SPACEWISE
Fueling Curiosity, Guiding Exploration, Beyond the Horizon.
Created on 10th March 2024
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SPACEWISE
Fueling Curiosity, Guiding Exploration, Beyond the Horizon.
The problem SPACEWISE solves
SPACEWISE stands as the pinnacle of SpaceTech innovation, poised to revolutionize spacecraft trajectory optimization and fuel efficiency. Harnessing advanced mathematical modeling, optimization techniques, and an intuitive interface, it promises unparalleled precision in minimizing fuel consumption, predicting flight times, and selecting optimal orbital parameters. Its groundbreaking features include multi-stage optimization, real-time guidance, and multi-objective optimization, empowering users to navigate space travel with unparalleled efficiency.
The primary objectives of SPACEWISE are crystal clear: to optimize fuel consumption, trajectory, and orbit selection, provide visually immersive launch trajectory visualization, predict flight times accurately, select optimal orbital parameters, resolve space-related queries, and facilitate comparative analysis of diverse space mission options. These objectives are underpinned by cutting-edge technology, including sophisticated mathematical models, robust optimization algorithms, efficient computational requirements, and a user-friendly interface.
Moreover, it offers advanced capabilities such as real-time guidance, uncertainty analysis, and a commitment to open-source principles, fostering further innovation and collaboration within the space exploration community. It caters to a diverse spectrum of users, ranging from mission planners and propulsion engineers to stu
Challenges we ran into
While building Spacewise, there were certain challenges that we ran into including:
To display real time coordinates for satellites, the most common API that is used worldwide i.e, N2YO API did not provide information for our location i.e, in India. Thus this lead us to use demo data on which we implemented mathematical equation to continuosly keep track of latitudes and longitudes and display data with most accuracy as possible.
In addition, we faced unexpected setbacks when our Jupyter Notebook crashed during crucial stages of development. This unforeseen challenge disrupted our workflow and necessitated alternative approaches for deploying the ML model. We had to explore different methods, including using Taipy through VS Code and Google Colab Notebook, to successfully deploy the ML model and continue our progress towards completion.
Data Availability: One of the primary challenges we faced was the limited availability of exact data on satellites, launch sites, orbits, and other space-related parameters. Obtaining accurate and up-to-date information was crucial for the successful implementation. But we reproduced our own data and tried best to work with demo data and all the resources we could find.
Chatbot Optimization: We encountered issues with extracting relevant and accurate information from unstructured text data, as well as challenges in processing natural language queries and providing meaningful responses in real-time. Implementing it with wikipedia was a challenge. However we found an alternative and trained our chatbot model "SPACEWISER".
Furthermore, applying Flask and Docker for deployment posed additional hurdles. The intricacies of setting up and configuring these tools proved to be cumbersome, requiring meticulous attention to detail and troubleshooting to overcome technical issues and ensure smooth deployment of our ML model.
Tracks Applied (2)
Taipy
Major League Hacking
All-Girls Team
Technologies used