Exploring Around: Humidity

Having troubles with my skin condition I’m trying to explore the causes and find solutions to solve this personal problem.


Spending most of the time indoors, especially during winter season, I found my health factors get worse towards the end of the day:

  • Skin drying
  • Discomfort in nasal area
  • Heavy head

All of this is causing productivity decreases, as well as time wasted on hygiene procedures that bore me.


Each human body is a biological system. Each external change has an impact on this system. In response to each impact, the biological system starts its adjustment mechanisms.

Abstracting from thousands of impacts causes adjustment mechanisms to activate; one of the reasons is thermal environment conditions.

I decided to explore what the science says. The most simple and thoughtful was an article about thermal comfort found on Wiki. Briefly, satisfaction with the thermal environment is important because it influences productivity and health. Thermal environment factors are air temperature, mean radiant temperature, air speed and humidity.

Therefore, the main factor is air temperature and according to standart (of course, each country has its own regulatory documents):

A general recommendation is that the temperature be held constant in the range of 21–23°C (69–73°F). In summertime when outdoor temperatures are higher it is advisable to keep air-conditioned offices slightly warmer to minimize the temperature discrepancy between indoors and outdoors.

As for relative humidity, there is a more complex story. In short, “it depends”. It depends on the season and on the temperature outside. In general, the recommended level of indoor humidity is in the range of 40–60% in air conditioned buildings.

Low humidity caused by heaters and cold temperatures during winter time can lead to dry skin, irritated sinuses, irritated throat, and itchy eyes. High humidity environments prevent the evaporation of sweat from the skin. When the evaporation of sweat is the main method of heat loss in humans, then high humidity + high temperature could cause heat stroke.

So the task here is to remain within those thermal conditions that cause minimum body adaptation, which speaking graphically get us to the center of the graph. Do those conditions get to the center or not? I’ve decided to measure.

Bonus part

I love to fly. I might even say I’m a fan of “Up in the Air” movie, where George Clooney flies across the States almost daily. Each flight for me is like a red-letter day. But from another aspect, each flight is stressful because of the negative impacts on my fussy skin. I thought it was connected to low pressure that my body suffers from. However, after exploring the current issue, I figured out it’s mostly connected to air quality.

The impact of flight time on humidity
“One of the professional diseases among aircrew”, — Ira, the former flight attendant, says.

Low relative humidity occurs on most flights. Potential health impacts: temporary drying of skin, eyes, and mucous membranes can occur at relative low humidity (10 to 20%). This is exactly what I experience every time.


I’ve asked a colleague to help me build the device to measure humidity and temperature during the day.

30 minutes and it’s done. Humid 1.0 is here. It consists of a Raspberry Pi board, temperature/humidity sensor, SD card, which is all connected to a power bank (I was so naive to expect 1/4 of charge would be enough, hah).

Actually a wi-fi module exists on a photo but we had no time to implement the data transfer to an iPhone. “Just let it store the data on a card and then we’ll grab it”. So then we eliminated the antenna and thanks God it became a little bit smaller.

Production version should fit iPod nano ☺

I spent one day taking Humid 1.0 everywhere with me. I saw the red flashes around the room when I was falling asleep, I held it in my pocket while walking, answered dozens of questions while it was on my work table and even caught the waitress’ eye during lunch.

The next day, we grabbed the data from the card and got .txt file with thousands of rows, some of them were with no data filled. I’ve asked my friend to filter it and leave only 1 measurement per minute, which is enough due to non-instant sensor reaction to changes.

Data proccesing. Python rocks

Then I rolled up my sleeves and plotted graphs in Google Docs. Additionally, I logged my environment changes throughout the day to compare it with gathered data.

Long day… Temperature (Celsius) in red, Humidity in blue.

It showed that the indoor temperature in our coworking space increases from morning when there are only a few people, till the afternoon, when it’s almost full. Then lunch-time-Brownian-motion makes the space ventilated with fresh wet and cool air. After that, the humidity slightly decreases and the temperature increases until the end of the day.

By the way, as seen on the chart, I have very comfortable sleeping conditions (~16°C/44%). And our coworking secret sleeping room is almost perfect too.

Then, I plotted the chart of humidity/temperature to see how it fits to the target-data researched early.

Seems I didn’t hit a bulls-eye…

Grouping together points that change slightly we could get time-based average values of temperature and humidity. This allows to define which values are noteworthy and which are just short-term and show location changing.


Knowing time intervals and values related to that intervals and matching it with locations we attended that day allows to get location-based thermal comfort information.

Gathering day-to-day information forms personal database of locations and environments person has been. Comparing to personal feeling (point to think about on data objectivity) allows to analyse and understand are locations comfort or not.

Adding synchronisation with calendar leads system to learn and suggest when stressful environments are near at hand.

From data to meaningful insights.

Moreover, it could greatly work as here-and-now solution using smartwatches. Considering watch’s screen is always visible to the owner watches are perfect reminder tool. Less info, no analytics, no bother when all is ok, but action suggestions when it’s not.

Smartwatch interaction

So, such suggestion system would greatly help me understand the environment and prevent negative effects. Continuous measurement could be possible having some tiny device which will transfer data to mobile phone. It should be always on top and not covered with layers of clothing. Vision is shown below.

“Idea sketch should fit a napkin. But its a right way” © Anton

What’s next

I’ll continue measurements of the environment around. And knowing that temperature and humidity are not the only problem, I would like to learn more about the impact of air composition.

Air pollution is a significant risk factor for a number of health conditions including respiratory infections, heart disease, stroke and lung cancer. Therefore adding more sensors for detecting particulates (i.e. ozone, nitrogen dioxide, and sulfur dioxide) is another challenge despite existing one to build more tiny and mobile device.

I’m experienced designing interfaces for hardware devices as well as for web/mobile applications. Portfolio on Behance