DEV Community: Janvi Bhardwaj

The Thermal Shock Series #2: Designing a Thermal Shock Scoring Algorithm

Janvi Bhardwaj — Mon, 07 Sep 2026 17:34:17 +0000

Designing a Thermal Shock Scoring Algorithm

A concept exploration exploring the math behind quantifying cumulative temperature stress on the human body.

In my last post, I wrote about the invisible health risk of walking in and out of AC buildings all day. The research is clear. Repeated thermal transitions cause real physiological stress, and nobody is tracking it.

So I started thinking about what it would take to actually measure this. Not with hardware, and not with expensive sensors. Just with logic, published research, and the kind of data a phone already has.

Here is the algorithm I came up with, on paper and not in code yet, for turning "I walked outside" into a meaningful health risk number.

What are we actually measuring?

I needed to define what thermal shock means mathematically. It is not just temperature. A 5 degree change when you step into a corridor is very different from a 20 degree change when you step into the Chennai sun. Doing it once is also very different from doing it six times.

So the score needs to capture three things:

How big was each temperature jump?
How quickly are the jumps happening?
Which direction did it go, cold to hot or hot to cold?

Step 1: Detect transitions

The phone knows where you are. GPS tells you outdoor versus indoor location. WiFi network names tell you which building you are in. You do not need a temperature sensor in every room. You just need zone classification.

I divided the campus into three zone types:

Cold zone (~18°C): AC labs, AC classrooms, library.
Transition zone (~28°C): Corridors, covered walkways, lobbies.
Hot zone (real time): Outdoors, pulled from a weather API.

A typical day might look like this:

9:50 AM:AC Lab (18°C) to Outdoor (37°C) — +19°C
10:00 AM:Outdoor (37°C) to AC Lab (19°C) — -18°C
11:30 AM:AC Lab (19°C) to Corridor (30°C) — 11°C
11:35 AM:Corridor (30°C) to Outdoor (38°C) — +8°C
12:00 PM:Outdoor (38°C) to AC Lab (18°C) — -20°C
1:00 PM:AC Lab (18°C) to Outdoor (36°C) — +18°C

Step 2: Direction weighting

Not all transitions are equal. When you go from cold to hot, your blood vessels dilate rapidly. That is vasodilation, and it is abrupt and physiologically expensive. Hot to cold is still stressful, but the body handles it slightly better because vasoconstriction is a faster and more controlled response.

So I added a direction weight:

Hot to cold: multiply by 1.0
Cold to hot: multiply by 1.3

The 1.3 factor reflects the asymmetry in thermoregulatory response documented in the research I cited in my first post.

Step 3: Recovery time

If you walk out of AC, stand outside for two hours, and then walk back in, your body has had time to adjust. But if you cross a parking lot for 10 minutes and immediately enter another AC building, your body never recovered from the first shock.

So I added a recovery factor:

Less than 30 minutes since last transition:multiply by 1.5
30 minutes to 2 hours:multiply by 1.0
More than 2 hours:multiply by 0.8

The formula

Shock = |Temperature Delta| × Direction Weight × Recovery Factor

Example:Transition at 12:00 PM (outdoor 38°C to AC lab 18°C, only 25 minutes after previous transition):
Shock = 20 × 1.0 × 1.5 = 30.0

Example:Transition at 1:00 PM (AC lab to outdoor, one hour after previous transition):
Shock = 18 × 1.3 × 1.0 = 23.4 *(This is a cold to hot transition, so the direction weight kicks in.)

Where AI would come in?

Everything above is just a calculator. Artificial intelligence would come in when the system starts learning from real data. Over weeks, the model could notice:

Personal baseline:You tolerate heat better than average, so the thresholds adjust.
Symptom correlation:You experience headaches on days when the score exceeds 120.
Schedule patterns:Tuesdays are lab heavy and consistently produce the highest scores.
Weather adjustment:A score of 100 when it is 42°C is much worse than when it is 34°C.

This is where it would become a genuine machine learning problem rather than a rule based system pretending to be artificial intelligence.

Why not use phone temperature sensors?

Your phone has a thermometer, so why not just read it?

Because phone ambient temperature sensors measure the internal temperature of the device. They are heavily influenced by battery heat, CPU load, and whether the phone is sitting in your pocket. They are not measuring the room at all.

Instead, this approach uses zone classification. If GPS and WiFi say you are in the AC lab, we know it is approximately 18°C. If you are outdoors, the system pulls the temperature from a weather API. Is it perfectly accurate? No. Is it good enough to detect a 19°C jump versus a 5°C change? Absolutely.

The honest limitations

-The direction weight of 1.3 is based on physiological principles but has not been validated with this specific formula.
-The risk bands are proposed rather than clinically established.
-Self reported symptom data comes with compliance and bias issues.
-Indoor temperature estimation by zone type is approximate.
-I have not coded this yet; it is currently a conceptual design.

I am a first year computer science and engineering student, not a medical researcher. But the underlying research is real, the math is defensible, and the gap in existing solutions is genuine. Sometimes the value is not in having the perfect algorithm, but in being the first person to think through an algorithm at all for a problem that nobody else is measuring.

The Thermal Shock Series #1: The Invisible Health Risk in Every AC Building

Janvi Bhardwaj — Sun, 06 Sep 2026 13:21:53 +0000

I walk out of my AC lab six times a day. The lab sits at 18°C. Chennai outside is 37°C. That's a 19-degree jump and my body absorbs it in the ten seconds it takes to reach the parking lot.

By evening, I'm tired. Sometimes I have a headache. Sometimes my throat feels scratchy. I used to blame it on sleep, or the hostel food, or just "college stress." Turns out the actual cause might be something nobody around me was tracking and something I never even thought of as a health risk.

What's actually happening to your body
When you step from an 18°C room into 37°C heat, your blood vessels rapidly dilate. Your blood pressure drops. Your respiratory system goes from cold, dry air to hot, humid air in seconds. Your body's thermoregulation system - the internal machinery that keeps you at 37°C suddenly has to work overtime.

Do this once, and you barely notice. Do it six times a day, five days a week, for months and it compounds into something researchers call thermal transition stress.

I'm not making this up. This isn't a wellness blog theory. This is published, peer-reviewed research.

The research that changed how I think about AC
A study from AIIMS Hyderabad tracked 400 adults and found that people who frequently switch between air-conditioned indoor environments and outdoor heat experience what they called "thermal regulation stress due to disturbance in thermal adaptation and reduced tolerance to hot environments."

Read that last part again - reduced tolerance to hot environments. The AC isn't just cooling you. It's training your body to handle heat worse.

A separate study published in ScienceDirect found that even healthy individuals accustomed to air conditioning showed "substantial thermal burdening when abruptly exposed to urban exterior environments." These weren't sick people. These were healthy office workers and the transition alone was enough to measurably stress their bodies.

And here's the one that really hit me - a study on office workers in Malaysia found that AC users consistently reported higher rates of Sick Building Syndrome symptoms:

47.6% reported headaches

44.4% reported cough

38.7% had nasal irritation

25% experienced fatigue

25% had dizziness

Almost half. Getting headaches. From the building they work in.

The threshold nobody told us about
There's a recommended safe limit for the temperature difference between indoor and outdoor environments - 10°C.

At my campus, the gap is 20°C. Double the safe threshold.

And I experience this gap six times a day. Monday through Friday. For the entire semester.

When I first calculated this, I sat with it for a minute. I'd been living inside a health risk I could literally feel, the fatigue, the throat issues, the weekly colds but I never connected it to the one thing I do dozens of times a week: walking in and out of AC.

The scale of this problem
This isn't just a VIT Chennai problem.

India has over 40 million office workers in air-conditioned environments

There are more than 30,000 colleges with AC classrooms in tropical climates

The WHO reports that Sick Building Syndrome affects over 20% of building occupants globally

Chennai specifically has a 15–22°C indoor-outdoor gap for eight months of the year

And yet, I searched for a tool that tracks this. An app. A wearable feature. A campus system. Anything.

Nothing exists.

There are temperature apps. There are weather apps. There are indoor air quality monitors. But not a single product tracks what actually matters is how many times you transition between thermal zones in a day, how big each jump is, and what that cumulative exposure does to your health.

Why I started paying attention
I'm a first-year CSE student. I'm not a doctor or a climate scientist. But I can read research papers, and I can count.

Six transitions a day. 19-degree average gap. Five days a week. That's roughly 570 degrees of cumulative thermal shock per week that my body is absorbing and I was blaming the headaches on not drinking enough water.

This is the kind of problem that hides in plain sight. Everyone experiences it. Nobody measures it. And because nobody measures it, nobody fixes it, not the student, not the university, not the AC system.

I started thinking about what it would take to actually track this. Not with expensive sensors or medical devices, just with the phone in my pocket, a weather API, and some basic math.

That became an idea worth exploring. More on the technical side in the next post.

The uncomfortable question
Next time you walk out of your AC office or classroom into the heat and you feel that wave hit you, ask yourself:

How many times did I do this today?

And then ask:

Is anyone counting?

Because the research says it matters. And right now, the answer is nobody.

I'm a first-year B.Tech CSE student at VIT Chennai, writing about AI, health-tech, and problems that hide in everyday life. This post is part of a series exploring the intersection of environmental health and technology.

References
Impact of Air Conditioners on Sick Building Syndrome — AIIMS Hyderabad, 2023

Effect of Abrupt Exposure to Outdoor Heat on AC-Accustomed Individuals — ScienceDirect

Sick Building Syndrome in Malaysian Office Workers — PMC, 2025

AC and Heat Shock Response — Temperature Threshold Guidelines

Indoor Air Quality and Health Risks of AC Usage — Oxford Academic, 2024