Lunar Village People (LVP) has received the following awards and nominations. Way to go!
We are an international and interdisciplinary group of people, passionate about science and we believe that teamwork is the key to achieve any goal. Some of us knew each other from past Hackathons and for others this was their first, but all integrated and committed to the project in a very energetic way. We all put our grain of sand to make this idea the best we can and always were opened to new points of view, proposals and critics because we know that is the way ideas grow and become better. We are very happy to be participating because this experience also gave us the possibility of knowing new people and make friends. The time we have shared will live in us forever!
We are LVP!:
THE PROBLEMS: CHALLENGES OF HUMANITY
We believe thinking about humankind's future is crucial for our species to survive the challenges that come ahead and that through our project we contribute to a possible and plausible solution to a series of topics such as overpopulation, lack of resources, global warming and also for scientific research itself.
Getting accurate data about Moon's lava tube's interior to be able to make reliable maps which allows planification of human settlements inside the tubes.
We’ve designed an IR space sensor  with magnetometer (IRMAS) to map lava tubes in order to build human colonies inside them [3,6,10].
A lava tube is a type of natural cave formed when a low-viscosity lava flow develops a continuous and hard crust, which thickens and forms a roof above the still-flowing lava stream. These geophorms can be up to 14–15 metres (46–49 ft) wide and also extremely long. On the Moon, lava tubes may be as wide as 500 metres (1,600 ft) . Some lunar lava tubes(believed to have formed during basaltic lava flows) have been discovered and have been studied as possible human habitats, providing natural shielding from radiation
Applying Digital Image Processing and Machine Learning using NASA data (Lunar Reconnaissance Orbiter-LRO),  we remotely select the best landing place taking into account proximity to resources such as solid water , minerals, construction materials and of course the lava tubes .
Once our rover mission arrives to the Moon, our biomimetic microbots will create a network to get more accurate data about lava tube’s interior: we use segment measure devices, a series of microbot will hover surface of the moon and some will land in certain places working as well as beacons while other microbots will get inside the lava tubes to scan and redirect interiors data to the beacons and this late to satellite. In that way, a node net will be formed, which will scan surface and ground of the Moon accessing to information never achieved before. All this will be done in real-time processing. With that in-situ data we will be able to create reliable maps to plan the settlements.
Project Presentation: https://docs.google.com/presentation/d/1Lr-2wnbriB...
IR Sensor Animation: Link
Matlab Script: https://drive.google.com/drive/folders/1rWOFluDPG2...
Gist-Github Repository: https://gist.github.com/LunarVillagePeople
IRMAS: Infrared and Magnetic Sensor
The IR sensor  is based on graphene (two graphene plates with one vanadium plate in the middle that can be replaced by amorphous silicon), and due it's adjustable bands gives more detail of scanned surroundings. With magnetometry we analyze magnetic anomalies to reduce as much as possible the interference and possible error generated through remote scanning [5,8,9].
SMD: SEGMENT MISSION DEVICES
We will use a series of devices that will carry attached different sensors involved on our mission, such as IRMAS, Lidar, sonar, etc. Some of the devices will function as well as beacons receiving the signals captured by other devices that will go underground inside the lava tubes.
We believe the best technology to apply are milli/microbots  with electro contractible parts (or SnakeSkin robot ) that will allow them to travel the sometimes difficult terrain on the Moon and also rugged lava tubes interior. They will be equipped with Artificial Intelligence (AI) and will rove Moon's surface forming a node net getting signals from the underground devices and sending it to the satellite.
MISSION PHASES: Rover Mission 'IRMAS'
-Phase Nº1: Statistics and take off. We will use NASA data in Digital Image Processing and Machine Learning to [1,4] select the best place for landing focussing on proximity to resources. Thereby, we will send the IRMAS to the Moon directing it towards the chosen landing zone.
-Phase Nº2: Landing zone adjustment. Once near the Moon, a group of biomimetic microbots will be released to the Moon which will work as beacons to scan the surface forming a node net. With this new data and its analysis in real time, we will be able to correct any possible error made on Phase Nº1 as well as be able to take a glimpse of the zone in situ and make last minute decisions about possible changes regarding topography not detected before, bad conditions, etc.
-Phase Nº3: Mapping Moon´s lava tubes. On the Moon we will use more biomimetic microbots as segment mission devices (SMD). Each device will carry different sensors such as our IRMAS plus Lidar, among others and the ones which enter lava tubes will send collected data to the beacons and from here to the NASA satellite to compile and analyze it. In this way, using Machine Learning with this new data, we will be able to make detailed maps of the lava tubes interior and plan the settlement of sustainable human colonies inside them. The SMD will also scan the surroundings to collect accurate data about useful resources for the settlement.
SCALABILITY: PRESENT AND FUTURE
The technology application used on this mission can also be used on Earth to detect and analyze more deeply lava tubes which can be used for example as shelter for refugees.
As for the mission itself, we believe it has the potential to be carried out first on the Moon and afterwards on Mars, taking into account certain modifications inherent in the case.
We know the sky is not the limit, we committed ourselves to this idea and hope to see it grow bigger and stronger. We are ready to keep on innovating to reach the infinity and beyond!
SPECIAL THANKS TO:
- Nicolás Galiano (video edition)
- Maximiliano Monaro (audio edition)
- Ezequiel Salazar (male voice in video)
 NASA Mission LRO (Lunar Reconnaissance Orbiter): LROC Quickmap.
 PhD Thesis-UTN : H. Giannetta “Studies of materials and MEMS processes for the implementation of a tunable microsensor in the infrared band”, National Technological University, Buenos Aires, Argentina. September 2017.Link.
 Antonello Piombo, et al, "Thermal anomaly at the Earth's surface associated with a lava tube", Journal of Volcanology and Geothermal Research, Volume 325, 2016, Pages 148-155, https://doi.org/10.1016/j.jvolgeores.2016.06.019.
 NASA Mission Grail. Gravity measurement , GRAIL
 Chappaz, L., R. Sood, H. J. Melosh, K. C. Howell, D. M. Blair, C. Milbury, and M. T. Zuber (2017), Evidence of large empty lava tubes on the Moon using GRAIL gravity, Geophys. Res. Lett., 44, 105–112, doi: 10.1002/2016GL071588.
 Kaku, T., Haruyama, J., Miyake, W., Kumamoto, A., Ishiyama, K., Nishibori, T., … Howell, K. C. (2017). Detection of intact lava tubes at Marius Hills on the Moon by SELENE (Kaguya) lunar radar sounder. Geophysical Research Letters, 44, 10,155–10,161. https://doi.org/10.1002/2017GL074998.
 Shuai Li, Paul G. Lucey, Ralph E. Milliken, Paul O. Hayne, Elizabeth Fisher, Jean-Pierre Williams, Dana M. Hurley, Richard C. Elphic, "Direct evidence of surface exposed water ice in the lunar polar regions", Proceedings of the National Academy of Sciences Aug 2018, 201802345; DOI: 10.1073/pnas.1802345115
 Michael E. Purucker, A global model of the internal magnetic field of the Moon based on Lunar Prospector magnetometer observations, Icarus, Volume 197, Issue 1, 2008,Pages 19-23, ISSN 0019-1035, https://doi.org/10.1016/j.icarus.2008.03.016.
 Richmond, N. C., and L. L. Hood (2008), A preliminary global map of the vector lunar crustal magnetic field based on Lunar Prospector magnetometer data, J. Geophys. Res., 113, E02010, doi: 10.1029/2007JE002933.
 Leonardo Carrer, Christopher Gerekos, Lorenzo Bruzzone, A multi-frequency radar sounder for lava tubes detection on the Moon: Design, performance assessment and simulations, Planetary and Space Science, Volume 152, 2018, Pages 1-17,ISSN 0032-0633, https://doi.org/10.1016/j.pss.2018.01.011.
 Lu, H., Zhang, M., Yang, Y., Huang, Q., Fukuda, T., Wang, Z., & Shen, Y. (2018). A bioinspired multilegged soft millirobot that functions in both dry and wet conditions. Nature Communications, 9(1), 3944. https://doi.org/10.1038/s41467-018-06491-9
 Rafsanjani, A., Zhang, Y., Liu, B., Rubinstein, S. M., & Bertoldi, K. (2018). Kirigami skins make a simple soft actuator crawl. Science Robotics, 3(15), eaar7555. https://doi.org/10.1126/scirobotics.aar7555
 Haruyama, J., Hioki, K., Shirao, M., Morota, T., Hiesinger, H., van der Bogert, C. H., … Pieters, C. M. (2009). Possible lunar lava tube skylight observed by SELENE cameras. Geophysical Research Letters, 36(21), L21206. https://doi.org/10.1029/2009GL040635
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