## A little bit about light

I’ve been giving myself a crash course refresher on light over the last new months. It started when I picked up a used Laser Cutter and wanted to figure out how it cuts with light. What I’ve written here is my understanding of things. I may be wrong, if so, please let me know in the comments.

My simplification of a CO2 laser is that it’s a poorly designed Neon light that gets way too hot and produces a heat ray that we can manipulate with mirrors to vaporize things. Magnifying lens on a sunny day style. I fear if I ever find an ant in my laser cutter whatever project I was working on will be a total loss as I will be chasing the ant with my laser beam. https://en.wikipedia.org/wiki/Carbon_dioxide_laser

So I now have this really sharp cut thing that I can’t see the blade on. A CO2 laser beam is invisible. If you see a red dot on a laser cutter, that is a separate cat-toy style red laser put in place so we can guess about where the actual invisible laser will do it’s thing.

My laser cutter’s light is 9.4-10.6 micron wavelength. This is the same wavelength that Humans glow in the dark. Well, everything room temperature glows at this light frequency or ‘color’.

## Deep Infrared

A thermal camera can see light in this ‘Deep Infrared’ zone. I have a Seek Thermal camera that plugs into my cell phone which allows me to see effectively 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 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.

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.

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. Because, you know, science and stuff.

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. Because, you know, lazy and stuff.

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 deep 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. CLICK. OH, that’s why “Low E” windows are better, they reflect heat. I get it now.

## Near Infrared

Another portion of light, called Near Infrared, has some interesting properties as well. 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 camera 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 as to 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.

There is a gadget that takes advantage of these useful properties. The SCiO which is a Near Infrared ‘scanner’.

This little device 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.

Amazing!

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.

Understanding how a fancy new tool works ‘under the hood’ helps me manage my expectations of what the tool can and can’t do well. I can ‘hack around the edges’ of it’s capabilities because I understand what the edges of capabilities are and why they exist.

## 2nd layout of the Mobile Science Lab

I added more items to the Mobile Science Lab.  The main new item is a WeatherFlow WEATHERmeter. This is a pretty neat bluetooth device that captures wind speed and direction, temperature, humidity, and barometric pressure.

New stuff means I needed to update the case.  I fiddled a bit to get everything to fit.  I think the next iteration will end up including layers.  I will need to find some laser safe foam core or something light like that.  The cardboard won’t hold up all that well when there are removable sections.

I ordered a much larger Pelican case tonight. The SCiO I am ordering at the end of the week should fit into the new case.

I’ve also added some NFC stickers a few places to make using the bits a little easier. The case has my contact info embedded in it.  The WEATHERmeter is now set up to just tap the phone against it and the correct App will load.

## Backpacking recipe – Chicken Quinoa.

I tried a backpacking recipe on a soda can alchohol stove On my Altoid tin stove tonight.  I rather liked it,  so I am putting it here so I can find it again if I remember to look here.

## Chicken Quinoa

• 1/2 cup quinoa
• 1 Tbsp dried chives
• 1 packet of True Lemon
• 1/4 tsp ground coriander
• 1/4 tsp ground cumin
• 1/4 tsp paprika
• 1 3-once foil packet of chicken

I used Lemon Essential oil because that is what I carry. I also used a tin can of chicken,  water and all, so it was too wet,  so I added some gelatin to thicken it a bit. Also,  parsley instead of chives.  It would have been better with the chives.
Recipe is from http://www.wildbackpacker.com/backpacking-food/recipes/backpacking-dinner-recipes/ with more like it.

## Internet of Things Phone Smart Charger

I pre-ordered one of the Samsung Galaxy Note7 phones. The ones in the news recently for being an explosion hazard.

I love the new phone – pocket computer really, the way I use it. I wasn’t about to give it up over some silly thing like spontaneous combustion.

I had read that Tesla runs their car batteries between 40%-80% for normal use to maximize the lifetime of their very expensive car batteries. I figured that cell phone batteries would benefit from similar treatment. A bit of research generally confirmed this, with http://batteryuniversity.com/learn/article/how_to_prolong_lithium_based_batteries being the most concise write-up. The first half basically demonstrates that you can get the same amount of total power to flow through the battery regardless of how much you charge it – summed over the total life of the power draw in the data tables. The 2nd half is more interesting. It says that high voltage charges and heat shorten the overall lifespan of the battery.

The Note7 is a sealed phone wihtout a replaceable battery. I can’t pull my usual trick of replacing the battery after a year of abusing it.

Heat seams to be the trigger for the phone explosions. So I can make my phone more safe, and make it last longer by managing the top voltage and heat in the battery.

I can do this.

I bought a wireless Qi charger to charge the phone because it charges slower. The fast charger can charge the phone crazy fast, but it gets HOT when it does this. Hot is bad. Thus, slow is good. The wireless charger will also reduce wear on the USB C port. A nice side benefit. No phone explosions while I sleep and burn the house down – this is a good thing.

I bought a Belkin WEMO wifi controlled outlet. It is If-This-Than-That (IFTTT.com) capable so I can control it from my phone. There are other smart plugs available that will work, this is simply the one I could find in a store that I could verify would work with IFTTT.

I configured IFTTT to have 2 different actions. One for turning the WeMo on, the other off. I set these up as Maker Channel triggered recipes. There are other triggers that you can use such as email or SMS, but I am a web developer, so web-based triggers are a natural fit for me.

I installed Tasker on the phone and configured it to monitor charge state and battery temperature.

I created 3 tasks, one to turn the charger on, and two to turn it off.

The ON trigger looks for the battery to be below 80% charged, and below 35 degrees Celsius. This will make a request to the IFTTT.com Maker Chanel URL for ON.

One OFF trigger looks at the battery temperature. 35.1 degrees or higher. The other OFF trigger looks for the battery charge to be 90% or higher. These two both make a web request to the IFTTT.com Maker Chanel OFF URL I set up.

So now as the phone battery heats up or gets close to full, the phone tells the charger to turn off. I let the phone have a 10% charge window so I am not toggling the switch and charger on and off all night long.

I also programed the WeMo to turn itself on a little while before my alarm is set to go off. This is to let the battery be closer to 90% charged rather than 80% charged when I wake up. I haven’t found the right time for this yet. I still need to play with it a bit.

I know there are other ways to make a smart phone charger. This is what I came up with. I will be getting an additional smart plug and building one for at the office so I don’t over-charge my phone when at work. I will try a different brand likely to see if I can come up with a cheaper way.

## Lightening talk slides

Slides for a lightening talk.  Easiest way to publish this, post it to my blog.