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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Spacelab data processing facility (SLDPF) quality assurance (QA)/data accounting (DA) expert systems - Transition from prototypes to operational systems

The SLDPF is responsible for the capture, quality monitoring processing, accounting, and shipment of Spacelab and/or Attached Shuttle Payloads (ASP) telemetry data to various user facilities. Expert systems will aid in the performance of the quality assurance and data accounting functions of the two SLDPF functional elements: the Spacelab Input Processing System (SIPS) and the Spacelab Output Processing System (SOPS). Prototypes were developed for each as independent efforts. The SIPS Knowledge System Prototype (KSP) used the commercial shell OPS5+ on an IBM PC/AT; the SOPS Expert System Prototype used the expert system shell CLIPS implemented on a Macintosh personal computer. Both prototypes emulate the duties of the respective QA/DA analysts based upon analyst input and predetermined mission criteria parameters, and recommended instructions and decisions governing the reprocessing, release, or holding for further analysis of data. These prototypes demonstrated feasibility and high potential for operational systems. Increase in productivity, decrease of tedium, consistency, concise historical records, and a training tool for new analyses were the principal advantages. An operational configuration, taking advantage of the SLDPF network capabilities, is under development with the expert systems being installed on SUN workstations. This new configuration in conjunction with the potential of the expert systems will enhance the efficiency, in both time and quality, of the SLDPF's release of Spacelab/AST data products.

Basile, Lisa↗
NASA NTRSDate not supplied

Data Fusion With Uncertainty Quantification for Sub-City-Scale Air Quality Assessment and Forecasting

Many information sources can support air quality assessment and forecasting, including atmospheric chemistry model outputs, satellite retrievals of column chemical and aerosol constituents, and surface-based air quality monitoring data from both regulatory and low-cost instruments. Systematic integration of these data sources provides a major opportunity to improve understanding and management of air quality, but also presents technical barriers, especially in resource- and data-constrained settings in the Global South. This presentation describes a data fusion system, currently under development using the Google Earth Engine platform, which aims to integrate the information sources listed above to support comprehensive sub-city-scale assessment and management of air quality. Furthermore, the data fusion framework includes provisions for the quantification of uncertainties in the resulting fused estimates based on the variability of and among the input data sources. These capabilities will allow air quality managers to better understand their local air quality situation, including relative confidence in the fused estimates for different constituents, locations, and times, leading to better informed air quality management decisions. This presentation covers the underlying methodology of the data fusion and uncertainty quantification approaches, provides an update on the status of its implementation, and presents early qualitative and quantitative results.

Carl Malings↗
DOE OSTI2025

Applying Deep Learning for Wildfire Identification: Economical and Accessible Solutions Leveraging Small Datasets

Wildfires significantly impact human health, air quality, visibility, weather, and climate change and cause substantial economic losses. While state and county-operated air quality monitors provide critical insights during wildfires, they are not available in all regions. This highlights the need for affordable, accessible tools that allow the general public to assess air quality impacts. In this study, we apply machine learning with deep neural networks to diagnose air quality rapidly from sky images taken at the Pacific Northwest National Laboratory in Richland, WA, USA. Using a convolutional neural network (CNN) framework, we trained a deep learning model to classify air quality indices based on sky images. By leveraging transfer learning, our approach fine-tunes a pre-trained model on a small dataset of sky images, significantly reducing training time while maintaining high accuracy. Our results demonstrate the potential of deep learning to provide rapid air quality diagnostics during wildfire episodes, offering early warnings to the public and enabling timely mitigation strategies, particularly for vulnerable populations. Additionally, we show that lower respiratory infections pose the highest health risk during acute smoke exposures. Reactive oxygen species (ROS) from wildfire particles further exacerbate health risks by triggering inflammation and other adverse effects.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Possibilities and Challenges in Using Satellite Data for PM2.5 Forecasts

Satellite remote sensing has brought our observation of the earth's atmosphere into a new era, and remote sensing capability could lead to a quantum leap in our ability of air quality monitoring and prediction. In terms of aerosols, the most common quantity from satellite retrieval is the atmospheric column aerosol optical thickness (AOT), and the most common quantity indicating air quality at the surface is the concentration of PM2.5. w e present here the relationship between the column AOT and the surface PM2.5 from a global aerosol model GOCART and from satellite and surface measurements. We will discuss the possibilities and challenges in using satellite data for PM2.5 forecasts, and if model-satellite assimilation can improve the forecast quality.

Chin, Mian↗
NASA NTRS2005

Evaluation of NASA Data Products for RPO Applications

This presentation summarizes preliminary investigations at SSC by NASA's ASD in Air Quality including decision support tools, partner plans, working groups, and committees. An overview of follow-on short-term and long-term objectives is also provided. A table of potential NASA sensors for use with air quality applications is included, along with specifications for MODIS 04 and 06 products. This presentation was originally given by Rich Piorot of the Vermont Department of Environmental Conservation - Air Quality as part of a round-table discussion during "Exploring Collaborative Opportunities in Air Quality Monitoring, Modelling and Communication Workshop" in Boulder, CO, on March 21-22, 2005; verbal consent for this presentation to be provided to Mr. Piorot was given by the NASA SSC ASD Air Quality Program Manager on March 14, 2005.

Frisbie, Troy↗
NASA NTRS2004

Development and Performance of the Oxygen Sensor in the CSA-CP Aboard the International Space Station

A combustion products analyzer (CPA) was built for use on Shuttle in response to several thermodegradation incidents that had occurred during early flights. The CPA contained sensors that measured carbon monoxide, hydrogen chloride, hydrogen cyanide, and hydrogen fluoride. These marker compounds, monitored by the CPA, were selected based upon the likely products to be released in a spacecraft fire. When the Toxicology Laboratory group at Johnson Space Center (JSC) began to assess the air quality monitoring needs for the International Space Station (ISS), the CPA was the starting point for design of an instrument to monitor the atmosphere following a thermodegradation event. The final product was significantly different from the CPA and was named the compound specific analyzer-combustion products (CSA-CP). The major change from the CPA that will be the focus of this paper was the replacement of an unreliable hydrogen fluoride (HF) sensor with an oxygen sensor. A reliable HF sensor was not commercially available, but as the toxicology group reviewed the overall monitoring strategy for ISS, it appeared that a portable oxygen sensor to backup the major constituent analyzer was needed. Therefore, an oxygen sensor replaced the HF sensor in the new instrument. This paper will describe the development, deployment, and performance of the CSA-CP oxygen sensor on both Shuttle and ISS. Also, data for CSA-CP oxygen sensor accuracy at nominal and reduced pressures will be presented.

Limero, Thomas↗
NASA NTRSDate not supplied

Differential Mobility Spectrometry on the ISS: Successes and Current Concerns

With the construction of the International Space Station (ISS), crew members moved from the relatively short flights of the Space Shuttle (~ 2 weeks) to missions lasting months to a year. As such, environmental monitoring needs also changed, transitioning from a reliance on archival sampling to a combination of archival sampling and in-flight data collection. In the case of trace volatile organic compound (VOC) monitoring, this in-flight monitoring was performed early on by the Volatile Organic Analyzer (VOA), a gas chromatograph-ion mobility spectrometer, which operated on the ISS for 7 years. This large, fixed-position analyzer was replaced by Air Quality Monitors (AQMs), a pair of small gas chromatograph-differential mobility spectrometers, in the spring of 2013. During their initial half decade of use, and covering multiple sets of units, the AQMs performed well, meeting all of their validation criteria and generally showing excellent accuracy when compared to the now-reduced archival samples. These instruments were also used to perform a survey of the US Operating Segment (US Lab Module, European Columbus Module, and Japanese Pressurized Module), confirming that the atmosphere in this segment is well-mixed. The AQMs were also able to provide important information in contingency situations, such as confirming that no ammonia was present on the ISS following alarms suggesting that the coolant loops had leaked in January 2015. As the fleet of AQMs has aged, though, issues of concern have arisen. These have ranged from pervasive electronics board problems to loss of sensitivity due to carbon dioxide to incorrect identification of compounds. Some of these issues are unavoidable due to the nature of the AQM’s use and preparation prior to flight. However, with the extension of the ISS to 2030 (well past its original 2024 lifetime), the fleet of AQMs will be asked to perform longer, requiring solutions to some of the inherent problems. In this presentation, we will discuss the history of the AQM on the ISS with a focus on more recent results. These results show both the continued usefulness of the AQM for atmospheric monitoring and also the current concerns, including: 1) the incorrect identification of benzene, 2) reporting of elevated isopropanol concentrations, and 3) the loss of the reactant ion peak (RIP) that must be resolved in order for the instrument to continue to serve as the primary trace VOC monitor on the ISS.

W T Wallace↗
NASA NTRSDate not supplied

Differential Mobility Spectrometry on the ISS: Successes and Current Concerns

With the construction of the International Space Station (ISS), crew members moved from the relatively short flights of the Space Shuttle (~ 2 weeks) to missions lasting months to a year. As such, environmental monitoring needs also changed, transitioning from a reliance on archival sampling to a combination of archival sampling and in-flight data collection. In the case of trace volatile organic compound (VOC) monitoring, this in-flight monitoring was performed early on by the Volatile Organic Analyzer (VOA), a gas chromatograph-ion mobility spectrometer, which operated on the ISS for 7 years. This large, fixed-position analyzer was replaced by Air Quality Monitors (AQMs), a pair of small gas chromatograph-differential mobility spectrometers, in the spring of 2013. During their initial half decade of use, and covering multiple sets of units, the AQMs performed well, meeting all of their validation criteria and generally showing excellent accuracy when compared to the now-reduced archival samples. These instruments were also used to perform a survey of the US Operating Segment (US Lab Module, European Columbus Module, and Japanese Pressurized Module), confirming that the atmosphere in this segment is well-mixed. The AQMs were also able to provide important information in contingency situations, such as confirming that no ammonia was present on the ISS following alarms suggesting that the coolant loops had leaked in January 2015. As the fleet of AQMs has aged, though, issues of concern have arisen. These have ranged from pervasive electronics board problems to loss of sensitivity due to carbon dioxide to incorrect identification of compounds. Some of these issues are unavoidable due to the nature of the AQM’s use and preparation prior to flight. However, with the extension of the ISS to 2030 (well past its original 2024 lifetime), the fleet of AQMs will be asked to perform longer, requiring solutions to some of the inherent problems. In this presentation, we will discuss the history of the AQM on the ISS with a focus on more recent results. These results show both the continued usefulness of the AQM for atmospheric monitoring and also the current concerns, including: 1) the incorrect identification of benzene, 2) reporting of elevated isopropanol concentrations, and 3) the loss of the reactant ion peak (RIP) that must be resolved in order for the instrument to continue to serve as the primary trace VOC monitor on the ISS.

William T. Wallace↗
NASA NTRS2021

Satellites for long-term monitoring of inland U.S. lakes: The MERIS time series and application for chlorophyll-a

Lakes and other surface fresh waterbodies provide drinking water, recreational and economic opportunities, food, and other critical support for humans, aquatic life, and ecosystem health. Lakes are also productive ecosystems that provide habitats and influence global cycles. Chlorophyll concentration provides a common metric of water quality, and is frequently used as a proxy for lake trophic state. Here, we document the generation and distribution of the complete MEdium Resolution Imaging Spectrometer (MERIS; Appendix A provides a complete list of abbreviations) radiometric time series for over 2300 satellite resolvable inland bodies of water across the contiguous United States (CONUS) and more than 5,000 in Alaska. This contribution greatly increases the ease of use of satellite remote sensing data for inland water quality monitoring, as well as highlights new horizons in inland water remote sensing algorithm development. We evaluate the performance of satellite remote sensing Cyanobacteria Index (CI)-based chlorophyll algorithms, the retrievals for which provide surrogate estimates of phytoplankton concentrations in cyanobacteria dominated lakes. Our analysis quantifies the algorithms' abilities to assess lake trophic state across the CONUS. As a case study, we apply a bootstrapping approach to derive a new CI-to-chlorophyll relationship, ChlBS, which performs relatively well with a multiplicative bias of 1.11 (11%) and mean absolute error of 1.60 (60%). While the primary contribution of this work is the distribution of the MERIS radiometric timeseries, we provide this case study as a roadmap for future stakeholders' algorithm development activities, as well as a tool to assess the strengths and weaknesses of applying a single algorithm across CONUS.

MERIS timeseries↗
NASA NTRS2011

DISCOVER-AQ: An Overview and Initial Comparisons of NO2 with OMI Observations

The first deployment of the Earth Venture -1 DISCOVER-AQ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality) project was conducted during July 2011 in the Baltimore-Washington region. Two aircraft (a P-3B for in-situ sampling and a King Air for remote sensing) were used along with an extensive array of surface-based in-situ and remote sensing instrumentation. Fourteen flight days were accomplished by both aircraft and over 250 profiles of trace gases and aerosols were performed by the P-3B over surface air quality monitoring stations, which were specially outfitted with sunphotometers and Pandora UV/Vis spectrometers. The King Air flew with the High Spectral Resolution Lidar for aerosols and the ACAM UV/Vis spectrometer for trace gases. This suite of observations allows linkage of surface air quality with the vertical distributions of gases and aerosols, with remotely-sensed column amounts observed from the surface and from the King Air, and with satellite observations from Aura (OMI and TES), GOME-2, MODIS and GOES. The DISCOVER-AQ data will allow determination of under what conditions satellite retrievals are indicative of surface air quality, and they will be useful in planning new satellites. In addition to an overview of the project, a preliminary comparison of tropospheric column NO2 densities from the integration of in-situ P-3B observations, from the Pandoras and ACAM, and from the new Goddard OMI NO2 algorithm will be presented.

Pickering, Kenneth↗
NASA NTRS2017

US Navy Submarine Sea Trial of NASA developed Multi-Gas Monitor

During a successful 2 year technology demonstration of the tunable diode laser spectroscopy (TDLS) based Multi-Gas Monitor (MGM) on the International Space Station (ISS), we began discussing with the US Navy the possibility of conducting a sea trial of an MGM on a submarine. The sea trial would also include a gas chromatography/differential mobility spectrometer based Air Quality Monitor (AQM), which is used operationally on ISS for select volatile organic compounds. AQM results will be the subject of a separate paper. The Navy’s interest in testing NASA equipment is in a planned update to the environmental monitoring equipment used aboard submarines. NASA’s goal is studying submarines as closed environment analogs to spacecraft. MGM’s core technology was developed by Vista Photonics Inc using Small Business Innovation Research (SBIR) grants and expanded for various applications using NASA program funding. The MGM measures oxygen, carbon dioxide, ammonia and water vapor in ambient air, displays concentrations with temperature and pressure, and stores 30 second moving averages. The sea trial involves colocating the instrument with the Central Air Monitor (CAM) and connecting it to rack power prior to departure, and letting it run during the entire sea trial of a few months duration. All data stored is inside MGM, with no connection to the vessel data bus. Crew intervention is limited to checking MGM periodically to see that it is working and power cycling if the display is OFF. After the trial is over, the unit with its data will be retrieved. Post sea trial calibration check and data analysis are planned and results will be compared with both CAM data and results from MGM’s ISS technology demonstration.

Mudgett, Paul D.↗
NASA NTRS2017

US Navy Submarine Sea Trial of NASA developed Multi-Gas Monitor

During a successful 2 year technology demonstration of the tunable diode laser spectroscopy (TDLS) based Multi-Gas Monitor (MGM) on the International Space Station (ISS), we began discussing with the US Navy the possibility of conducting a sea trial of an MGM on a submarine. The sea trial would also include a gas chromatography/differential mobility spectrometer based Air Quality Monitor (AQM), which is used operationally on ISS for volatile organic compound analysis. AQM preparation and results will be the subject of a separate paper. The Navy's interest in testing NASA equipment in general relates to their ongoing search for better air monitoring technology. NASA's goal is studying submarines as closed environment analogs to spacecraft. MGM's core technology was developed by Vista Photonics Inc. using Small Business Innovation Research (SBIR) grants and expanded for various applications using NASA program funding. The MGM measures oxygen, carbon dioxide, ammonia and water vapor in ambient air, displays concentrations with temperature and pressure, and stores 30 second moving averages. The sea trial involves collocating the instrument with the Central Atmosphere Monitoring System (CAMS Mk II) of the submarine, connecting it to rack power prior to departure, and letting it run during the entire 90 day patrol. All data is stored within MGM, with no connection to the vessel data bus. Crew intervention is limited to checking MGM periodically to see that it is working and power cycling if necessary. After the trial is over, the unit with its data will be retrieved. Post sea trial calibration check and data analysis are planned and results will be compared with both CAMS Mk II data and results from MGM's ISS technology demonstration. Since the sea trial itself has been delayed, this paper describes the preparation of MGM for the sea trial and also provides a summary of the latest data from the ISS MGM technology demonstration.

Mudgett, Paul D.↗
DOE OSTI2022

Omega-3 fatty acids attenuate cardiovascular effects of short-term exposure to ambient air pollution

Background: Exposure to air pollution is associated with elevated cardiovascular risk. Evidence shows that omega-3 polyunsaturated fatty acids (omega-3 PUFA) may attenuate the adverse cardiovascular effects of exposure to fine particulate matter (PM 2.5 ). However, it is unclear whether habitual dietary intake of omega-3 PUFA protects against the cardiovascular effects of short-term exposure to low-level ambient air pollution in healthy participants. In the present study, sixty-two adults with low or high dietary omega-3 PUFA intake were enrolled. Blood lipids, markers of vascular inflammation, coagulation and fibrinolysis, and heart rate variability (HRV) and repolarization were repeatedly assessed in 5 sessions separated by at least 7 days. This study was carried out in the Research Triangle area of North Carolina, USA between October 2016 and September 2019. Daily PM 2.5 and maximum 8-h ozone (O 3 ) concentrations were obtained from nearby air quality monitoring stations. Linear mixed-effects models were used to assess the associations between air pollutant concentrations and cardiovascular responses stratified by the omega-3 intake levels. Results: The average concentrations of ambient PM 2.5 and O 3 were well below the U.S. National Ambient Air Quality Standards during the study period. Significant associations between exposure to PM 2.5 and changes in total cholesterol, von Willebrand factor (vWF), tissue plasminogen activator, D-dimer, and very-low frequency HRV were observed in the low omega-3 group, but not in the high group. Similarly, O 3 -associated adverse changes in cardiovascular biomarkers (total cholesterol, high-density lipoprotein, serum amyloid A, soluable intracellular adhesion molecule 1, and vWF) were mainly observed in the low omega-3 group. Lag-time-dependent biphasic changes were observed for some biomarkers. Conclusions: This study demonstrates associations between short-term exposure to PM 2.5 and O 3 , at concentrations below regulatory standard, and subclinical cardiovascular responses, and that dietary omega-3 PUFA consumption may provide protection against such cardiovascular effects in healthy adults.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data Sharing

Current weather monitoring systems often remain out of reach for small-scale users and local communities due to their high costs and complexity. This paper addresses this significant issue by introducing a cost-effective, easy-to-use local weather station. Utilizing low-cost sensors, this weather station is a pivotal tool in making environmental monitoring more accessible and user-friendly, particularly for those with limited resources. It offers efficient in-site measurements of various environmental parameters, such as temperature, relative humidity, atmospheric pressure, carbon dioxide concentration, and particulate matter, including PM 1, PM 2.5, and PM 10. The findings demonstrate the station’s capability to monitor these variables remotely and provide forecasts with a high degree of accuracy, displaying an error margin of just 0.67%. Furthermore, the station’s use of the Autoregressive Integrated Moving Average (ARIMA) model enables short-term, reliable forecasts crucial for applications in agriculture, transportation, and air quality monitoring. Furthermore, the weather station’s open-source nature significantly enhances environmental monitoring accessibility for smaller users and encourages broader public data sharing. With this approach, crucial in addressing climate change challenges, the station empowers communities to make informed decisions based on real-time data. In designing and developing this low-cost, efficient monitoring system, this work provides a valuable blueprint for future advancements in environmental technologies, emphasizing sustainability. The proposed automatic weather station not only offers an economical solution for environmental monitoring but also features a user-friendly interface for seamless data communication between the sensor platform and end users. This system ensures the transmission of data through various web-based platforms, catering to users with diverse technical backgrounds. Furthermore, by leveraging historical data through the ARIMA model, the station enhances its utility in providing short-term forecasts and supporting critical decision-making processes across different sectors.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Remote sensing of atmospheric chemistry; Proceedings of the Meeting, Orlando, FL, Apr. 1-3, 1991

The present volume on remote sensing of atmospheric chemistry discusses special remote sensing space observations and field experiments to study chemical change in the atmosphere, network monitoring for detection of stratospheric chemical change, stratospheric chemistry studies, and the combining of model, in situ, and remote sensing in atmospheric chemistry. Attention is given to the measurement of tropospheric carbon monoxide using gas filter radiometers, long-path differential absorption measurements of tropospheric molecules, air quality monitoring with the differential optical absorption spectrometer, and a characterization of tropospheric methane through space-based remote sensing. Topics addressed include microwave limb sounder experiments for UARS and EOS, an overview of the spectroscopy of the atmosphere using an FIR emission experiment, the detection of stratospheric ozone trends by ground-based microwave observations, and a FIR Fabry-Perot spectrometer for OH measurements.

Mcelroy, James L.↗
DOE OSTI2021

Wildfires increasingly impact western US fluvial networks

Wildfires are increasing globally in frequency, severity, and extent, but their impact on fluvial networks, and the resources they provide, remains unclear. We combine remote sensing of burn perimeter and severity, in-situ water quality monitoring, and longitudinal modeling to create the first large-scale, long-term estimates of stream+river length impacted by wildfire for the western US. We find that wildfires directly impact ~6% of the total stream+river length between 1984 and 2014, increasing at a rate of 342 km/year. When longitudinal propagation of water quality impacts is included, we estimate that wildfires affect ~11% of the total stream+river length. Our results indicate that wildfire activity is one of the largest drivers of aquatic impairment, though it is not routinely reported by regulatory agencies, as wildfire impacts on fluvial networks remain unconstrained. We identify key actions to address this knowledge gap and better understand the growing threat to fluvial networks, water security, and public health risks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Scalable & Non-Destructive Characterization Strategy to Study Semiconductor/Dielectric Interfaces and Predict Wafer-Level Device Performance

The defect density present at the dielectric-semiconductor interface in an MOS structure directly influences the channel carrier characteristics in semiconductor devices, especially in wide bandgap material systems used in power devices. While these trap defects are typically quantified through electrical characterization of MOS-capacitor test structures, this treatment offers very little insight into the physical nature of interface defects. Such shortcomings demand a physical characterization strategy to guide fabrication optimization. X-ray photoelectron spectroscopy (XPS) is suggested as a viable technique to determine chemical data for dielectric interfaces formed using atomic layer deposition (ALD) on GaN substrates. Previously, 1-D XPS characterization has confirmed the presence of a Ga x O y interlayer between ALD dielectrics and the GaN substrate. In this work, XPS data is serially collected to form 2-D images of an ALD-Al 2 O 3 /GaN interface as a proof-of-concept experiment for in-situ XPS quality monitoring during ALD processing. The information provided by this work reveals some of the challenges for incorporating XPS characterization as an in-situ strategy during fabrication of GaN-based devices. Separately, electrical mapping of a 2-D array of ALD-Al 2 O 3 /GaN MOS-capacitor devices provide a means to quantify the spatial variations in interface quality across a single wafer. Physical characterization techniques, such as time-of-flight secondary ion mass spectroscopy, provide additional chemical information about the Al 2 O 3 /Ga x O y /GaN structure that complement the electrical mapping results. This analysis shows that a higher Ga x O y content correlates with higher interface state defects for trap energies deep in the band gap.

42 ENGINEERING↗
NASA NTRS2021

Ultra Long-Lived, Self-Surveying Autonomous Air Quality Sensing - Executive Summary

We set out to evolve ultra-low power air quality sensing technologies developed at JSC to add a highly accurate positioning sensor based on SBIR technology to give a self-surveying air quality monitoring platform with years-long lifetime on a small, disposable coin cell battery. Using Radio Frequency Identification (RFID) technology for data transport, the system can take advantage of RFID-based inventory management systems in place on lunar exploration assets to provide this capability with extremely small SWAP impacts. Years-long operational lifetimes enable flexible, autonomous environmental monitoring during lengthy intervals between and unprecedented situational awareness during crewed missions. Software integration of the localization system into the JSC RFID sensing platform was advanced, but the COVID-19 pandemic complicated and slowed maturation of the localization system SBIR product, and center closure indefinitely deferred a final hardware integration and system demonstration. In the meantime, progress was made to mature the air-quality sensing platform for flight, including hardware, software, antenna, and mechanical improvements. The underlying RFID sensing capability was also adapted to a drawer motion sensing system, which is currently (FY21) being taken toward an ISS flight demonstration as part of the RFID Enhanced Autonomous Logistics Management (REALM)-3 experiment.

Raymond Summers Wagner↗