2020 NASA International Space App Challenge
Challenge
“To develop an operational sleep shift scheduling tool that provides autonomous customization of a schedule for sleep, exercise, and nutrition to manage fatigue”
My Role
Product Management, Data Science, UI/UX Prototyping
My teammates
Aerospace Medicine - Research, Project Management
Software Engineering - App Development
Key Research Questions
What are the variables that influence astronauts’ sleep?
What kind of solution can we develop within the time constraint?
Should we and/or which ones do we prioritize: sleep, exercise or nutrition?
Key Constraints
Time: 48 hours
Use of NASA datasets
Research:
Background search of primary research (e.g., academic papers, relevant videos/interviews/descriptions)
Review of relevant datasets
Define (Target Solution):
Focus on melatonin, as a variable that influences the circadian rhythm, to improve overall sleep quality.
Solution for Astronauts for use in Space.
Project & Product Management
Ideate
Our solution considers three factors regarding sleep shifting:
1) Docking Time: Morning, Afternoon, Evening
2) Task vs. No Task
3) Landing Time: Morning, Afternoon, Evening
Constraints regarding scheduling:
nap time has to occur either in morning or afternoon
exercise occurs either in the morning or afternoon
sleep time is fixed
meal time is fixed
Critical Decisions:
Tool: App (Android)
Data:
Nutrition Data (NASA)
Dataset of Food & Beverages consisting of Melatonin
Spacewalk Duration (NASA)
Low-Fidelity UI Wireframe in Figma
Prototype: Android App
See link below for demo
Test and Limitations
Due to the time constraint, we did only an internal testing for main functions for demo purposes.
Limitations include not being able to test outside the team, no real-world user research (supplemented by research, watching secondary sources such as videos and interviews), not all functions were developed (machine learning for prioritizing food with Melatonin), dataset relevant to melatonin levels was not specific for astronauts.
Presentation and Results
Our team came in third for Taipei.
For full demo, code, and description:
https://2020.spaceappschallenge.org/challenges/sustain/sleep-shift-scheduling-tool/teams/solar-women/project