera

This is a thermal imaging camera that plugs into the USB port of many cell phones. It uses the phone screen to display what it can see. This is a VERY cool tool. It allows you to see heat.

A thermal camera can see light in a portion of what is called the ‘Far Infrared’ zone. Specifically the 9-14nm wavelength area where all things ‘glow’ as they give off heat.

I can walk around and find things that are plugged in that are doing a bad job of being off, and give off heat because they are still on. I can tell the temperature of about anything, just by looking at it with my cell phone. I can also look for things that are supposed to help keep me warm and are failing at their job like doors and windows.

A Deep Infrared image of a Kurig Coffee Machine
A Kurig Coffee Machine that wasn’t told to ‘power save’. It’s been heating up since it was plugged in.

Except nothing is ever that simple. Materials have a property called ‘emissivity’. This is how well they emit light at a certain wavelength. Things that emit light well, tend to absorb light well. Things that don’t emit well tend to be reflective in nature.

Humans have a pretty high emissivity about .98 (with 1 being perfectly emissive and 0 being perfectly not-emissive) so we need clothes to stay warm as we would glow all of our heat away without them. But because we are highly emissive, we can absorb heat well too, so this is why you can feel heat being given off by things like hot pans, light bulbs, and turtle heat lamps, and sitting in a sunny spot.

You can see here that I glow. My clothes hold in some of my heat and my glasses block the Deep Infrared light.
You can see here that I glow. My clothes hold in some of my heat and my glasses block the Deep Infrared light.

Things such as shiny metals have a low emissivity, so they tend to reflect heat like a mirror. This is how camping space blankets work. The thermal ‘glow’ that us humans have gets reflected back at us. We absorb a lot of this reflected heat, so space blankets feel warm to us.

But, what this means, is that my fancy thermal camera can’t take accurate temperatures of shiny metal things. What I am really taking the temperature of is the things reflected on these ‘heat mirrors’. To do a good job using thermal imaging for temperature reading the more expensive equipment has material tables that you can assign to spots that have a lookup to a emissivity table so it can calculate the proper temperature based on what it sees.

I am going to carry some electrical tape which has a pretty high emissivity number around .96 and just stick that on things I want a proper temperature of.

Materials have some pretty funny ideas about what is ‘clear’ and what is ‘opaque’ at wavelengths other than what we can see with our eyes. Thin plastic bags that we can’t see through are transparent to far infrared. Stick your hand in a bag, you can see your fingers as clearly as if the bag wasn’t there. Windows, glasses, things that we see through all the time are as black as night to thermal. “Low E” windows are not only black to thermal, they are reflective as well, so you can see your heat reflection in a ‘good’ modern window.

WeatherFlow WEATHERmeter

This is a bluetooth weather station that fits in the palm of your hand.

  • Wind Speed & Direction
  • Temperature
  • Humidity
  • Pressure