What inspired your team to choose this challenge?  

We were fascinated by intergalactic communication and how it all worked between Earth and Mars. Given social connection is an important part of life especially during these COVID-19 pandemic times, we were inspired to create an app to help the users on both the planets to not only communicate with the Space team (scientist/engineers) but also with family and friends to keep socially connected. While also increasing the efficiency in obtaining accurate data. 

What was your approach to developing this project?  

We analysed different approaches by which we communicate from Earth and Mars and vice versa. Given we were familiar with the Starlink project and Deep Space Optical Communication, we brainstormed how we can use the pre-existing space infrastructure while considering the possible future space infrastructures.  

Assuming that there will be multiple satellite and spacecrafts travelling in the future, the messages can be sent via piggybacking on the computers on board the space shuttles, space stations, and satellites. These satellites will have the capability to find the shortest path to send the data and conduct data backups simultaneously on multiple satellites. 

In space communication, there is often loss of data. We addressed this problem with a distributed data storage, which ensures that there is a signature for every packet of data. If any data corruption occurs during transmission/communication, the other satellites will check the data. So, if more than 51% of the satellites, or computing nodes, agree upon a particular signature, then the ones that don’t match will be replaced with the authentic copy. 

What tools, coding languages, hardware, software did you use to develop your project?  

• We created a prototype of a software module for the process of effectively and accurately communicate the data from Mars to Earth and vice versa. 
• We developed a python module to break down the image into small text files and create a unique signature using sha256 encryption algorithm. 
• Following open source python modules were used: 
• OpenCV – Image processing module. 
• Numpy – Mathematics and linear algebra. 
• Matplotlib – for viewing the images. 
• Hashlib – for encrypting the data. 
• We used GitHub for version control and collaboration while developing and testing the software. 

What problems and achievements did your team have? 

Problems: 

• Technical troubleshooting using Miro (collaboration board), the video conferencing didn’t work for one team member. They could see all of us but they were stuck on mute. Also, Miro was limited to screen sharing only one board at a time. 
• Team then suggested to move to Discord: a collaboration tool where we could all chat, share files, share screens and collaborate in real time. Only issue was video chat connections during peak times of the day (sometimes the audio/video was patchy). 
• The solution was to use the technology during off peak times with video chats, and only use audio during the day. 
• Too many communication chats channels: Space Apps (delayed notifications), Facebook messenger (not everyone has an account), so the team moved to Discord as a central place of communication. 
• Info/links to the challenge and project brief was hard to find on site – used Trello to store resource/reference links and track project progression. 

Achievements: 

• Day 1: researching, creating content for the pitch deck, creating the MVP app and testing the code, design discussions and set up communication/collaboration boards/technology. Main achievement was deciding our project submission solution – MVP app, with pitch deck and video and creating and testing the content. 
• Day 2: wrapped up the project with finalising pitch deck, coding testing, video editing. 
• Collaborating effectively as team across 3 different time zones: Sydney, Malaysia and India. We had a team of diverse skillsets including technical, design and business/marketing.  

We considered different weather conditions (cold temperatures, dust storms and etc. on Mars) that are useful for the transmission of the message from the NASA weather API. 

We also considered using the resources data of satellites (NASA API) in our web application in order to find the shortest path for the message signal to travel. This greatly improves the efficiency of communication not only from Mars, but also other planets as well. 

With location of each satellites known, the signal is transmitted in smaller chunks to send files of larger size. In addition, the transmitted signal can then be verified based on their encrypted signature for each chunk of the message. These API are proposed for finding the shortest path among the satellites to reach the message from Mars to Earth and vice versa. 

Moon Kids Presentation: Space Comms App

Please note there's a video demo embedded on slide 4, if the video doesn't work please refer to: https://www.youtube.com/watch?v=1iCtHQFEW6s

• API Link: https://sscweb.gsfc.nasa.gov/WebServices/REST/json/  
• https://airandspace.si.edu/stories/editorial/challenge-communication-space 
• https://mars.nasa.gov/msl/mission/communications/ 
• https://mars.nasa.gov/msl/mission/communications/#data 
• https://www.discovermagazine.com/the-sciences/nasas-interplanetary-internet-coming-soon-to-a-planet-near-you 
• https://www.forbes.com/sites/ellistalton/2018/09/06/communications-infrastructure-on-mars-could-be-the-envy-of-earth/#7821f9d33706 
• https://www.jpl.nasa.gov/edu/learn/video/mars-in-a-minute-what-happens-when-the-sun-blocks-our-signal/ 
• NASA weather API:  https://api.nasa.gov/