Results for “crowdsourcing” — Page 3

NASA NTRS2014

Using Social Media and Mobile Devices to Discover and Share Disaster Data Products Derived From Satellites

Data products derived from Earth observing satellites are difficult to find and share without specialized software and often times a highly paid and specialized staff. For our research effort, we endeavored to prototype a distributed architecture that depends on a standardized communication protocol and applications program interface (API) that makes it easy for anyone to discover and access disaster related data. Providers can easily supply the public with their disaster related products by building an adapter for our API. Users can use the API to browse and find products that relate to the disaster at hand, without a centralized catalogue, for example floods, and then are able to share that data via social media. Furthermore, a longerterm goal for this architecture is to enable other users who see the shared disaster product to be able to generate the same product for other areas of interest via simple point and click actions on the API on their mobile device. Furthermore, the user will be able to edit the data with on the ground local observations and return the updated information to the original repository of this information if configured for this function. This architecture leverages SensorWeb functionality [1] presented at previous IGARSS conferences. The architecture is divided into two pieces, the frontend, which is the GeoSocial API, and the backend, which is a standardized disaster node that knows how to talk to other disaster nodes, and also can communicate with the GeoSocial API. The GeoSocial API, along with the disaster node basic functionality enables crowdsourcing and thus can leverage insitu observations by people external to a group to perform tasks such as improving water reference maps, which are maps of existing water before floods. This can lower the cost of generating precision water maps. Keywords-Data Discovery, Disaster Decision Support, Disaster Management, Interoperability, CEOS WGISS Disaster Architecture

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NASA NTRS2017

Mining Twitter Data to Augment NASA GPM Validation

The Twitter data stream is an important new source of real-time and historical global information for potentially augmenting the validation program of NASA's Global Precipitation Measurement (GPM) mission. There have been other similar uses of Twitter, though mostly related to natural hazards monitoring and management. The validation of satellite precipitation estimates is challenging, because many regions lack data or access to data, especially outside of the U.S. and in remote and developing areas. The time-varying set of "precipitation" tweets can be thought of as an organic network of rain gauges, potentially providing a widespread view of precipitation occurrence. Twitter provides a large source of crowd for crowdsourcing. During a 24-hour period in the middle of the snow storm this past March in the U.S. Northeast, we collected more than 13,000 relevant precipitation tweets with exact geolocation. The overall objective of our project is to determine the extent to which processed tweets can provide additional information that improves the validation of GPM data. Though our current effort focuses on tweets and precipitation, our approach is general and applicable to other social media and other geophysical measurements. Specifically, we have developed an operational infrastructure for processing tweets, in a format suitable for analysis with GPM data; engaged with potential participants, both passive and active, to "enrich" the Twitter stream; and inter-compared "precipitation" tweet data, ground station data, and GPM retrievals. In this presentation, we detail the technical capabilities of our tweet processing infrastructure, including data abstraction, feature extraction, search engine, context-awareness, real-time processing, and high volume (big) data processing; various means for "enriching" the Twitter stream; and results of inter-comparisons. Our project should bring a new kind of visibility to Twitter and engender a new kind of appreciation of the value of Twitter by the science research communities.

validatio↗

NASA NTRS2018

Surprising Results from Large Crowds Using Micro-Purchase Challenges - Using Contests on Freelancing Communities to Source Innovative, Impactful and Cost-Effective Solutions

Our world is more connected than ever before. The new digital economy is empowering platforms and crowds to become a progressively strategic way for organizations to innovate ahead of their competition. Existing research shows the effectiveness and quality of solutions crowdsourcing yields, yet few organizations genuinely understand it nor are leveraging those solutions to unlock the full range of benefits. Moreover, early adopters often face structural and financial barriers towards evangelizing digital platforms at scale within their organizations. NASA is an exception - being an advocate of the field since 2010, it has paved the path for large organizations to follow. An empirical analysis is conducted on NASA's Center of Excellence for Collaborative Innovation (CoECI) micro-purchase challenges on a crowd-based platform to assess the cost-savings, quality of work, time for work turnaround and brand effects of using this problem-solving mechanism. The results proved to provide a tangible impact on all four parameters. As such, micro-purchases could become a compelling entry-point for organizations who are willing to experiment and subsequently build a convincing business case to present to stakeholders. The paper concludes with NASA's learnings, supplemented by literature, on how to redesign business processes, change conventional thinking and create an organization that will transform its future with crowds.

Tang, Sarah↗

NASA NTRS2018

Enriching the Twitter Stream Increasing Data Mining Yield and Quality Using Machine Learning

Social media data streams are important sources of real-time and historical global information for science applications. At the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), we are exploring the Twitter data stream for its potential in augmenting the validation program of NASA Earth science missions, specifically the Global Precipitation Measurement (GPM) mission. We have implemented a tweet processing infrastructure that outputs classified precipitation tweets. Inputs are "passive" tweets, along with a smaller number of tweets from "active" participants, i.e., those knowingly contributing to our effort. The "active" tweets, presumably of higher quality, enrich the Twitter stream. "Active" sources include data scraped from other social media (e.g., public Facebook posts) and data from existing crowdsourcing programs (e.g., mPING reports). In addition, there is likely relevant precipitation information in images and documents that are the end points of links often included in tweets. Information derived from these "active" sources could then be tweeted into the Twitter stream, thus enriching its quality. The objective of our current work is to mine these tweetÂ linked images and documents, using neural networks, to increase the information content and quality related to precipitation. For images, we classified them as either precipitation-related or not. For training and validation, we used images obtained via the Google custom search API. We created two models: (1) by training a simple Convolutional Neural Network and (2) by using transfer learning principles to adapt a pre-trained object recognition model. For documents, both those linked to tweets and the tweet contents, we trained Hierarchical Attention Networks to determine precipitation occurrence, type, and intensity. For training and validation, we used a keyword-filtered tweet data set labelled with ground truth data from Dark Sky (an API to retrieve weather-related labels) and the National Severe Storms Laboratory's MultiÂ Radar/Multi-Sensor (MRMS) system. Our results demonstrated the efficacy of our machine learning approaches for enriching the Twitter stream, to derive information potentially useful for validation of earth science satellite data.

Albayrak, Arif↗

NASA NTRSDate not supplied

NASA's Centennial Challenges: A Pathway to a Sustainable Lunar Presence

Since its beginning in 2005, NASA’s Centennial Challenges Program, at the time of publication of this paper, has initiated 20 challenges in technology, innovation development areas including: propulsion, robotics, communication and navigation, human health, destination systems, science instrumentation, nanotech, materials and structures and aerodynamics. As NASA moves toward the goal of a sustainable lunar presence, the agency is investing in new open innovation crowdsourcing challenges through the Centennial Challenges Program to cultivate new ideas from the public and address current technology gaps while also advancing technology for terrestrial applications.

Centennial Challenges↗

NASA NTRSDate not supplied

Populating a Graph Database to Run a Usage-Based Discovery Tool

Most dataset discovery tools for Earth Observation data rely on descriptions and other metadata of the datasets, using keyword searches or attribute filtering to determine relevance. However, these descriptions often do not include the potential uses of the data. Thus, a user working on floods will rarely see few if any rainfall datasets show up in such a search. The Usage Based Discovery tool, on the other hand, offers usage instances to the user, either research articles or applications, along with the datasets that those usage instances used. This allows a user, particularly one new to the world of Earth Observation data, to investigate which datasets are used in similar cases. The information that powers Usage-Based Discovery is a graph database of relationships of usage to dataset and usage to topic, allowing the user to narrow their search for similar cases. In order to scale out to a graph database rich enough to provide a satisfactory user experience, we combine manual and automated processes to populate the graph. The initial content of the graph has been seeded primarily via human-aided data curation methods, using sites like Google Scholar. To scale up this effort, we’ve employed crowdsourcing. It is easy for anyone to contribute to our graph using their Open Researcher and Contributor Identifier for authorization. We’re now experimenting with Machine Learning and Natural Language Processing to help automate population of the graph, starting with the classification of research articles by topic. Finding adequate training data in the absence of a comprehensive and open research article API continues to be a significant challenge.

Vincent Inverso↗

NASA NTRSDate not supplied

Small Satellite Reliability Initiative (SSRI) Knowledge Base Tool: Use Case Review and Future Functionality and Content Direction

NASA’s Small Satellite Reliability Initiative (SSRI), in conjunction with NASA’s Small Spacecraft Systems Virtual Institute (S3VI), has developed the SSRI Knowledge Base to improve mission confidence for small spacecraft. The SSRI is a collaborative activity with broad participation from civil, Department of Defense, and both national and international commercial space systems providers and stakeholders. The S3VI is jointly sponsored by NASA’s Space Technology Mission Directorate and Science Mission Directorate. The SSRI Knowledge Base is a comprehensive and searchable online tool that consolidates and organizes resources, best practices, and lessons learned from previous small satellite missions sponsored by NASA, other government agencies, and academia. This free, publicly available tool is available to the entire SmallSat community at https://s3vi.ndc.nasa.gov/ssri-kb/. The SSRI Knowledge Base provides vetted, high-quality sources of information on elements that are key to successful small satellite missions. These resources include SSRI working group generated documents and presentations in addition to existing guides, publications, standards, software tools, websites, and books. The Knowledge Base is fully searchable, offers downloadable content when possible, and otherwise links to or references content directly from within the tool. All 58 of the planned topic pages that comprise the SSRI Knowledge Base have been recently completed and include over 450 unique resources that are now available for review. Over the past several months, significant enhancements to the tool’s capabilities have been developed and implemented. These enhancements consist of the completed baseline content, an Application Programming Interface (API), improved user interfaces, new interfaces for crowdsourcing of content and user ratings, and custom website analytics to inform future development. This presentation and paper will discuss the motivation for the SSRI Knowledge Base, review educational use case(s), and outline plans for further development. The 2022 session topic that best fits the abstract (select only one): Coordinating Successful Educational Programs

Small Spacecraft↗

NASA NTRSDate not supplied

Vertical Translation System for the Common Habitat Architecture

The Common Habitat is a large, long-duration habitat that uses an SLS core stage Liquid Oxygen (LOX) tank as its primary structure. Measuring 8.4 meters in diameter and 15 meters in length, it is manufactured as a habitat and launched as such into space. It is intended for use on the Moon as part of a permanently occupied outpost, on Mars as part of an outpost that will be occupied for hundreds of days at a time, and in deep space as part of the Deep Space Exploration Vehicle where it will support crewed missions up to 1200 days in duration. A study of internal orientation and crew size resulted in a Common Habitat configuration sized for a crew of eight with a three-deck horizontal orientation. The Common Habitat Vertical Translation System provides a means for transporting crew and cargo between decks in a Common Habitat spacecraft in gravity levels varying from 0g to 1g. A crowdsourcing campaign was conducted through the GrabCAD platform to initially solicit ideas for restraints and mobility aids, including vertical translation. Four of the five top responses repeated ideas that would be incorporated into features of the Vertical Translation System. The first was a safety barrier (to prevent falls into the opening between decks) that could collapse to form a floor surface covering the opening when not in use. The second idea was a folding ladder that could be stowed in the ceiling when not in use. The third idea was an elevator platform that could traverse the ladder. Several key driving requirements were established for the Vertical Translation System: it may not penetrate into or through the lower deck; it must work on the Earth, Moon, Mars, and in microgravity; it must be easy to operate; it must enable translation of any item that can fit through the Common Habitat’s 40” x 60” hatches, inclusive of suited and unsuited crew with any degree of incapacitation and any equipment or cargo item; and it must include three component systems – deploying floor / safety barriers, a deployable ladder, and an elevator platform. Additional requirements were established for each of the component systems. The safety barriers must form a roughly 40-inch tall, complete wall enclosure on all four sides when deployed; it must include an easy to open gate that allows access to/from the ladder when deployed; and when retracted, the safety barrier must form a smooth, load-bearing floor that can be walked on, and wheeled objects can be rolled across in gravity, without being a trip hazard. The deployable ladder must be composed of multiple ladders that work together; it must stow in the ceiling when not in use; and it must not penetrate into the 40” x 60” vertical passage corridor. The elevator platform must work with the deployable ladder system; it must be able to bridge any gap in ladders between decks; it must stop at each deck flush with the deck surface; it must be capable of transporting an incapacitated crew member as a single rescuer operation; it must be capable of transporting a full-size subsystems pallet; it must function as an elevator for a crew member carrying large objects; it must have safety functions to prevent falls from the platform, or crew/cargo collisions with edges of hatch openings, or entanglement with ladder rungs/structure; it must stow when not in use; and it must autonomously both connect itself to the ladder and deploy itself to any deck where needed when called (e.g., a crew member on any deck can call for the platform and it must connect itself to the ladders without assistance and translate to the requestor’s deck). These requirements were developed into a system concept with the assistance of a NASA Pathways Intern who also added the requirement to size the design based on the use of commercial components, using existing motors and other mechanisms to ensure that the resulting system could be inexpensively produced. The Floor and Safety Barrier consists of four panels, two roughly 40 inches long and two roughly 60 inches long that can fold into the floor on top of each other when not in use. The uppermost panel is load bearing and acts as the floor surface. When deployed, they connect with each other to form a rigid barrier surrounding the vertical passageway. One of the panels contains a hinged gate that can be opened when deployed to allow for access to/from the passageway. The Deploying Ladder consists of two ladder segments, one mounted on the ceiling of the lower deck and the other mounted on the ceiling of the mid deck. A rotating mechanism is mounted on the ladder to allow it to rotate into a horizontal position against the ceiling for stowage, or down to a vertical position for use. A second rotating mechanism is built into the ladder, allowing the rungs to rotate. A toothed surface intended to work with the elevator platform covers the front of the ladder rails and the top and bottom of the rails are designed to be flush when aligned with another ladder segment. The elevator platform is essentially a motorized, self-propelled deck. It has a mechanism that holds it in contact with the ladder rails and drives itself against the toothed surface. This mechanism allows the elevator platform to ascend or descend the ladder. In order to stow the platform when not in use, a set of short ladder rails (without rungs) are mounted to the ceiling of the mid deck. When the mid deck ladder is stowed, it is flush with these rails and the platform can drive itself onto those short rails for stowage. An additional mechanism on the platform can pitch its deck surface 90 degrees, such that when the ladder is to be stowed, the platform can fold up against the ceiling. As a consequence of the ladder and elevator platform design, the opening between decks in the Common Habitat was enlarged to ensure that the elevator platform can accept a payload up to 40”x60” in dimension.

Human Centered Design↗

NASA NTRSDate not supplied

Dust Mitigation Technology to Enable Survive the Night Capabilities

Introduction: As we return to the Moon, the lunar regolith (i.e. lunar dust) covering the surface will be an obstacle to nominal operations. Accounts from Apollo astronauts and analysis of hardware returned from the surface illustrate just how deleterious the dust can be [1]. During Apollo missions, the lunar dust adhered to hardware mechanically and electrostatically [2]. Surviving the Night: Mitigating the lunar dust will be critical to surviving the night. Going hand-in-hand with other extreme environment considerations, dust mitigation is critical to mission success. Dust Impacts on Other Systems: The lunar dust can have negative implications for power, thermal, mechanisms, and several other systems or sub-systems. For example, Apollo encountered marked degradation of performance in heat rejection systems for the lunar roving vehicle, science packages, and other components because of the lunar dust [1]. For power alone, dust can cause internal clogging for power connectors, heat rejection issues, excessive dust on reflective surfaces, reduced power output for solar arrays, and so on. Dust Mitigation Strategy: In addition to considering technology solutions, it is important for hardware, systems, and or components to have a dust mitigation strategy. At a high level, hardware that will encounter the lunar dust should consider these things when defining a dust mitigation strategy: • Understand Natural Environment • Understand Induced Environment • Understand Tolerance to Dust • Write Dust Requirements • Select Dust Mitigation Solutions • Test Hardware in Dusty Environment More information on each of these can be provided to hardware owners. Dust Mitigation Technology Development: NASA has a series of technologies that may be available for hardware that needs to survive the lunar night. Many of these solutions are leveraging dust mitigation technology development efforts from NASA’s Space Technology Mission Directorate (STMD), as well as efforts from ESDMD programs, industry, and academia. Through a series of STMD programs (both internal to NASA and through partnerships), there are several technologies in development as considerations as dust mitigation solutions for hardware. Within STMD, the Game Changing Development Program (GCD) has funded several internal dust mitigation projects including low to mid TRL development, demonstrations on CLPS landers of high TRL solutions, and creating standards and best practices for dust mitigation. STMD dust mitigation efforts also include a series of partnerships for developing technologies and advancing the state of dust mitigation at NASA. This includes the Lunar Surface Innovation Consortium (LSIC), Small Business Innovation Research, Early Stage Innovations (ESI), Space Technology Research Grants (STRG), Announcement of Collaboration Opportunities (ACOs) and Tipping Points (TPs), and Challenges and Crowdsourcing, among others. There are also a series of dust mitigation solutions that have been widely used terrestrially, or during Apollo. In recent years, several studies have produced more data on the efficacy of these potential solutions in the lunar environment. Dust Mitigation Solutions: Dust mitigation solutions generally fall into four categories: • Dust Tolerant Mechanisms • Passive Dust Mitigation Capabilities • Active Dust Mitigation Capabilities • Dust Measurement Capabilities There are a series of solutions that may prove beneficial for hardware that needs to survive the lunar night, including new technology development as well as proven, terrestrial solutions. This presentation will discuss in more detail what some of these solutions are for payloads going to the surface. References: [1] J. R. Gaier, NASA/TM—2005-213610, The Effects of Lunar Dust on EVA Systems During the Apollo Missions [2] T. J. Stubbs, et al. Impact of Dust on Lunar Exploration, 2005

dust mitigation↗

NASA NTRSDate not supplied

Survive the Dust: Dust Mitigation Technology to Enable Survive the Night Capabilities

Introduction: As we return to the Moon, the lunar regolith (i.e. lunar dust) covering the surface will be an obstacle to nominal operations. Accounts from Apollo astronauts and analysis of hardware returned from the surface illustrate just how deleterious the dust can be [1]. During Apollo missions, the lunar dust adhered to hardware mechanically and electrostatically [2]. Surviving the Night: Mitigating the lunar dust will be critical to surviving the night. Going hand-in-hand with other extreme environment considerations, dust mitigation is critical to mission success. Dust Impacts on Other Systems: The lunar dust can have negative implications for power, thermal, mechanisms, and several other systems or sub-systems. For example, Apollo encountered marked degradation of performance in heat rejection systems for the lunar roving vehicle, science packages, and other components because of the lunar dust [1]. For power alone, dust can cause internal clogging for power connectors, heat rejection issues, excessive dust on reflective surfaces, reduced power output for solar arrays, and so on. Dust Mitigation Strategy: In addition to considering technology solutions, it is important for hardware, systems, and or components to have a dust mitigation strategy. At a high level, hardware that will encounter the lunar dust should consider these things when defining a dust mitigation strategy: • Understand Natural Environment • Understand Induced Environment • Understand Tolerance to Dust • Write Dust Requirements • Select Dust Mitigation Solutions • Test Hardware in Dusty Environment More information on each of these can be provided to hardware owners. Dust Mitigation Technology Development: NASA has a series of technologies that may be available for hardware that needs to survive the lunar night. Many of these solutions are leveraging dust mitigation technology development efforts from NASA’s Space Technology Mission Directorate (STMD), as well as efforts from ESDMD programs, industry, and academia. Through a series of STMD programs (both internal to NASA and through partnerships), there are several technologies in development as considerations as dust mitigation solutions for hardware. Within STMD, the Game Changing Development Program (GCD) has funded several internal dust mitigation projects including low to mid TRL development, demonstrations on CLPS landers of high TRL solutions, and creating standards and best practices for dust mitigation. STMD dust mitigation efforts also include a series of partnerships for developing technologies and advancing the state of dust mitigation at NASA. This includes the Lunar Surface Innovation Consortium (LSIC), Small Business Innovation Research, Early Stage Innovations (ESI), Space Technology Research Grants (STRG), Announcement of Collaboration Opportunities (ACOs) and Tipping Points (TPs), and Challenges and Crowdsourcing, among others. There are also a series of dust mitigation solutions that have been widely used terrestrially, or during Apollo. In recent years, several studies have produced more data on the efficacy of these potential solutions in the lunar environment. Dust Mitigation Solutions: Dust mitigation solutions generally fall into four categories: • Dust Tolerant Mechanisms • Passive Dust Mitigation Capabilities • Active Dust Mitigation Capabilities • Dust Measurement Capabilities There are a series of solutions that may prove beneficial for hardware that needs to survive the lunar night, including new technology development as well as proven, terrestrial solutions. This presentation will discuss in more detail what some of these solutions are for payloads going to the surface. References: [1] J. R. Gaier, NASA/TM—2005-213610, The Effects of Lunar Dust on EVA Systems During the Apollo Missions [2] T. J. Stubbs, et al. Impact of Dust on Lunar Exploration, 2005

dust mitigation↗

NASA NTRSDate not supplied

Game Based Learning For Earth Science Applications Training

Current NASA Earth capacity development programs employ mechanisms ranging from online resource sharing, and virtual and in-person trainings to share knowledge. While these programs are highly successful at engaging individuals around the world – in 2018, over 8000 individuals and over 2000 institutions from all 50 US states and over 140 countries were engaged through over 150 projects and trainings – user feedback has highlighted the desire for expanded hands-on, practical experiences in incorporating NASA EO insights with localized data and actions. We aim to address this gap by leveraging the benefits of game-based learning to build user skills in integrating NASA and local EO data to guide decisions for climate resiliency and hazard planning. This project is being executed as a two-phase crowdsourced challenge: 1) Phase 1 will require a well-researched product concept that reflects an understanding of NASA’s Earth data and tools and user needs, and proposes an innovative and interactive game or extended reality experience to train users in identifying relevant NASA data and applying insights to their climate resiliency decisions; 2) Winners of Phase 1 will be provided seed funding to develop a working prototype of the product. We aim to award 1-3 final winners to support the development of more than one game, thereby ensuring that NASA's diverse audiences around the world can access training games that best suit their needs and capabilities. This EO training game project fits in the NASA Earth Science Applied Sciences Program’s Capacity Development Program, contributing to the program mission of “helping people around the world better understand [NASA’s Earth] data and find ways to use them” (https://appliedsciences.nasa.gov/what-we-do/capacity-building). The final training game will complement existing programmatic activities of workforce development, trainings, and collaborative projects, while providing the unique value of providing interactive experiences to users and collecting real-time data and feedback to improve NASA’s Earth applications’ products and services related to climate resilience.

Human centered design↗

NASA NTRS2023

Do Citizen Science Intense Observation Periods Increase Data Usability? A Deep Dive of the NASA GLOBE Clouds Data Set With Satellite Comparisons

The Global Learning and Observations to Benefit the Environment (GLOBE) citizen science program has recently conducted a series of month-long intensive observation periods (IOPs), asking the public to submit daily reports on cloud and sky conditions from all regions of Earth. This provides a wealth of crowdsourced observations from the ground, which complements other conventional scientific cloud data. In addition, the GLOBE reports are matched in space and time with geostationary and low Earth orbit satellites, which allows for a straightforward comparison of cloud properties, and minimizes the biases associated with mismatched sampling between participants and satellites. The matched GLOBE dataset is used to calculate the mean observed cloud cover by atmospheric level both worldwide and by region. The overall magnitudes of cloud cover between the GLOBE participants and the matched satellites agree within 10%, which is notable given the distinctly different natures of the data sources. The mean vertical cloud profiles show GLOBE reporting more low-level clouds and fewer high-level clouds than satellites. The low cloud disagreement is likely related to satellites missing low clouds when high clouds block their view. Conversely, the high cloud disagreement is related primarily to cloud opacity, as satellites may miss some optically thin clouds. Monte Carlo testing shows the results to be robust, and the tripled amount of IOP data reduces uncertainty by half. These findings also highlight ways in which citizen science IOP data may be used to support scientific research while accounting for their unique properties. Plain Language Summary: Citizen science is becoming an increasingly prominent aspect of scientific research, and so it important to study how citizen science data can be used effectively. For example, The GLOBE Program has recently conducted a series of special data-collecting events, or “challenges”, which gathered large numbers of reports on cloud and sky conditions. Because NASA GLOBE Clouds matches the participant reports with cloud observations from satellites, we can use these data to get a combined view of clouds from above and below. When looking at the average cloud cover for different atmospheric levels across Earth, we find that the GLOBE participants and the satellites agree quite closely. This is a surprising and fascinating find, given how different in nature volunteer ground reports are to satellite measurements. However, there are some small but notable disagreements between GLOBE participants and satellites about the distribution of cloud cover at different levels. In addition, by testing the data for uncertainty, we show that the results from the GLOBE data are reliable, and that more public participation improves the reliability. So, by carefully designing the analysis methodology, and by testing for the uncertainty of the data, citizen science can make a meaningful contribution to scientific research.

J. Brant Dodson↗

NASA NTRSDate not supplied

A Crew Seat for Human Exploration in Multiple Gravity Environments

This work attempts to develop a single crew seating solution that is applicable across a range of gravity environments encountered by spacecraft proposed in several conceptual spacecraft architectures. All of these spacecraft will need to provide some sort of stationary accommodation for the crew for performing various activities such as work in science laboratories, maintenance and repair facilities, medical care facilities, and spacecraft operations centers, as well as for basic habitation in crew quarters, entertainment / relaxation facilities, and crew dining facilities. Depending on the spacecraft or architecture, this stationary accommodation may be experienced continuously in microgravity, such as would be the case for the Deep Space Exploration Vehicle. Alternately, it could be in continuous lunar or Martian gravity, such as the Common Habitat base camps. It could experience fractional gravity, such as a Pressurized Rover for In-Space Missions at a Near Earth Asteroid or one of the Martian moons. It could alternate between artificial gravity and microgravity, such as the Nautilus-X. It could alternate between microgravity and lunar or Martian gravity, such as the SpaceX Starship Human Landing System or the Blue Origin Blue Moon Block 2 Human Landing System. Or it could be in continuous Earth gravity, such as ground trainer systems. Prior human spaceflight systems for stationary accommodation have been focused on microgravity applications. These systems have their own limitations and cannot be used in a gravity environment. A public crowdsourcing campaign generated dozens of ideas, which ultimately generated a Gecko Mobility Aids system for crew translation and the Multi-Gravity Crew Seat (MGCS) for stationary accommodation. The MGCS functions in gravity as a traditional terrestrial seat, performing functions of load for the overall body and forearms, as well as head and neck load relief while positioning the body within range of an intended task. In microgravity, the MGCS functions as a body restraint, securing the body against inadvertent drifting by applying a restraining pressure at the front and back of the thighs, shoulders, and back. The initial MGCS concept was developed in a NASA hackathon and was refined through a review of dozens of terrestrial seating styles. Additionally, a review of anthropometry and biomechanics data related to the neutral body posture was conducted to help inform the microgravity configuration of the MGCS. A series of CAD models were iteratively developed, with subject matter expert reviews leading to design improvements. A scale model was constructed and used with a humanoid model to demonstrate MGCS accommodation of a human-like body in both gravity and microgravity modes. Work to develop a full-scale protype of the MGCS is discussed, including design and fabrication of the headrest, arm rest, seat back, seat pan, seat base, and the conversion mechanisms. A 1-g human-in-the-loop evaluation of the prototype assessed the acceptability of performing seated activities in the MGCS, collecting data on the usability, comfort, and ease of ingress/egress. Based on the evaluation results, design modifications needed for reduced gravity testing are documented and initial work is indicated for a reduced gravity test plan.

Restraints and Mobility Aids↗

NASA NTRS2015

Citizen Science

Scientists and engineers constantly face new challenges, despite myriad advances in computing. More sets of data are collected today from earth and sky than there is time or resources available to carefully analyze them. Some problems either don't have fast algorithms to solve them or have solutions that must be found among millions of options, a situation akin to finding a needle in a haystack. But all hope is not lost: advances in technology and the Internet have empowered the general public to participate in the scientific process via individual computational resources and brain cognition, which isn't matched by any machine. Citizen scientists are volunteers who perform scientific work by making observations, collecting and disseminating data, making measurements, and analyzing or interpreting data without necessarily having any scientific training. In so doing, individuals from all over the world can contribute to science in ways that wouldn't have been otherwise possible.

distributed computing↗