Systems Integration and Operationalization: Supporting Unmanned Aircraft Systems Integration into the National Airspace System
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The UAS-NAS Project hosted a Systems Integration Operationalization (SIO) Industry Day for the SIO Request for Information (RFI) on November 30, 2017 in San Diego, California. This presentation is being presented to the same group as a follow up regarding the progress that the UAS-NAS project has made on the SIO RFI. The presentation will be virtual with a teleconference
National Aeronautics and Space Administration (NASA) initiated the Unmanned Aircraft Systems Integration and Operationalization (SIO) demonstration as a partnership between NASA and Industry with the goal of accelerating routine unmanned aircraft systems (UAS) operations in the national airspace (NAS). In order to accomplish this goal, NASA partnered separately with Bell and two other industry teams each pioneering the development, integration, and testing of their UAS, with the intent to make progress towards type certification. The program culminated in flight demonstrations representing future commercial operations by each partner.
The NASA SIO demonstration flight of April 3, 2020 represents a successful culmination of 18 months of coordinated effort between GA-ASI, NASA, the FAA, Collins Aerospace, and Honeywell Aerospace to operate a Medium Altitude, Long Endurance (MALE) Unmanned Aircraft System (UAS) safely in the National Airspace System (NAS) using industry leading prototype technologies. The GA-ASI team consisted of technical experts, program managers, engineers, mechanics, flight technicians, flight crews, and numerous other subject matter experts. This final report describes the most significant and potentially impactful aspects of the planning, integration, test, and flight aspects of this effort. GA-ASI successfully integrated the key technologies needed for UAS to fly in the NAS onto our prototype SkyGuardian UAS, which was designed to meet the most stringent airworthiness standards applicable to an aircraft of its size category. A proven Detect and Avoid (DAA) system, developed by GA-ASI and utilizing Honeywell Aerospace technology was integrated onto SkyGuardian for the first time, along with datalink radios from Collins Aerospace that meet the new civil standard for Control and Non-Payload Communication (CNPC) links. GA-ASI also obtained approvals from the FAA and FCC to operate the reconfigured UAS. The SIO demonstration flight represented a commercial aerial surveying operation conducted at medium altitude (>10,000ft above mean sea level). The aircraft’s onboard sensors were used to capture photographic, infrared and radar imagery of public and commercial infrastructure and land, and to subsequently produce the types of data products that would provide business value to potential customers. These survey services would supplement or replace services currently provided by manned airplanes and helicopters, small drones or satellites. A “virtual” mission was also planned, to show what additional survey data could have been captured during the flight if additional sensors had been installed on the aircraft’s external hardpoints. This revision of the final report focuses on information of value to the wider UAS community, and avoids propriety data to facilitate broad dissemination. It also includes a description of GA-ASI’s engagement with the FAA following the SIO flight, which led to the award of an updated Special Airworthiness Certificate in the Experimental Category (SAC-EC) and a Certificate of Waiver or Authorization (COA) allowing operation of the SkyGuardian UAS using its DAA system to satisfy right-of-way rules, instead of a chase plane. The associated operational limitations are described to illustrate the further steps that would be needed to remove those limitations for unhindered commercial operations.
NASA is conducting research under the UAS Integration in the NAS Project to develop standards that will enable mid-size and large unmanned aircraft to fly unrestricted in the National Airspace System. As these efforts move into its second phase, NASA is planning a series of flight tests and demonstrations, integrating industry partners' technologies. These events will not only provide valuable data to inform the RTCA Special Committee 228 DAA and C2 MOPS, but also provide an opportunity for the UAS community to test their technologies in a realistic environment. An overview of NASA UAS-NAS research will be presented touching on human systems integration, modeling and simulation and guidance and control. Plans for Flight Test 6 and Systems Integration Operationalization (SIO) will also be presented. The purpose of this meeting is to share with Kitty Hawk, at a high level, UAS-NAS research and discuss potential future collaboration between NASA and Kitty Hawk.
National Aeronautics and Space Administration (NASA) awarded a Cooperative Agreement to American Aerospace, and two other companies, under the Unmanned Aircraft Systems Integration and Operationalization (SIO) demonstration with the goal of accelerating routine unmanned aircraft systems (UAS) operations in the national airspace (NAS). The team lead by American Aerospace Technologies Inc (AATI) demonstrated its UAS AiRanger™ successfully on February 25 as part of NASA’s SIO program.
Unmanned aircraft will revolutionize healthcare services by providing efficient and expeditious delivery of life-saving transplant organs and supplies to hospitals in urban environments, where road traffic and congestion can slow delivery times and endanger lives. Bell has developed the Autonomous Pod Transport (APT) vehicle to serve this market, with entry into service in mid-2020s. Adverse weather conditions can introduce risks and inefficiencies in urban environments leading to flight delays and cancellations. In 2018, National Aeronautics and Space Administration (NASA) and Bell entered into a cooperative agreement, under the Systems Integration and Operationalization (SIO) program to tackle key challenges to enable future commercial unmanned aircraft operations. The Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) at the University of Massachusetts, Amherst, joined this team to demonstrate weather avoidance technologies for remotely piloted and autonomous vehicles. CASA has developed the ‘City Warn’ hazard alerting platform to gather weather information from various weather sensors and models, and based on user (or mission) preferences for alerting and on user (or unmanned aircraft) locations, the platform shares timely weather intelligence with users and the systems used by them for remote operations. This presentation discusses the weather avoidance solution developed during this project, leading up to the demonstration of the end-to-end system in Fall 2020. The presentation will cover the following topics: 1) goals related to weather avoidance 2) the design requirements process, including the results of pilot interviews, 3) weather observation and avoidance needs 4) selection of regional and national weather data sets 5) design of the weather graphical interface and 6) considerations for real-time weather alerting. The end-to-end system that was developed will be discussed, along with the results from the demonstration flight. The presentation will conclude with insights from the project team on lessons learned and best practices on weather avoidance technologies for the industry going ahead.
Unmanned aircraft will revolutionize healthcare services by providing efficient and expeditious delivery of life-saving transplant organs and supplies to hospitals in urban environments, where road traffic and congestion can slow delivery times and endanger lives. Bell has developed the Autonomous Pod Transport (APT) vehicle to serve this market, with entry into service in mid-2020s. Adverse weather conditions can introduce risks and inefficiencies in urban environments leading to flight delays and cancellations. In 2018, National Aeronautics and Space Administration (NASA) and Bell entered into a cooperative agreement, under the Systems Integration and Operationalization (SIO) program to tackle key challenges to enable future commercial unmanned aircraft operations. The Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) at the University of Massachusetts, Amherst, joined this team to demonstrate weather avoidance technologies for remotely piloted and autonomous vehicles. CASA has developed the ‘City Warn’ hazard alerting platform to gather weather information from various weather sensors and models, and based on user (or mission) preferences for alerting and on user (or unmanned aircraft) locations, the platform shares timely weather intelligence with users and the systems used by them for remote operations. This presentation discusses the weather avoidance solution developed during this project, leading up to the demonstration of the end-to-end system in Fall 2020. The presentation will cover the following topics: 1) goals related to weather avoidance 2) the design requirements process, including the results of pilot interviews, 3) weather observation and avoidance needs 4) selection of regional and national weather data sets 5) design of the weather graphical interface and 6) considerations for real-time weather alerting. The end-to-end system that was developed will be discussed, along with the results from the demonstration flight. The presentation will conclude with insights from the project team on lessons learned and best practices on weather avoidance technologies for the industry going ahead.
Systems Integration and Operationalization (SIO) Scope and Objectives, schedule, partnership requirements overview, etc. Kick off topics that will guide the course of the SIO partnership between NASA and PAE ISR.
The One Big Beautiful Bill Act (OBBB), enacted July 4, 2025, makes billions of dollars in federal energy tax credits conditional on supply chain independence from China and other foreign entities of concern. The OBBB simultaneously creates powerful economic incentives to reshore energy supply chains to the United States and allied nations. Through such incentives, the OBBB elevates digital assurance and supply chain verification from voluntary best practices into critical capabilities for demonstrating tax credit eligibility. The OBBB uses tax credit eligibility requirements to simultaneously address national security concerns regarding foreign supply chain dependencies and incentivize domestic energy manufacturing. This brief details how organizations should operationalize these requirements through baseline compliance audits, interim documentation systems, supply chain diversification strategies, and long-term institutional integration of digital assurance capabilities that turn compliance burdens into competitive advantages
Introduction: NASA’s VIPER mission presents a unique operational paradigm within the history of robotic spaceflight. The proximity of the Moon to the Earth and the terrain elements (surface characteristics, light/shadow dynamics, communication links) of the lunar South Polar landing site create unprecedented operational conditions between these two planetary bodies. Apollo era lunar science and exploration included humans in situ to operate instruments and assimilate observational inputs in real-time. Previous lunar orbital missions have worked to operational timescales, e.g., decisional timelines and communication exchanges, that were weeks in length. Mars rover missions have worked to operational timescales, e.g., decisional timelines and communication exchanges between Mars and Earth, that were hours, days, and weeks in length. In the case of the VIPER mission, our operational decisioning for rover driving and instrument commanding will be compressed to minute-scale timeframes. These operational conditions directly impact the manner and speed with which the VIPER Science Team (VST) is required to synthesize and analyze data and produce timely science-driven decisions throughout surface mission operations. The VST shall provide mission enhancing scientific input to guide rover traverse planning and drill site confirmation and selection throughout surface operations. Further, the VST input will be of vital importance to the mission’s ability to maximize science return and to meet broader NASA objectives for future lunar in-situ resource utilization (ISRU)and exploration activities. The VST co-located in the Mission Science Center (MSC) will be responsive to the tactical operational cadence of the Mission Operations Center (MOC) and will provide further strategic and Long-Term Planning (LTP) guidance to the mission. The VIPER Science Operations & Integration(SO&I)team has developed an architecture that is focused on the infusion of science-decisioning into the operational framework and execution cadence of VIPER. NASA analog research has played a significant role in the construction of the VIPER science operations systems. As an example, the SO&I team has led analog missions that have focused on bringing together expertise in the sciences (natural, applied and social) and in operations in service of learning how to build and hold together interdisciplinary work environments and what tools are needed to support high tempo, high intensity integrated decisioning. These experiences have provided an essential foundation of knowledge to the VIPER team. Those analogs that specifically influenced the VIPER science operations construct were identified through a process of comparative analysis to prioritize those that offered relevance in whole or in part, and those that did not. The analog research output that provided extensibility to the VIPER science operations architecture included remote teams of humans and robots in cooperation (synchronous and asynchronous) with simulated earthbound systems, engineering and science teams, and the integrated assembly of tools that supported scientific analysis and data synthesis and provided infrastructure for the remote testing framework. Analogs which included real-time data monitoring, synthesis, visualization and access in a democratized and operationalized manner were of particular interest to the development of the VIPER MSC toolset both in terms of the technology and the processes used to develop the supporting infrastructure. We anticipate that each subsequent mission to the lunar south pole, whether with robots or humans, will be able to optimize science and exploration return by evolving strategies to infuse real-time collaborative science-decisioning. Furthermore, these efforts will result in a foundation for science operations development in support of human-robotic exploration of deep space and Mars. NASA analogs can continue to provide the opportunity to prepare, test and iterate on the operational concepts and tools that will support these ever-expanding space exploration efforts. Our presentation will include an overview of the VIPER Science Operations & Integration development process and specifics on what aspects of analog research have had a significant impact on our work systems.
High spatial and temporal resolution air quality estimation and forecasting can be enhanced by combining global data sources, like chemical transport models and satellite remote sensing, with local information from regulatory and low-cost air quality monitors. Successful integration of data from these diverse sources is complicated by many factors, however, including differences in spatial and temporal resolution, data availability and latency issues, varying data quality, and large computational and data storage requirements. This presentation will provide an overview of a NASA-funded effort to develop the foundation for future operationalization of air quality forecasting for world-wide end-users and integration into their air quality management decision processes, which will be achieved in future phases of this multi-year project. We will summarize our progress in developing a data fusion system using the Google Earth Engine platform which can integrate model, satellite, and surface-level monitoring datasets to enhance estimation and forecasting of air-quality-relevant pollutants at sub-daily and sub-city scales. The tool is being developed in close cooperation with several city- and regional-level air quality managers in the USA and around the world. Our end-goal is to provide these air quality managers with the information they need to assess and anticipate the impacts of poor air quality, track changes in air quality due to ongoing mitigation efforts and land use changes, and identify ways to improve their air quality monitoring strategies. This presentation will focus on recent advances achieved through the project, including integration of multiple air quality datasets in a prototype data fusion system in Google Earth Engine, the quantification of uncertainties associated with our data fusion approach, and the development of user interfaces and visualization tools to convey air quality information in a way which best meets end-user needs.
High spatial and temporal resolution air quality estimation and forecasting can be enhanced by combining global data sources, like chemical transport models and satellite remote sensing, with local information from regulatory and low-cost air quality monitors. Successful integration of data from these diverse sources is complicated by many factors, however, including differences in spatial and temporal resolution, data availability and latency issues, varying data quality, and large computational and data storage requirements. This presentation will provide an overview of a NASA-funded effort to develop the foundation for future operationalization of air quality forecasting for world-wide end-users and integration into their air quality management decision processes, which will be achieved in future phases of this multi-year project. We will summarize our progress in developing a data fusion system using the Google Earth Engine platform which can integrate model, satellite, and surface-level monitoring datasets to enhance estimation and forecasting of air-quality-relevant pollutants at sub-daily and sub-city scales. The tool is being developed in close cooperation with several city- and regional-level air quality managers in the USA and around the world. Our end-goal is to provide these air quality managers with the information they need to assess and anticipate the impacts of poor air quality, track changes in air quality due to ongoing mitigation efforts and land use changes, and identify ways to improve their air quality monitoring strategies. This presentation will focus on recent advances achieved through the project, including integration of multiple air quality datasets in a prototype data fusion system in Google Earth Engine, the quantification of uncertainties associated with our data fusion approach, and the development of user interfaces and visualization tools to convey air quality information in a way which best meets end-user needs.
Degradation of freshwater ecosystems and the services they provide is a primary cause of increasing water insecurity, raising the need for integrated solutions to freshwater management. While methods for characterizing the multi-faceted challenges of managing freshwater ecosystems abound, they tend to emphasize either social or ecological dimensions and fall short of being truly integrative. This paper suggests that management for sustainability of freshwater systems needs to consider the linkages between human water uses, freshwater ecosystems and governance. We present a conceptualization of freshwater resources as part of an integrated social-ecological system and propose a set of corresponding indicators to monitor freshwater ecosystem health and to highlight priorities for management. We demonstrate an application of this new framework -the Freshwater Health Index (FHI) - in the Dongjiang River Basin in southern China, where stakeholders are addressing multiple and conflicting freshwater demands. By combining empirical and modeled datasets with surveys to gauge stakeholders' preferences and elicit expert information about governance mechanisms, the FHI helps stakeholders understand the status of freshwater ecosystems in their basin, how ecosystems are being manipulated to enhance or decrease water-related services, and how well the existing water re-source management regime is equipped to govern these dynamics over time. This framework helps to operationalize a truly integrated approach to water resource management by recognizing the interplay between governance, stakeholders, freshwater ecosystems and the services they provide
South and Southeast Asia is subject to significant hydrometeorological extremes, including drought. Under rising temperatures, growing populations, and an apparent weakening of the South Asian monsoon in recent decades, concerns regarding drought and its potential impacts on water and food security are on the rise. Reliable sub-seasonal to seasonal (S2S) hydrological forecasts could, in principle, help governments and international organizations to better assess risk and act in the face of an oncoming drought. Here, we leverage recent improvements in S2S meteorological forecasts and the growing power of Earth Observations to provide more accurate monitoring of hydrological states for forecast initialization. Information from both sources is merged in a South and Southeast Asia sub-seasonal to seasonal hydrological forecasting system (SAHFS-S2S), developed collaboratively with the NASA SERVIR program and end-users across the region. This system applies the Noah-MultiParameterization (NoahMP) Land Surface Model (LSM) in the NASA Land Information System (LIS), driven by downscaled meteorological fields from the Global Data Assimilation System (GDAS) and Climate Hazards InfraRed Precipitation products (CHIRP and CHIRPS) to optimize initial conditions. The NASA Goddard Earth Observing System Model - sub-seasonal to seasonal (GEOS-S2S) forecasts, downscaled using the National Center for Atmospheric Research (NCAR) General Analog Regression Downscaling (GARD) tool and quantile mapping, are then applied to drive 5-km resolution hydrological forecasts to a 9-month forecast time horizon. Results show that the skillful predictions of root zone soil moisture can be made one to two months in advance for forecasts initialized in rainy seasons and up to 8 months when initialized in dry seasons. The memory of accurate initial conditions can positively contribute to forecast skills throughout the entire 9-month prediction period in areas with limited precipitation. This SAHFS-S2S has been operationalized at the International Centre for Integrated Mountain Development (ICIMOD) to support drought monitoring and warning needs in the region.
This presentation provides an update on the OPTIMA GOAAT project, with emphasis on the cloud-native data platform developed in-house to ingest, manage, and operationalize high-resolution power system data. Since our last NASPI presentation, accessible via OSTI ID #2671437, the project team advanced the design and deployment of a scalable architecture capable of handling both synchronized and non-synchronized streams, including PMU, point-on-wave (POW), COMTRADE, and SCADA data. These materials review the project status, recent progress, and key lessons learned. The core of the presentation examines the architecture and engineering of our cloud-native ingestion and data management platform. We then explain how pipelines were designed to collect, normalize, time-align, store, and serve heterogeneous data at scale. We will discuss design choices such as data models, streaming versus batch ingestion, storage tiers, and interoperability with analytics applications. Practical experiences with cloud-native technologies were shared during the event, including benefits, limitations, and integration challenges in a utility environment, along with methods used to improve performance, reduce latency, and optimize resource usage. The presentation also showcases user interface designs and visualization tools that convert raw measurements and analytics results into intuitive, actionable insights for operators and engineers. During the presentation examples were provided demonstrating how visualization, event views, and summarized analytics enhance situational awareness and support operational decision-making. These use cases illustrate how a well-designed data infrastructure can bridge the gap between high-volume measurements and practical grid operations.
At the National Aeronautics and Space Administration (NASA), foresight is a coordinated, iterative, and continual process for making informed decisions. NASA faces diverse and relatively unique challenges and opportunities as the leading U.S. agency for aeronautics development, cutting-edge scientific discovery, and human space exploration. To address these challenges and leverage opportunities, NASA uses foresight to strategically plan technology development across four mission directorates: Aeronautics Research Mission Directorate, Space Technology Mission Directorate, Science Mission Directorate, and Human Exploration and Operations Mission Directorate (recently separated into the new Exploration Systems Development Mission Directorate and Space Operations Mission Directorate). The mission directorates leverage a broad community of experts and partners to incorporate technology foresight into mission and program planning. Through this process NASA realizes tangible benefits to the agency’s science, technology, and exploration programs. As an independent office, NASA’s Office of Technology, Policy, and Strategy (OTPS) provides strategic advice, supported by independent assessments and rigorous analysis, to inform NASA senior leadership on key areas to align mission and agency-level activities. OTPS serves as a trusted authority to inform technology strategy at the agency to enable future missions. Specifically, OTPS coordinates and uses inputs from a broad community of experts, both internal and external to NASA, to inform decision making for technology plans, investments, and partnerships. OTPS develops and maintains the NASA Technology Taxonomy to standardize communication across the agency’s diverse technology portfolio and the related Strategic Technology Investment Plan that integrates priorities and informs technology investment. Through these efforts, OTPS has refined elements of foresight-informed strategic planning that may be applicable to other technology-driven industries where foresight is essential for resilience. This chapter describes the processes of foresight for technology development at NASA and provides insight into the value the agency derives from these processes. The chapter further describes the role of OTPS as an independent advisory office that supports NASA’s efforts to capitalize on foresight and strategic technology planning. We present these examples with consideration for how organizations in defense, security, and other technology-driven industries can operationalize foresight in their own strategic technology development.