LunarWSN: A Wireless Sensor Network for In-Situ Lunar Water Ice Detection

The future lunar sustainable habitation will be resource-intensive. Taking advantage of local resources on the lunar surface is the most effective way to reduce the cost and risk for future lunar missions. Water is one of the most important resources that can provide not only drinking water for crews, but also fuel for rockets and spacecrafts. To date, most of our knowledge of lunar water distribution is from remote sensing, which is vague (kilometer-scale resolution). More in situ measurements are indispensable to acquire meter-scale resolution knowledge of lunar water distribution. The current main force of in situ planetary explorations is a single high-cost rover that can provide merely a series of single-point measurements or a lander without mobility that can only measure surrounding areas. Neither rovers nor landers can work in dangerous areas where data of interest often exists. Wireless Sensor Networks (WSNs) are a technology that is typically dedicated to collecting in situ sensing data from regions of interest. A WSN is composed of multiple sensor nodes that are relatively small, light, and easy to deploy. The sensor nodes are designed based on a variety of missions and distinctly different environments. In this thesis, we present a WSN sensor node designed for measuring the water content in lunar soil simulant. The sensor node is designed to be ballistically deployed from a rover or lander to regions of interest that might be unsafe for rovers or landers. The sensor nodes can create an expandable WSN, that we term LunarWSN. The LunarWSN sensor nodes can make simultaneous observations from multiple positions. Each node is a miniaturized, modular design, whose sensor payload can be customized to different scientific missions. After anchoring on the lunar surface, the sensor nodes can localize themselves, set up a wireless communication network, and start the sensing operation — the measurements of permittivity of the lunar soil, which infers water content.

Name thesis:degree_name

Master

Department dc:contributor.department

Program in Media Arts and Sciences (Massachusetts Institute of Technology)

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2021

Author dc:creator

• Liu, Fangzheng

Advisor dc:contributor.advisor

• Paradiso, Joseph A.

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright MIT

Licence dc:rights.uri

• http://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/142844

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/142844