High-Level Project Summary
Our project Const. aims at overcoming numerous challenges faced by space biologists while operating with an organism in the space. therefore we developed a website through which a user can analyze the data of organisms and compare their features when living on both earth and space flight conditions. From this we solve the problem of knowing the most favorable or viable organisms that can live up to most of the space condition reactions to it. The soul motive of this project is to educate the users from the research papers which are really hard to comprehend , so we come as a medium for them in understanding that in a fun and easy way . From us , children will be excited to explore space .
Link to Final Project
Link to Project "Demo"
Detailed Project Description
Our project is focused upon providing the education of research papers and space exploration of biologist to people who are unable to comprehend and analyse the data for comparing the living organisms that are used in space explorations by biologists . So we took the dataset from the NASA genelab repo and made a ML model that narrows down the best values in that dataset . We used RandomForestClassifier as the data was unstructured . And thus combining those best features and creating an organism that can survive in both space and earth environment . It benefits the children and people as it educates them and make them excited enough to know things more in this field as this field is widely neglected by us . We hope to achieve all the children aspirations and taking out more and more info for them .
We used HTML5, CSS , JavaScript , ML , Sklearn , RandomForestClassifier as an algo , Flask , Github , Jupyter notebook , pandas
Space Agency Data
NASA GENELABRepo , NASA 5 main hazards used in our project as a data source and as datasets for our ML model .
We used the genelab datasets to narrow down the best features of the organisms and made the best species out of it with 0.9 accuracy . It was inspired as this is the the most trusted data source for us.
Hackathon Journey
It was really good to participate in a international nasa space app challenge for the first time and getting to know more about people and community . I learnt many things from people like how to work in a tight schedule and more. We started to build this project as an absolute beginner to space and biotechnology field . We CONST . as a team learnt temwork through this hackathon and management .
References
NASA genelab Repo
NASA open source docs
Tags
#web #ml #prediction #ai #nasaday #space #biology #artemis