Introducing cozie

A Fitbit platform for human comfort data collection

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Cozie Clock Face
iPhone image

Tailor your experiment via the Fitbit mobile app

and design your flow

Survey flow
Query your data programmatically
import requests
import pandas as pd
import json

YOUR_TIMEZONE = 'Asia/Singapore'

payload = {'experiment-id': 'experiment', 'weeks': '30', 'user-id': 'user01'}

# the api-key below is limited to 200 queries per day. Please contact us to get an API key
headers = {"Accept": "application/json", 'x-api-key': '7v90iALbXt1yRHdVomfpH80wmz14wTt92I0CR0na'}

response = requests.get( '', params=payload, headers=headers)
my_json = response.content.decode('utf8').replace("'", '"')
data = json.loads(my_json)
df = pd.read_json(data[1]['data']).T
df.index = df.index.tz_localize('UTC').tz_convert(YOUR_TIMEZONE)


Free to use

public database

full functionality

Example Projects

  • Indoor Comfort Study in Singapore In this study fifteen users were given a smartwatch for one month and were prompted to give feedback on their thermal preferences. The data revealed a range of results from building anomalies, occupant behaviour, occupant personality clustering, and general feedback related to the building.
  • Development of personalized thermal comfort models We are currently conducting a field thermal comfort study which involves 20 participants. The aim of this project is to develop personalized thermal comfort models using wearables and IoT sensors. Participants were asked to complete an average of 6 surveys per day for a period of 6 months. The study is planned to end in Oct 2020. The results will be used to to inform the design of future sustainable buildings in the tropics.

Designed with love by:

Prageeth Jayathissa
Lead Developer
Federico Tartarini
Developer, UI design, Back End
Kairat Talantbekov
Front End
Matias Quintana
Back End
Tapeesh Sood
UI Design
Clayton Miller
Project Coordinator