Building a Home PC Lab

Trigger warning: This post (and potential series) is going to discuss some AI/LLM stuff. That’s only a part of what’s going on, but if you hate all things LLM, then maybe this post isn’t for you.

Reasons for Building a PC

I haven’t built a PC in probably 25 years now. Even then, I had the kind assistance of two friends who knew a lot more about PC building than I ever did. More recently I’ve been interested in building a PC for a variety of reasons:

The intellectual exercise of building something, mostly out of parts, all by myself
Having a PC running Ubuntu / Linux, something I’ve toyed with now and then, but never really tried in earnest. I already eschew most closed source software in favor of open source alternatives¹ , so moving to an open source operating system seems almost natural.
Some of my personal information currently resides on a computer I use for work – and I’d like to create a clean separation of these things for a variety of practical reasons.
Having an inexpensive and dedicated box would let me sandbox certain programs, try out different new ideas, and still let me access all this information and processing power remotely, if set up properly.
Yeah, I wouldn’t mind an Iron Man style Jarvis virtual assistant / butler, but the technology is still a fair bit aways as are my own skills and budget for such things.

Building in Parallel

I’ve taken to “building in parallel” for several recent projects. With the recent remote temperature sensor system, I tried taking measurements with an infrared heat gun, then an ESP32C3 module with lots of wires, then several Wemos D1 Mini modules each separately sending data back to my PC. While the ESP32C3 systems were still (mostly) working, I recognized some of the weaknesses and failure points and began working on the Wemos systems and didn’t take the ESP32C3 sensors offline until the Wemos sensors were up and running. There was certainly overlap for a little while, but this also let me calibrate both systems. I enjoyed working on these things, so building an entire second set of sensors in exchange for doubling the price and quadrupling the soldering wasn’t a horrible experience. I’m reminded of a quote from Contact, “First rule in government spending: why build one when you can have two at twice the price?”

As with those sensors, I’ve had some automated projects running constantly lately. Something that downloads a huge work calendar daily, a few simple reminders, something that sends me reminders over a messaging platform, and a few other assorted digital doodads. I’m keeping all of these online, on my work PC, until I can get the Linux box going – then I’ll look forward to closing these down.

Pricing Things Out

As with nearly any learning experience, you end up paying for it one way or another – money, tuition, wasted attempts and materials, time. Partially because I’m just starting out and partially because I’m fairly frugal, I set a budget of ~$250² If I’m going to spend any money at all, I wanted something that would work – but I’m not ready to drop $5k on RAM/GPU/newest processors. My needs are still modest – and largely covered by my equally modest work computer. It’s an Intel i7 with 32GB RAM in a very small mini PC case, handles email, big spreadsheets, graphic programs, python projects, and even 3D modeling and rendering with OpenSCAD if you give it enough time. It cost $550 before tax, new from Amazon, nearly 4 years ago, and is still going strong.

For this project I contemplated going with a fanless headless system, but these seemed to require special aluminum cases and appeared to be little harder to come by. I thought about tracking down some e-waste resources, Facebook Marketplace, and Craiglist – but all of these require a fair bit of legwork and I feel like they’d also have more than a modest possibility of wasted time. Any new PC would set me back at least $500 through either Amazon or Costco, so I turned to eBay since the rating system provides at least a modicum of quality assurance – if not in the product, at least the seller.

There are a ton of options for older PC’s that can be given a new lease on life with Ubuntu and some extra memory. I’m still pretty biased against Dell, HP, and Gateway for producing sub-par consumer grade computers for myself, family, and friends. Some noodling about and half-hearted research suggested that these brands may produce significantly better enterprise machines than their consumer grade lines. This only irritates me even more, if true. This pretty much left me with Lenovo.

I ended up going with a “Lenovo ThinkCentre M70q Tiny i5-10500T 2.30 GHz” and paid a little extra to have the eBay seller customize it with 32 GB DDR4 RAM total, a 512 GB M.2 NVMe SSD, and throw in the antenna. Besides being fairly accommodating and helpfully communicative, I went with this listing because it fell squarely in my price range / project budget, it already came with the power adapter, they were California, and it could ship very quickly. While I could have easily spent another week or three trying to find a better deal on better and newer equipment, this was always going to be a project running on low end / older equipment and I valued the immediacy of getting to work over the incremental value of a better system. Frankly, just not having to hunt for a compatible power adapter was a huge plus for me.

In the end I purchased the main system from the eBay seller, paid an extra $36 to make sure the system had 32GB of RAM, ordered a used 512GB SSD (they threw in the antenna) from them in a second purchase for $55, a SATA SSD enclosure to re-use an old 500GB SSD, and $7 to grab some HDMI dummy plugs off Amazon. I knew the system would come with 16GB of RAM, but the benefit of “buying up” to 32GB also meant that I knew the machine wouldn’t have two 8GB sticks instead of a single 16GB stick. I could later upgrade from 16GB to 32GB if I had a single 16GB stick to start – but having two 8GB sticks would mean I would later have to get two 16GB sticks.

Specs and Prices

Anyhow, for those of you playing along at home, here are all the parts for my $284.30 computer system.

Part	Cost	Shipping	Tax	Total
M70q Gen 1(i5-10500T, 16GB, Adapter Incl., No SSD), upgraded to 32GB	$185.99	$5.93	$14.41	$206.33
M.2 SATA SSD to 2.5” SATA adapter enclosure	$10.79		$0.84	$11.63
512 GB NVMe M.2 SSD, antenna	$55.00		$4.13	$59.13
Dummy HDMI Plug	$6.69		$0.52	$7.21
				$284.30

I didn’t have to buy the SSD enclosure – but it seemed like a very inexpensive way to double the storage and repurpose my old drive. I didn’t realize I’d need to get an HDMI dummy plug, or even what they were, until I tried to “remote” into the headless box and got a fairly ugly looking desktop instead of the slick Ubuntu desktop. This was probably the least necessary of these purchases. If I kept the system to the PC with the 32GB upgrade, ran the OS off my old SSD in the SATA enclosure, and picked up a $7 antenna off Amazon, the system would have only cost about $213. The extra $59.13 doubled the hard disk space and enabled a more graphically pleasing interface. It’s not much of a splurge and this was never a “build a PC for as little as possible” kind of a challenge anyhow.

The final system is probably on par with my existing 4 year old PC at roughly half the cost. I think it was a “decent” deal and I have a system that I can use to offload a lot of projects. If any of these projects end up requiring more processing power, I’m not even really “out” $285 since I can still keep using this system for other tasks (home automation, running daily scripts, etc).

And, yes, I’m trying to use this PC as a basis for a bundle of scripts I can deterministically interact with via voice input / output as well as certain LLM powered tasks. First, a helpful comic.

And, that kids, is how AI killed human interaction

We’re probably hurtling towards dead internet theory. I can’t search through Google or even DuckDuckGo anymore without having to wade through their AI summaries and then scroll past search results from AI slop. Using ad blockers or setting up a PiHole to block ads and stop tracking from ever touching my PC may impoverish some otherwise worthy websites. However, I simply don’t have to read every advertisement sent in the mail, on the inside of my grocery shopping cart, or every billboard. Yeah, I hate the idea of AI companies boiling oceans of drinking water for their inscrutable purposes…

There’s a quote I love by H.L. Mencken; “Every normal man must be tempted, at times, to spit on his hands, hoist the black flag, and begin slitting throats.” What if the best way to filter out AI garbage is to use an LLM to do some of that filtering for me? ³⁴

Searching through any search provider is kinda garbage these days, but there’s no reason I should have to wade through that AI garbage myself. Gone are the days you can drill down to the kind of search results you want by simply adding “-negative_search_terms”, because there’s probably no financial reason for them to permit this.

But what if I created my own search function? I recently tasked an AI with searching up 10 options for a certain product for me on Amazon and it did a mediocre job, finding 7 dead or unavailable listings. But it also saved me a lot of time looking through dozens of pages of crap when I only needed to look through 10 crap listings. With some tinkering, I think I could make a script that would identify negative search terms, perform the search as requested, then remove those that should have been removed with the negative search terms. I could see this being incredibly useful for Ebay and Amazon purchases.

A preview for next time: After some dithering, much watching of youtube videos, I’m going to give Hermes Agent a shot over OpenClaw.

Project Jarvis

LibreOffice, Thunderbird, OpenSCAD, etc [↩]
Is it really a budget if there’s a range?

Words to live by

[↩]
And, yes, I have considered the possibility that an AI company’s aim might be to make everyone distrust the entirety of the internet, then sequester everyone into their own little siloed version of digital reality, everyone watching slightly more targeted ads and Marvel movies than everyone else, and any attempt to use another LLM to filter shit out only results in more precise targeting… [↩]
I went to the hardware store yesterday and was told by someone who worked there in an orange apron that the entire store, inside and out, was covered in Flock cameras. I think this bullshit surveillance is really starting to get to me. [↩]

House Temperature Readings So Far

Just an update with the charts and measurements so far.

07/07/2026, readings from XIAO ESP32C3 and thermistors

07/08/2026, readings from XIAO ESP32C3 and thermistors

07/09/2026, readings from XIAO ESP32C3 and thermistors

07/10/2026, readings from XIAO ESP32C3 and thermistors

07/11/2026, readings from XIAO ESP32C3 and thermistors

07/12/2026, readings from XIAO ESP32C3 and thermistors

07/13/2026, readings from XIAO ESP32C3 and thermistors

07/14/2026, readings from XIAO ESP32C3 and thermistors… totally broken

07/14/2026, readings from Wemos D1 and AHT10 sensors

07/15/2026, readings from Wemos D1 and AHT10 sensors

07/16/2026, readings from Wemos D1 and AHT10 sensors

Summer Science - Testing Effects of Window Coverings on Interior Temperatures

Back on track

Okay, as of 11:30 AM, the AC was working again and battling against 104 degree heat. That means we can start looking at our data again – and plan out what to do about the window, sun shade, or other system for blocking some or all of the heat for this one picture window.

In an effort to help make this data more representative of what’s actually going on inside the house, I put a thin piece of aluminum around the sensor in the entry way. My thought was that it would help deflect some of the direct heat hitting the sensor and causing it to register ~100 degree heat on the ground.

Distributed temperature sensors for creating a “heat progression map” of temperatures in a house. Right now I only have three sensors, but these are inexpensive enough, that I could see creating several to send temperature back to my PC. There’s always a tradeoff between effort, speed, and cost.

One infrared thermometer. $15
One board, 3 sensors, lots of wire. ~$30 and lots of wire hassles
- $5 XIAO board, $2 worth of thermistors and resistors, $2 protoboard, $15 wire
- A small amount of soldering
Three boards with a sensor each. ~$25 and very portable / placeable
- 3x ($3 Wemos D1 Mini, $2 AHT10 sensor, $2 protoboard, $1 tap light, $1 for two AA batteries)
- SO MUCH SOLDERING

For the best looking and most useful data, I think the three-board but higher effort approach is best. It also scales very nicely. For about $50 you could distribute 6 sensors throughout your house and get a sense of how heat moves around you home.

Summer Science - Testing Effects of Window Coverings on Interior Temperatures

WWMWD?

Welp. I guess this is a good time to dust off this little gem from the book, “The Martian.”

I’ve been trying to get consistent readings inside the house for a little over a week now. The infrared thermometer was helpful, but was too manual and to variable in readings despite trying to control by checking at wider intervals and taking measurements in very specific sections of the floor, wall, and ceiling. The XAIO board and thermistors were a great first step, but required too many wires and it was also having trouble broadcasting data. ¹ The Wemos D1 Mini, while an underpowered board, took a lot of fiddling to get running and a fair bit of soldering, but has worked very well.

Until external factors cropped up.

Yesterday, at the absolute peak of outside heat, our AC unit stopped working. I’m pretty sure the sound of it turning off yesterday was the last time it was working. The temperature inside reached about 86 degrees upstairs based on the home thermostat and stayed at that level until about midnight when we started up the whole house fan.²

If I were comparing a given day’s temperature to a different day’s temperature, all the readings would be basically useless. However, I’m actually more interested in figuring out if a single sunscreen can soften or blunt the increases in internal house temperatures. The data from yesterday is going to be useless for looking at absolute changes in temperature, but it certainly shows what would happen if we don’t have a working AC unit on a very hot day.³

Yeah, having the AC go out is a hassle – but on the bright side, at least it happened during a time when I was running some science experiments.

But, with about a week left to go, I’m less certain I’m going to be able to present the findings and associated original project I was planning on.

Summer Science - Testing Effects of Window Coverings on Interior Temperatures

Though, now that I think about it, this might have been improved if I attached the antenna to it? [↩]
86 degrees inside sounds comparable to Italian AC [↩]
Though, it shouldn’t take a rocket scientist to realize it’ll get warmer here without AC. [↩]

Musings on measurements and a wacky cat

More thoughts / ideas:

At about 5:30 PM, right around the time the heat measured at the entryway started to rapidly increase, I noticed two things. First, our AC unit was louder and persistent – it hasn’t seemed to have turned off since in the 30 minutes since. Second, the cat went absolutely bananas – eyes super dilated, calling out, then splayed on the ground in an almost seizure like stretch, then a weird slow walk. I had remarked on this odd behavior to the fam yesterday.
In looking at the data / charts I have now, it’s clear there was a huge spike in the temperature measurement in the entryway as the sun approached and then covered that sensor. Annnnnnd… now I’m wondering about the advisability of leaving those batteries and that board in that temperature, even if it’s only for 30 minutes of peak temperature. Fortunately, I connected the sensors with a length of wire so I could conceivably keep the batteries out of direct sun / heat. I might need to extend this further.
I think it would be interesting to review the delta / change in temperature over time, rather than the actual temperatures over time. Right now I’m just looking at these colored squiggles and thinking “Oh, that looks neat, and this bit is spikey, and how about that uptick, huh?” But, by looking at the change over time, I could actually quantify these things.
I know I’d suggested the next time I make something like this, I’ll just use another XIAO board, since they’re only slightly more expensive than the Wemos D1 Mini’s, but given the kinds of problems I was having with the XIAO seizing up, maybe not? I could get another 5 D1’s for about $15 and I have plenty of extra sensors and wire now that I’ve taken down my XAIO setup, but I don’t have any extra tap light enclosures. :) I know I can make do with off-the-shelf battery holders – and goodness knows I’ve got plenty – but I do kinda want to have them all be about the same.
It’s now 6:03 PM and the AC unit just shut off. I know there are API ways to know when the AC unit is active, but that requires the cooperation of my smart thermostat company – and they haven’t replied to my requests. I could build something that would sense motion and tape it to the AC unit, but it would be easier to build another temperature sensor and place it near an HVAC vent and treat the sudden drop or rise in temperature as an indication the HVAC was on.

Summer Science - Testing Effects of Window Coverings on Interior Temperatures

WHY IS EVERYTHING BROKEN?!

The running joke / perennial axiom of hardware startups is “hardware is hard.” I’m not even dealing with any kind of wild hardware. I’m using off-the-shelf sensors and an off-the-shelf board, connecting these in a way I can prove works, and transmitting data back to my PC. For some reason the XIAO ESP32C3 board is just not transmitting data back to the PC. Sure, sometimes I have to restart it which is no big deal. We all need a break. But, now it’s just not resetting properly when I power cycle it.

Anyhow, it’s clearly going haywire:

The good news is that the sensor data coming in from the single microcontroller + three hardwired sensors seems very consistent to the data that’s coming in from the three microcontrollers + single sensors, both over the last day and when compared against readings over the last week.

The observed trends is basically:

Outside temperature dips overnight, with a low around 5-6 AM, peak heat at around 3-4 PM.
When there’s no cloud cover, the house temperature at the entryway bumps first, then the family room, then the ambient house temperature peaks about two hours after entryway bump.
The house and outside temperatures are about the same by 10 PM to 12 AM.

In an ideal world, I’d just restart all the readings right now using the new system, get the sunscreen, then compare these patterns. However, the science display is due in about 10 days, which means I don’t have a lot of time to keep restarting / pivoting.

I guess what I’m doing now is just looking at the baselines. From there, I’ll make a prediction about what would happen with a sunscreen. Some of this sunscreen stuff may depend on external factors – the availability of the sunscreen vendors to measure/make the sunscreen. I don’t know what their lead times are, but I imagine during this heatwave they might be extra busy. Otherwise, I might try to make some predictions about how else we can affect the house temperature and humidity, perhaps with timing the opening windows, opening/closing blinds, and use of the whole house fan.

On interesting aspect of the more distributed Wemos boards / sensors is that these three sensors are also at different heights. The entryway sensor is at floor level in the path of the sun, the family room sensor is at about 6 feet off the ground, and the ambient sensor is at about 13-15 feet in the air. I am expecting the ground level to spike first, then the other two. I’m not sure if I should expect the 6 foot sensor to react first, because it’s closer to the ground height or the 13 foot sensor because it’s closer to the ceiling where the hot air will be collecting. If I had to guess, I would guess the higher one.

Although today is a real scorcher, the one upside is that I can compare it pretty nicely against the data from a very warm day last week with almost no cloud cover.

Summer Science - Testing Effects of Window Coverings on Interior Temperatures

Repeatedly Redundant (Sensing Sensors)

This is the second time the XIAO board stopped working for an extended period of time. Rebooting the board, unplugging/plugging the power cable and adapter from the wall, and even pulling the board from the headers, didn’t work to get it back online. I finally pulled the board, plugged it into USB, then made a do-nothing change to the main.py file¹ and plugged it back into the headers, which worked perfectly. There were no obvious errors in the board – it just … needed a boring update to the code?

This slideshow requires JavaScript.

Anyhow, I’d discussed some of the pros and cons of running three Wemos D1 Mini powered sensors² versus just one XIAO ESP32C3 powered sensors – but didn’t think about what happens when a single one goes down. Although the XIAO was out of commission, the three Wemos board kept going so I didn’t really lose any temperature data – especially since the data was so flat during from 12:30 AM to 9 AM this morning.

Admittedly, the locations for the three sensors aren’t perfectly matched. I have the three XIAO thermistors taped to the entryway flooring, taped to the metal plate just inside the family room, and one dangling in the air above the entryway out of any direct sunlight. The three Wemos AHT10’s are on the entryway floor near the entrance to the family room, well inside the family room on the mantleplace, and the last at the top of the stairs with the sensor in open air at almost the exact same height and area as the original XIAO ambient sensor. I actually wanted the second XIAO sensor over on the mantleplace as well – but didn’t want a run wires across the house that far to do it. I’m at peace with getting different readings from these sensors versus my historical readings because:

The AHT10’s are supposed to be more accurate – and also measure humidity which I’ll use near my 3D printer later on
There’s no really good way to tape the AHT10’s to a surface and that doesn’t really tell me much about the “feeling” of warmth inside the house anyhow
The floor readings were constrained by the amount of wire I had rather than really wanting measurements at those specific locations

Just looking at the charts of the incoming data suggests that the AHT10 sensor data is definitely less noisy than the thermistor data. Then again, it might be due to the way in which I’m taking readings every minute but then broadcasting the data every 5 minutes. I’m sure no one would notice or care if I sampled the data every 5 minutes, but when the peak heating coming in from that one picture window only lasts about 30 minutes, I think I’d like to get a better sense of what’s going on minute-by-minute rather than at 5 minute intervals.

Summer Science - Testing Effects of Window Coverings on Interior Temperatures

Changing something behind the comment line from “#==================” to the same thing with one less equal sign [↩]
Way more than triple the soldering [↩]

Now with remote sensors

As with many of my projects, the scope and build has changed somewhat over time. This project started with me just taking readings around my house with an infrared thermometer at somewhat regular intervals. However, this was tedious and prone to variance as I measure things by hand. After that, I started using a single XIAO board with three hardwired thermistors around our entry way. The nice thing about this kind of a setup is that I really only have to build/program one board, set it up, and then let it send data to my PC. The downside is that there’s wires everywhere – and it used up my entire stash of glorious rainbow colored ribbon cable. ¹

Practice when I work on a project is to buy replacement parts for the pieces I use up after I’m done. This way, I will still have stuff on hand for my next project. So, I’ll need to pick up more colored colored ribbon cables, small solderable prototyping boards, and replacement microcontrollers. Back in the day, I would stock up on Adafruit Trinkets, but for about a lower price and a slightly larger footprint, I can get a XIAO board with more IO ports, memory, speed, and built-in wifi/bluetooth. The little prototyping boards I’d purchased aren’t available from the same seller on Amazon, which is too bad. I really like these boards because they’re bigger than just the microcontroller, have power rails that run down the center rather than the sides and horizontal rows, and rounded corners. They’ve been incredibly convenient.

With this project, I wired up three Wemos D1 Mini boards, each to a different AHT10 temperature/humidity sensors, and shoved them into my favorite enclosure – cheap tap lights.²

This slideshow requires JavaScript.

As I’ve mentioned previously, I’m just not very good at soldering – which is why I go very slowly, checking, rechecking my progress as I go. Even so, I made two small and fixable mistakes, soldering the wrong connection somewhere and later accidentally bridging two contacts. Fortunately, some things are fixable.

The construction of these little wifi sensors isn’t very interesting. Rather than run each board off of 4.5 volts from three AA batteries, I’m using 3.0 volts from two AA batteries. By not passing that 4.5 volts through the voltage regulator to bring the power down to 3.3 volts, I should be able to save enough battery life to justify running this system off 2/3 the batteries. This meant I soldered the power connectors to the end and middle battery connectors. I have a suspicion that the XIAO boards are probably more power efficient, but if I don’t use those Wemos boards for something simple like this, well, I’ll probably never get around to doing it.

In any case, I now have these three sensors throughout the house near the locations of the prior sensors. I like these AHT10 sensors – but unlike the thermistors, I can’t really get the sensor right up against a surface. Hopefully it won’t matter much. While the readings directly off the flooring and metal plate were dramatic and gave a sense of the heat that was being absorbed and released by the house, it’s the actual temperatures in the house that are what I’m after. In the meantime, I’m running both systems in parallel so I can make sure they’re both pulling in reasonably consistent readings. If so, I’ll pull down the tangle of wires, wind them up, and set them aside for the next project.

Summer Science - Testing Effects of Window Coverings on Interior Temperatures

I picked up 15 feet for $5 about 13 years ago from Sparkfun, now selling for $7. Digikey also carries it for quite a bit more, but I haven’t run the math to figure out whether shipping makes a difference. [↩]
With some hunting, you can find a set of tap lights for about $1, they include a battery holder, switch, bright white LED, attractive sturdy case, and semi-translucent top. [↩]

Readings so far… 07/11/2026

Here are the readings so far from 07/07/2026 to today 07/11/2026.

There will be a few momentary blips in the data because now and then I have to restart my PC for some stupid reasons. In an ideal world, I’d have a dedicated Raspberry Pi (or even a special computer) designed to specifically capture this data. But, time constraints mean that I’m doing the best I can with what I have. I ordered some AHT10 boards to connect to the Wemos W600 boards (since this board doesn’t have an analog input) I have lying around – only to discover that the Wemos W600 boards are basically abandoned/unsupported and just won’t detect anything coming out of those sensor boards. I then tried some Wemos D1 Mini boards… and no dice there either.

I think the lesson might be… Just get more of the boards that I know will work. These days, that means the Adafruit QtPy boards and the SeeedStudio XIAO ESP32 line. They’re small and at $5-$8, I’ll save WAY more time than if I was trying to get a $2 board working. I guess it could be that the sensor boards are junk – but I won’t really know until I dig into these deeper and that’s not going to happen until the weekend.

I was inspired to start testing this stuff by a local science fair put on by our local utility company. But, let’s not kid ourselves, I’m only too happy to dive into a project like this. Rather than having a bunch of wires from one single ESP32 board going to three different locations in the house, I’d like to ideally have three remote sensors that are battery operated and I could place throughout the house. In a move that may well bite me in the backside, I’m trying to use a Wemos D1 Mini for these remote sensors. I already have them lying around, can run Micropython, and can connect to the I2C / AHT10 sensors I purchased. Rather than scrapping the existing system, I’m going to see if I can build up the new system in parallel, get it running, then disconnect the old system.

While I’ve shopped around for some window screens, I haven’t actually purchased one yet. However, I still have about 2 weeks to go before the science fair, so hopefully I still have time to get this done. :)

Summer Science - Testing Effects of Window Coverings on Interior Temperatures

Testing Interior Temperatures – preliminary results

I’m not going to bury the lede. There are several spikes or “upticks” in the household temperature. There’s one at about 7:30 AM (A) I’ll discuss below, one at about 5 PM (C) which coincides with the afternoon sun reaching the entryway, and another starting around 5:45 PM (D) when the afternoon sun starts to creep into the family room. Around 9:30 AM I closed the the windows that were open overnight and turned off the whole house fan.

While the above graph is based on about 1,200 samples from about midnight on 07/07/2026 to about 9:30 PM the same day, it’s just a sample of part of one single day. Even so, I find some interesting take-aways:

I turned off the whole house fan and closed the windows at the right time. In another few minutes, the interior temperatures would have reached equilibrium with the outside temperatures – and then quickly overtaken.
The readings on the laminate and metal plate spiked when expected, the laminate before the plate. The more exaggerated uptick is probably because the metal plate absorbed heat faster and then held onto it longer than laminate.
What I didn’t fully appreciate before I started the experiment was that the interior ambient temperatures were clearly lagging behind the floor sensor temperatures.
There’s an a sharp rise on the laminate temperature in the morning as well as a rise in these temperatures from about 7 AM to 9 AM. I believe this probably coincides with the morning sun coming in from the east facing windows.
Another thing I didn’t think about until after seeing these results is – what else could explain a temperature rise in the afternoon? Obviously, the house is going to heat up overall throughout the day – but are there any other factors? Our front door is painted black and the hardware becomes uncomfortably warm/hot with later afternoon light. While I would expect certain household objections to painting the entire front door white or covering it in aluminum foil in the name of science… I could run a small and less objectionable test by putting something insulating over the exterior door hardware to prevent it from heating up, and thereby not heating up the internal hardware.
You might wonder why the blue line, indicating the exterior temperatures, is so jagged compared the more detailed and noisy interior temperatures. The exterior data comes from a public source and is only updated once very 5 minutes, thus, it’s going to look more choppy than the data I can sample over WIFI multiple times a minute if I want. With updates only every 5 minutes, variations can look more pronounced as well. There’s a strange dip in the exterior temperature at around 7 AM, 12 PM, and 4 PM. The 7 AM dip coincides with a sharp increase in the cloud cover and the 4 PM dip appears to line up with a modest increase in cloud cover. I don’t see any immediate patterns which jump out at me regarding the 12 PM dip in exterior temperature. It would be interesting to look at the temperature data on a time graph as well as the humidity, cloud cover, wind, direct/diffuse radiation from the sun, and possibly even the air particulate counts. But, that would really only help me better understand exterior temperature trends in my particular climate. I’m more interested in how do the exterior temperatures and sunlight affect my interior temperatures – and what could I do to favorably effect these results.
One thing I’m wondering is whether it’s “fair” to measure the temperature in the family room using a black metal plate that will absorb and retain heat. I can’t reliably measure the carpet temperatures using this setup, so I have to use something. I’m concerned cardboard would be too good an insulator, I don’t have a spare plank of clean wood or tile, so I’m just kinda making do with what I have. Fortunately, I don’t really care about the temperature of that section of the room or even this piece of metal – I care about what’s heating it up and how I can blunt those effects. If I put in a sun screen and all of a sudden that sharp spike gets dulled – wonderful!

Summer Science - Testing Effects of Window Coverings on Interior Temperatures