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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Raspberry Pi–powered temperature monitoring of growth chamber microclimates

While controlled environments are desirable for growing and measuring plants, growth chambers and greenhouses typically have microclimates that impact plant growth, development, and stress responses. Furthermore, opening and closing the doors of a controlled environment introduces variation in the environment, especially at temperature extremes, affecting both the measurements and the organisms within. Using multiple temperature data loggers to normalize results can be cost-prohibitive and rarely offers real-time feedback on temperature status. We used low-cost single-board computers, cameras, and temperature sensors to manage and capture growth chamber temperatures while acquiring plant image data. Detailed here are methods to document microclimates within a growth chamber so that data can be normalized to measured temperature information. This protocol describes a low-cost method for automated temperature monitoring, which enables both high-throughput measurements of temperature along with plant growth and stress responses via plant imaging.

Plant Sciences↗
NASA NTRS2014

Scalable Asset Discovery, Vulnerability Scanning, and Penetration Testing for Remote Sites and Wireless Spectrums Utilizing an Embedded Linux Plug - PwniPlug and the Raspberry Pi B+ as a Sample Pen Test

All devices attached to the NASA KSC network are subject to security vulnerability scanning and/or penetration testing. In today's changing environment, vulnerable and/or unprotected systems can easily be overlooked. Systems that are not properly managed can become a potential threat to the operational integrity of our systems and networks. This includes all NASA (internal and external) information systems within NASA KSC Internet Protocol (IP) address space, and NASA KSC facilities. The Office of the Chief Information Officer (OCIO) recommends that all NASA Centers and information systems be subject to penetration testing on a regular interval in accordance with the guidelines identified by the National Institute of Standards and Technology (NIST). (ITS-HBK-2810.04-02A) Protecting information and equipment at NASA is an area of increasing concern. In addition to the CPU's on the network; Supervisory, Control and Data Acquisition (SCADA) systems are especially vulnerable because these systems have lacked standards, use embedded controllers with little computational power and informal software, are connected to physical processes, have few operators, and are increasingly also being connected to corporate networks. The scope of work is comprised of several individual components which together build upon previous work by Drew Branch, NASA KSC Intern. The Pwn Plug is the selected COTS (Commercial-Off-The-Shelf) device chosen to test simplification of mandatory IT Security tasks. The device will be utilized to provide services to NASA KSC and enable an assessment of infrastructure soundness and regulatory compliance in an efficient, economical, and business responsive manner. The Pwn Plug is designed as a pen testing appliance which provides a hardware platform that can support commercial penetration testing efforts at significantly reduced costs. The expected outcomes are: 1) External Penetration Testing, 2) Social Engineering, 3) Procedural Documentation, 4) Recommended Remediation Action Plan, 5) System Retest & Remediation Attestation and 6) Final Reports, out briefing and Presentation. Due to physical and material constraints beyond intern and mentor control, the project was redefined as a working pen-test scenario. Limitations of lab availability and tools dictated an academic exercise. This report was developed within the scenario guidelines suggested by the project mentor. The guidelines were to be creative in developing a Pen Test program for a client.

Penetration Testing↗
NASA NTRS2023

Space Networking Implementation for Lunar Operations

The High-Rate Delay Tolerant Networking (HDTN) project at NASA has developed a performance optimized and open-source Delay Tolerant Networking (DTN) implementation. The primary goal is to create a scalable networking solution to increase the scientific data return rate of space missions. To reach this goal, HDTN must span multiple edge cases in space networking by including tools and configurations to accommodate a wide range of space systems. Typically, HDTN evaluations are conducted on a laboratory emulation test bed, made up of hardware accelerated x86 based systems capable of data rates over 10 Gbps. HDTN must have an effective implementation process on a wide range of systems to increase the sustainability of the design. One important implementation option is with low-level embedded systems which could be used on small robotic missions. This paper details the implementation process, benchmark testing, and performance results of HDTN in multiple configurations on Raspberry Pi 4 devices. By implementing HDTN on a Raspberry Pi 4, a process for building HDTN onto ARM processors was developed and utilized to conduct benchmark tests in multiple network configurations, achieving a data rate performance exceeding 600 Mbps. Based on these results, HDTN proved to run on small ARM based systems with slight modifications to the build procedure. These results were then extended to evaluating an implementation of the HDTN software parsed across several Raspberry Pi 4 nodes. To test this capability, HDTN was configured in a simplified cut-through setup and distributed among multiple Raspberry Pi 4 processors. This distributed architecture was benchmark tested in a similar fashion to the testing of a singular HDTN implementation. The results from the benchmark testing are used to examine how these implementation options and capabilities can expand the use cases for DTN, and particularly with small robotic missions.

Space Networking↗
NASA NTRS2015

Pi-Sat: A Low Cost Small Satellite and Distributed Spacecraft Mission System Test Platform

Current technology and budget trends indicate a shift in satellite architectures from large, expensive single satellite missions, to small, low cost distributed spacecraft missions. At the center of this shift is the SmallSatCubesat architecture. The primary goal of the Pi-Sat project is to create a low cost, and easy to use Distributed Spacecraft Mission (DSM) test bed to facilitate the research and development of next-generation DSM technologies and concepts. This test bed also serves as a realistic software development platform for Small Satellite and Cubesat architectures. The Pi-Sat is based on the popular $35 Raspberry Pi single board computer featuring a 700Mhz ARM processor, 512MB of RAM, a flash memory card, and a wealth of IO options. The Raspberry Pi runs the Linux operating system and can easily run Code 582s Core Flight System flight software architecture. The low cost and high availability of the Raspberry Pi make it an ideal platform for a Distributed Spacecraft Mission and Cubesat software development. The Pi-Sat models currently include a Pi-Sat 1U Cube, a Pi-Sat Wireless Node, and a Pi-Sat Cubesat processor card.The Pi-Sat project takes advantage of many popular trends in the Maker community including low cost electronics, 3d printing, and rapid prototyping in order to provide a realistic platform for flight software testing, training, and technology development. The Pi-Sat has also provided fantastic hands on training opportunities for NASA summer interns and Pathways students.

Software↗
NASA NTRS2018

Increasing Flight Software Reuse with OpenSatKit

In January 2015 the NASA Goddard Space Flight Center (GSFC) released the Core Flight System (cFS) as open source under the NASA Open Source Agreement (NOSA) license. The cFS is based on flight software (FSW) developed for 12 spacecraft spanning nearly two decades of effort and it can provide about a third of the FSW functionality for a low-earth orbiting scientific spacecraft. The cFS is a FSW framework that is portable, configurable, and extendable using a product line deployment model. However, the components are maintained separately so the user must configure, integrate, and deploy them as a cohesive functional system. This can be very challenging especially for organizations such as universities building cubesats that have minimal experience developing FSW. Supporting universities was one of the primary motivators for releasing the cFS under NOSA. This paper describes the OpenSatKit that was developed to address the cFS deployment challenges and to serve as a cFS training platform for new users. It provides a fully functional out-of-the box software system that includes NASA's cFS, Ball Aerospaceâ€"TM"s command and control system COSMOS, and a NASA dynamic simulator called 42. The kit is freely available since all of the components have been released as open source. The kit runs on a Linux platform, includes 8 cFS applications, several kit-specific applications, and built in demos illustrating how to use key application features. It also includes the software necessary to port the cFS to a Raspberry Pi and instructions for configuring COSMOS to communicate with the target. All of the demos and test scripts can be rerun unchanged with the cFS running on the Raspberry Pi. The cFS uses a 3-tiered layered architecture including a platform abstraction layer, a Core Flight Executive (cFE) middle layer, and an application layer. Similar to smart phones, the cFS application layer is the key architectural feature for userâ€"TM"s to extend the FSW functionality to meet their mission-specific requirements. The platform abstraction layer and the cFE layers go a step further than smart phones by providing a platform-agnostic Application Programmer Interface (API) that allows applications to run unchanged on different platforms. OpenSatKit can serve two significant architectural roles that will further help the adoption of the cFS and help create a community of users that can share assets. First, the kit is being enhanced to automate the integration of applications with the goal of creating a virtual cFS 'App Store'. Second, a platform certification test suite can be developed that would allow users to verify the port of the cFS to a new platform. This paper will describe the current state of these efforts and future plans.

McComas, David↗
NASA NTRS2018

Increasing Flight Software Reuse with OpenSatKit

In January 2015 the NASA Goddard Space Flight Center (GSFC) released the Core Flight System (cFS) as open source under the NASA Open Source Agreement (NOSA) license. The cFS is based on flight software (FSW) developed for 12 spacecraft spanning nearly two decades of effort and it can provide about a third of the FSW functionality for a low-earth orbiting scientific spacecraft. The cFS is a FSW framework that is portable, configurable, and extendable using a product line deployment model. However, the components are maintained separately so the user must configure, integrate, and deploy them as a cohesive functional system. This can be very challenging especially for organizations such as universities building cubesats that have minimal experience developing FSW. Supporting universities was one of the primary motivators for releasing the cFS under NOSA. This paper describes the OpenSatKit that was developed to address the cFS deployment challenges and to serve as a cFS training platform for new users. It provides a fully functional out-of-the box software system that includes NASA's cFS, Ball Aerospace's command and control system COSMOS, and a NASA dynamic simulator called 42. The kit is freely available since all of the components have been released as open source. The kit runs on a Linux platform, includes 8 cFS applications, several kit-specific applications, and built in demos illustrating how to use key application features. It also includes the software necessary to port the cFS to a Raspberry Pi and instructions for configuring COSMOS to communicate with the target. All of the demos and test scripts can be rerun unchanged with the cFS running on the Raspberry Pi. The cFS uses a 3-tiered layered architecture including a platform abstraction layer, a Core Flight Executive (cFE) middle layer, and an application layer. Similar to smart phones, the cFS application layer is the key architectural feature for users to extend the FSW functionality to meet their mission-specific requirements. The platform abstraction layer and the cFE layers go a step further than smart phones by providing a platform-agnostic Application Programmer Interface (API) that allows applications to run unchanged on different platforms. OpenSatKit can serve two significant architectural roles that will further help the adoption of the cFS and help create a community of users that can share assets. First, the kit is being enhanced to automate the integration of applications with the goal of creating a virtual cFS "App Store".. Second, a platform certification test suite can be developed that would allow users to verify the port of the cFS to a new platform. This paper will describe the current state of these efforts and future plans.

Computer Programming and Software↗
NASA NTRSDate not supplied

Studying Microbial Adaptation in the Laboratory: Sensor & Control Upgrades for an Experimental Evolution Biofluidics System

Experimental evolution (EE) involves iteratively exposing a microbial community to specific stressors to study its response to changes in environment over time. EE work is commonly done manually in the laboratory, but, when there are many environmental variables to measure and adjust, it is highly labor intensive, prone to human error, and challenging to scale. Single-purpose automated continuous culturing chambers exist, but implement only limited stressor types. A more general-purpose design is desirable. The BeING Lab at Ames Research Center created the prototype Automated Adaptive Directed Evolution Chamber (AADEC) to address these problems, beginning with Escherichia coli tolerance of short-wave ultraviolet (UV-C) radiation and of temperature. In newer versions, AADEC monitors microbial activity and can adjust the UV-C and temperature levels automatically. An optical density measurement is used to determine how many cells are present in the growth medium—over time, this corresponds to how many survive and reproduce. Oxidation-reduction potential provides information on consumed metabolic energy, and pH and electrical conductivity on metabolic products. Dissolved oxygen content is used to determine aerobic vs anaerobic growth. A Raspberry Pi computer processes all this data to set the UV-C stressor level. AADEC’s auxiliary systems include peristaltic pumps to change media and agitation to counteract cell settling. These actuators can also act as additional stressors. With the Raspberry Pi monitoring sensors and adjusting actuators in real time, AADEC takes measurements and controls the environment much more accurately than can be done with a manual EE implementation. The third and latest AADEC iteration is the first to simplify design and usage with circuits on PCBs and the ability to pre-program experimental protocols. Still planned is expansion to a multi-well design for the study of varying cell cultures in parallel, which will enable researchers to retain and re-inoculate cultures exhibiting the desired trait most strongly while flushing out others. AADEC’s special capabilities make it a valuable tool for studying life under multiple stressors, enabling scientists to replicate changes in climate on microbes for study in a lab setting.

Microbial Adaptation↗
NASA NTRS2017

OpenSatKit Enables Quick Startup for CubeSat Missions

The software required to develop, integrate, and operate a spacecraft is substantial regardless of whether its a large or small satellite. Even getting started can be a monumental task. To solve this problem, NASAs Core Flight System (cFS), NASA's 42 spacecraft dynamics simulator, and Ball Aerospaces COSMOS ground system have been integrated together into a kit called OpenSatKit that provides a complete and open source software solution for starting a new satellite mission. Users can have a working system with flight software, dynamics simulation, and a ground command and control system up and running within hours.Every satellite mission requires three primary categories of software to function. The first is Flight Software (FSW) which provides the onboard control of the satellites and its payload(s). NASA's cFS provides a great platform for developing this software. Second, while developing a satellite on earth, it is necessary to simulate the satellites orbit, attitude, and actuators, to ensure that the systems that control these aspects will work correctly in the real environment. NASAs 42 simulator provides these functionalities. Finally, the ground has to be able to communicate with the satellite, monitor its performance and health, and display its data. Additionally, test scripts have to be written to verify the system on the ground. Ball Aerospace's COSMOS command and control system provides this functionality. Once the OpenSatKit is up and running, the next step is to customize the platform and get it running on the end target. Starting from a fully working system makes porting the cFS from Linux to a users platform much easier. An example Raspberry Pi target is included in the kit so users can gain experience working with a low cost hardware target. All users can benefit from OpenSatKit but the greatest impact and benefits will be to SmallSat missions with constrained budgets and small software teams. This paper describes OpenSatKits system design, the steps necessary to run the system to target the Raspberry Pi, and future plans. OpenSatKit is a free fully functional spacecraft software system that we hope will greatly benefit the SmallSat community.

Software↗
NASA NTRS2017

Abstract - Belbas, Nicholas (EC2)

Originally, I was brought into the Design and Analysis Branch in the Crew and Thermal Systems to work on administrative tasks like archiving and scheduling. However, I ended up splitting my time between secretarial tasks and a technical project. My technical project was originally meant to be a wireless sensor package for the 20ft Spacecraft Thermal Vacuum Chamber in the B7 High Bay. I would be using a miniature wifi development board and a temperature/humidity sensor along with custom 3D modeling to accomplish this. However, after some discussion with my technical mentor, the plan was changed to a mobile autonomous self-charging sensor platform. A mobile platform will allow the sensors to be moved around without depressurizing the chamber. Also, the self-charging aspect of the package allows for almost unlimited time in the chamber. If the on-board battery runs low, the robot can easily be driven to its charging dock and continue to transmit while charging. The driving base is based around a Raspberry Pi 3 board with a 12C PMW DC Motor controller and a PWM controller driving two small gear motors. The sensor transmitter itself is a RHT03 temperature and humidity sensor and Cozir CO2 sensor connected to an ESP8266 Huzzah board. The power distribution system utilizes a pair of 3.7v 3600mah lipo batteries wired to Powerboost 500 boards. Also, the self-charging mechanism utilizes two 12v-max inductive charging coils wired into the same Powerboost boards as the battery. The Raspberry pi is running Python 3.3 for the driving base and Javascript MJPEG library for transmitting live video from the onboard camera. The sensor package is running Arduino-based C++ and the program capturing the data is running PyqtGraph Python and HTML. The shell of the robot itself is a 3D printed case that will (work in progress) snap together. The photo to the left shows the two halves separated from each other. The black shell contains the power distribution boards and connectors while the white shell contains the driving base and data systems.

Belbas, Nicholas↗
DOE OSTI2025

Using radioactive material to evaluate decontamination of contaminated electronics

Electronic materials are used everywhere and can get easily contaminated by their use in the field/laboratory. The goal of this project was to use radioactive material to track the effectiveness of a cleaning procedure using an off-the-shelf cleaning gel. Radioactive potassium bromide (KBr) was used as a model contaminant in four contamination scenarios to gauge the effectiveness of a cleaning gel in the decontamination of contaminated raspberry pi’s. Finally, the investigated decontamination technique was found to be 75–97% effective in removing contamination from the tested electronic devices. 95% of the contaminated electronic devices retained their functionality post-decontamination.

38 - RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCL↗
DOE OSTI2026

Autonomous monitoring of algal biomass: Success stories and lessons learned from long-term field deployment

Autonomous, high-frequency monitoring of outdoor algal ponds is needed to quantify biomass productivity and detect culture decline in environments prone to contamination, grazers, and variable operating conditions. We report successes and lessons learned in translating a laboratory spectroradiometric monitoring approach to a multi-year autonomous field deployment at the Arizona Center for Algae Technology and Innovation (AzCATI). The system measures spectrally resolved pond reflectance by ratioing upwelling radiance from each raceway to simultaneous downwelling sky irradiance using fiber-coupled spectrometers. A physics-based reflectance model (ASHARP) is fit to each spectrum pair to estimate optical parameters, including a biomass-proxy coefficient (C a ) which enables near-real-time tracking of biomass accumulation and culture state at 2–5 min intervals. From May 2022 through September 2025 the platform operated continuously while scaling from two to six raceway ponds. Several strains of algae were monitored successfully, including the high productivity Tetraselmis striata and Picochlorum celeri. Transitioning data acquisition from a Windows laptop to a Raspberry Pi improved uptime from 57% (2022) to ~89% (2024–2025) and enabled routine real-time analysis. Further, we converted relative biomass estimates to absolute ash-free dry weight (AFDW) using experimentally-derived calibrations, providing field-relevant biomass predictions with conservative confidence bounds. These results demonstrate the feasibility of long-term, autonomous optical monitoring for well-mixed open-raceway algal cultivation and provide practical guidance for reliable field operation and scaling.

Katinas, Christopher Michael [Sandia National Labo↗
DOE OSTI2025

TRIM: AI Guided Random Number Generation for Resource-Constrained IoT Systems

Random numbers often serve as the backbone for many security solutions in diverse domains such as cryptography, side channel leakage prevention, and moving target defense. However, generating true random numbers requires a physical source of entropy (e.g. hardware, quantum, environmental phenomenon) making it difficult to realize at a large scale and at a low cost. On the flip side, pseudorandom number generators (easy to implement) following a specific distribution (e.g. Gaussian) can be easily compromised given a sufficient amount of traces. In this work, we have developed a machine learning-guided generative approach that can be used to create portable, resource-efficient, and cost-effective random number generators with high throughput and true randomness characteristics. We implement the proposed approach as a highly parameterized framework and perform extensive evaluation for different settings. The framework was able to learn from true random sources such as irrational numbers and environmental audio noise and imitate those sources towards generating new good quality random numbers on demand. We have generated more than 1 billion bits and observed robust performance in terms of true randomness metrics obtained from NIST SP 800-22 and FIPS 140-1 randomness test suites achieving a throughput of up to 142.85 Mbps. Compared to the state-of-the-art (SOTA) technique, the iso-cost setup of our framework can achieve more than 500 Mbps in a distributed setting. We have evaluated the efficacy of running the true randomness imitation AI models on target edge devices such as Raspberry Pi 4 (Model B), Nvidia Jetson Nano, Nvidia Jetson Orin Nano and Nvidia Jetson Xavier. We have also looked at the security of the TRIM framework itself against different adversarial threat models.

Cybersecurity↗
DOE OSTI2026

lumicap v0.1

Automated HDR luminance imaging system designed for daylighting research and building science. It controls a fisheye-lens camera to capture time-lapse bracket sequences, merges them into calibrated HDR images, and runs a full post-processing pipeline — all unattended. Features: - Scheduled LDR bracket capture via gphoto2 - HDR merging with vignetting, ND filter, and fisheye projection corrections - Illuminance and luminance meter integration (Konica Minolta T-10A, LS-100/150) - Daylight glare probability (DGP) and solar position computation - Automated false-color rendering, JPEG thumbnails, and daily time-lapse video - CSV data logging per timestep Uses: - Long-term monitoring of daylight conditions in buildings - Glare analysis for occupant comfort research - Solar irradiance and sky luminance studies Advantages: - End-to-end automation — capture, calibration, analysis, and archiving run without manual intervention - Built on the proven Radiance toolchain, ensuring photometrically accurate HDR output - Hardware-agnostic meter support via serial auto-detection - Lightweight — no GUI overhead, deployable on a headless Raspberry Pi or similar embedded system

Wang, Taoning [Lawrence Berkeley National Laborato↗
DOE OSTI2026

A New Era for Bubble Chamber Technology

Neutrino experiments like DUNE are limited by how well we understand the way neutrinos actually interact with atoms. The best way to fix that is to measure interactions on hydrogen, since a hydrogen nucleus is just a single free proton with largely none of the nuclear effects that heavier targets like argon have. The catch is that no one has built a hydrogen bubble chamber for a neutrino beam since the 1980s, mostly because the old chambers had too low of an active time. MAMBA is a project focused on bringing that technology back but built to cycle continuously at 1 Hz. I spent my summer internship on two of the subsystems that make that kind of speed possible. First, I helped install and test a new solid copper thermal link that replaced the old flexible braided cooling path, and it brought the coldhead down to 21.3 K, right at the target temperature. Second, I built and tested a Raspberry Pi based PLC control system, and across 20,000 trials it answered in a median of 0.64 ms, with only 0.66\% of trials running past 1 ms. Both results point the same direction: that inexpensive, off the shelf hardware can perform fast and reliable enough to eventually run a bubble chamber the way MAMBA needs it to run.

Williams, Nicholas [DuPage Coll.]↗
DOE OSTI2026

202508 HAIIC IR Images with Attitude Data at BNF

This campaign aims to collect infrared imagery using a custom data acquisition system to improve and validate a previously developed attitude estimation algorithm, with a focus on ensuring reliable performance at higher altitudes. The system integrates a Boson+320 infrared camera, a VN-200 IMU for recording attitude data synchronized with image acquisition, and a Raspberry Pi 4B+ for onboard processing and storage. Image orientation was controlled using a Gremsy T7 gimbal. The primary dataset spans roll angles from −40° to 40° and pitch angles from −20° to 40°, sampled at 1° increments. Additional, smaller datasets were also collected at 2.5° angular intervals.

Boson+320↗