Sleep Shift Scheduling Tool
Sleep Shift Scheduling Tool
Summary
Our idea is to build an all-in-one app for the astronauts that would help them keep a track about their activities. So while researching about Nasa Astronauts and their experiences with sleep we came to know that they were going through some tough times. We then came to know about Actiwatch and found out that this brilliant device built by Harvard University is being used by to collect various kinds of data about the Astronauts. Then we built a mobile based application that the astronauts can use to find out that how behind/ahead are they on Sleep and Calories. This will help the astronauts keep an account about it.
How We Addressed This Challenge
Our project solves the problem statement efficiently and effectively . We take in data from the actiwatch and then process all that data to use it as parameters to calculate the values to return, once that is is done our app suggests the astronaut or user what to do, and does this on a regular basis
How We Developed This Project
It is not new to us that astronauts have extended sleep latency and poor sleep efficiency, which was defined as “space insomnia”. Is this healthy? Is this a potential problem that can cause harm to important missions a render them as high risk? YES!
this problem can be avoided by a little bit of thinking and influencing the mind psychologically .
As a team we figured out various ways in which the problem of sleep in space can be sorted out.
With data from smart watches and the long list of data fields available ,like calories , activity, intake, etc we could estimate how much sleep is required to remain healthy,and also to maintain the rhythm. The various data fields have individual importance in influencing the sleeping habits and ability to sleep .
Python & Dart have been used in order to develop our software and make it into a working concept.
Our idea is crystal clear but when it comes to implementation, we had a number of shortcoming which we eventually hope to overcome in the future. The process of implementation is a little difficult due to certain information shortage and resource unavailability.
How We Used Space Agency Data in This Project
We used the provided data set to initialise our variables and set parameters according to the data, we then used that data set as history for our ML code to train the code supervised learning, and then implementation was done using that trained code to play music, suggest steps etc
Project Code
Data & Resources
Nasa Data Set
Harvard University Actiwatch
Apple watch
Github
Wikipedia