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By stretching the capabilities of NASA's Hubble Space Telescope to the limit, astronomers have photographed the close companion of Polaris for the first time. This sequence of images shows that the North Star, Polaris is really a triple star system. These findings were presented today in a press conference at the 207th meeting of the American Astronomical Society in Washington, D.C.

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    • By NASA
      An image of a coastal marshland combines aerial and satellite views in a technique similar to hyperspectral imaging. Combining data from multiple sources gives scientists information that can support environmental management.John Moisan When it comes to making real-time decisions about unfamiliar data – say, choosing a path to hike up a mountain you’ve never scaled before – existing artificial intelligence and machine learning tech doesn’t come close to measuring up to human skill. That’s why NASA scientist John Moisan is developing an AI “eye.”
      Oceanographer John MoisanNASA Moisan, an oceanographer at NASA’s Wallops Flight Facility near Chincoteague, Virginia, said AI will direct his A-Eye, a movable sensor. After analyzing images his AI would not just find known patterns in new data, but also steer the sensor to observe and discover new features or biological processes. 
      “A truly intelligent machine needs to be able to recognize when it is faced with something truly new and worthy of further observation,” Moisan said. “Most AI applications are mapping applications trained with familiar data to recognize patterns in new data. How do you teach a machine to recognize something it doesn’t understand, stop and say ‘What was that? Let’s take a closer look.’ That’s discovery.”
      Finding and identifying new patterns in complex data is still the domain of human scientists, and how humans see plays a large part, said Goddard AI expert James MacKinnon. Scientists analyze large data sets by looking at visualizations that can help bring out relationships between different variables within the data.
      Infrared images like this one from a marsh area on the Maryland/Virginia Eastern Shore coastal barrier and back bay regions reveal clues to scientists about plant health, photosynthesis, and other conditions that affect vegetation and ecosystems.John Moisan It’s another story to train a computer to look at large data streams in real time to see those connections, MacKinnon said. Especially when looking for correlations and inter-relationships in the data that the computer hasn’t been trained to identify. 
      Moisan intends first to set his A-Eye on interpreting images from Earth’s complex aquatic and coastal regions. He expects to reach that goal this year, training the AI using observations from prior flights over the Delmarva Peninsula. Follow-up funding would help him complete the optical pointing goal.
      “How do you pick out things that matter in a scan?” Moisan asked. “I want to be able to quickly point the A-Eye at something swept up in the scan, so that from a remote area we can get whatever we need to understand the environmental scene.” 
      Moisan’s on-board AI would scan the collected data in real-time to search for significant features, then steer an optical sensor to collect more detailed data in infrared and other frequencies. 
      Thinking machines may be set to play a larger role in future exploration of our universe. Sophisticated computers taught to recognize chemical signatures that could indicate life processes, or landscape features like lava flows or craters, might offer to increase the value of science data returned from lunar or deep-space exploration. 
      Today’s state-of-the-art AI is not quite ready to make mission-critical decisions, MacKinnon said.
      “You need some way to take a perception of a scene and turn that into a decision and that’s really hard,” he said. “The scary thing, to a scientist, is to throw away data that could be valuable. An AI might prioritize what data to send first or have an algorithm that can call attention to anomalies, but at the end of the day, it’s going to be a scientist looking at that data that results in discoveries.” 
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      Last Updated Feb 10, 2025 Related Terms
      Goddard Space Flight Center Artificial Intelligence (AI) Goddard Technology People of Goddard Technology Wallops Flight Facility Keep Exploring Discover More Topics From NASA
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    • By NASA
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      2 Min Read More Than 400 Lives Saved with NASA’s Search and Rescue Tech in 2024
      NASA Artemis II crew members are assisted by U.S. Navy personnel as they exit a mockup of the Orion spacecraft in the Pacific Ocean during Underway Recovery Test 11 (URT-11) on Feb. 25, 2024. Credits: NASA/Kenny Allen NASA’s Search and Rescue technologies enabled hundreds of lives saved in 2024.NASA/Dave Ryan Did you know that the same search and rescue technologies developed by NASA for astronaut missions to space help locate and rescue people across the United States and around the world? 
      NASA’s collaboration with the international satellite-aided search and rescue effort known as Cospas-Sarsat has enabled the development of multiple emergency location beacons for explorers on land, sea, and air. 
      Of the 407 lives saved in 2024 through search and rescue efforts in the United States, NOAA (National Oceanic and Atmospheric Administration) reports that 52 rescues were the result of activated personal locator beacons, 314 from emergency position-indicating radio beacons, and 41 from emergency locator transmitters. Since 1982, more than 50,000 lives have been saved across the world. 
      Using GPS satellites, these beacons transmit their location to the Cospas-Sarsat network once activated. The beacons then provide the activation coordinates to the network, allowing first responders to rescue lost or distressed explorers.  
      NASA Artemis II crew members are assisted by U.S. Navy personnel as they exit a mockup of the Orion spacecraft in the Pacific Ocean during Underway Recovery Test 11 (URT-11) on Feb. 25, 2024, while his crewmates look on. URT-11 is the eleventh in a series of Artemis recovery tests, and the first time NASA and its partners put their Artemis II recovery procedures to the test with the astronauts.NASA/Kenny Allen The Search and Rescue Office, part of NASA’s SCaN (Space Communications and Navigation) Program, has assisted in search and rescue services since its formation in 1979 Now, the office is building on their long legacy of Earth-based beacon development to support crewed missions to space. 
      The beacons also are used for emergency location, if needed, as part of NASA’s crew launches to and from the International Space Station, and will support NASA’s Artemis campaign crew recovery preparations during future missions returning from deep space. Systems being tested, like the ANGEL (Advanced Next-Generation Emergency Locator) beacon, are benefitting life on Earth and missions to the Moon and Mars. Most recently, NASA partnered with the Department of Defense to practice Artemis II recovery procedures – including ANGEL beacon activation – during URT-11 (Underway Recovery Test 11).  
      Miniaturized Advanced Next-Generation Emergency Locator (ANGEL) beacons will be attached to the astronauts’ life preserver units. When astronauts Reid Wiseman, Victor Glover, Christina Koch, and CSA (Canadian Space Agency) astronaut Jeremy Hanse splash back down to Earth — or in the unlikely event of a launch abort scenario — these beacons will allow them to be found if they need to egress from the Orion capsule.NASA The SCaN program at NASA Headquarters in Washington provides strategic oversight to the Search and Rescue office. NOAA manages the U.S. network region for Cospas-Sarsat, which relies on flight and ground technologies originally developed at NASA’s Goddard Space Flight Center in Greenbelt, Maryland. U.S. region rescue efforts are led by the U.S. Coast Guard, U.S. Air Force, and many other local rescue authorities. 

      About the Author
      Kendall Murphy
      Technical WriterKendall Murphy is a technical writer for the Space Communications and Navigation program office. She specializes in internal and external engagement, educating readers about space communications and navigation technology.
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      Last Updated Feb 06, 2025 EditorGoddard Digital TeamContactKatherine Schauerkatherine.s.schauer@nasa.govLocationNASA Goddard Space Flight Center Related Terms
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    • By NASA
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      Captured by the HiRISE camera on NASA’s Mars Reconnaissance Orbiter on March 4, 2021, this impact crater was found in Cerberus Fossae, a seismically active region of the Red Planet. Scien-tists matched its appearance on the surface with a quake detected by NASA’s InSight lander. With help from AI, scientists discovered a fresh crater made by an impact that shook material as deep as the Red Planet’s mantle.
      Meteoroids striking Mars produce seismic signals that can reach deeper into the planet than previously known. That’s the finding of a pair of new papers comparing marsquake data collected by NASA’s InSight lander with impact craters spotted by the agency’s Mars Reconnaissance Orbiter (MRO).
      The papers, published on Monday, Feb. 3, in Geophysical Research Letters (GRL), highlight how scientists continue to learn from InSight, which NASA retired in 2022 after a successful extended mission. InSight set the first seismometer on Mars, detecting more than 1,300 marsquakes, which are produced by shaking deep inside the planet (caused by rocks cracking under heat and pressure) and by space rocks striking the surface.
      By observing how seismic waves from those quakes change as they travel through the planet’s crust, mantle, and core, scientists get a glimpse into Mars’ interior, as well as a better understanding of how all rocky worlds form, including Earth and its Moon.
      A camera on the robotic arm of NASA’s InSight captured the lander setting down its Wind and Thermal Shield on Feb. 2, 2019. The shield covered InSight’s seismometer, which captured data from more than 1,300 marsquakes over the lander’s four-year mission. Researchers have in the past taken images of new impact craters and found seismic data that matches the date and location of the craters’ formation. But the two new studies represent the first time a fresh impact has been correlated with shaking detected in Cerberus Fossae, an especially quake-prone region of Mars that is 1,019 miles (1,640 kilometers) from InSight.
      The impact crater is 71 feet (21.5 meters) in diameter and much farther from InSight than scientists expected, based on the quake’s seismic energy. The Martian crust has unique properties thought to dampen seismic waves produced by impacts, and researchers’ analysis of the Cerberus Fossae impact led them to conclude that the waves it produced took a more direct route through the planet’s mantle.
      InSight’s team will now have to reassess their models of the composition and structure of Mars’ interior to explain how impact-generated seismic signals can go that deep.
      “We used to think the energy detected from the vast majority of seismic events was stuck traveling within the Martian crust,” said InSight team member Constantinos Charalambous of Imperial College London. “This finding shows a deeper, faster path — call it a seismic highway — through the mantle, allowing quakes to reach more distant regions of the planet.”
      Spotting Mars Craters With MRO
      A machine learning algorithm developed at NASA’s Jet Propulsion Laboratory in Southern California to detect meteoroid impacts on Mars played a key role in discovering the Cerberus Fossae crater. In a matter of hours, the artificial intelligence tool can sift through tens of thousands of black-and-white images captured by MRO’s Context Camera, detecting the blast zones around craters. The tool selects candidate images for examination by scientists practiced at telling which subtle colorations on Mars deserve more detailed imaging by MRO’s High-Resolution Imaging Science Experiment (HiRISE) camera.
      “Done manually, this would be years of work,” said InSight team member Valentin Bickel of the University of Bern in Switzerland. “Using this tool, we went from tens of thousands of images to just a handful in a matter of days. It’s not quite as good as a human, but it’s super fast.”
      Bickel and his colleagues searched for craters within roughly 1,864 miles (3,000 kilometers) of InSight’s location, hoping to find some that formed while the lander’s seismometer was recording. By comparing before-and-after images from the Context Camera over a range of time, they found 123 fresh craters to cross-reference with InSight’s data; 49 of those were potential matches with quakes detected by the lander’s seismometer. Charalambous and other seismologists filtered that pool further to identify the 71-foot Cerberus Fossae impact crater.
      Deciphering More, Faster
      The more scientists study InSight’s data, the better they become at distinguishing signals originating inside the planet from those caused by meteoroid strikes. The impact found in Cerberus Fossae will help them further refine how they tell these signals apart.
      “We thought Cerberus Fossae produced lots of high-frequency seismic signals associated with internally generated quakes, but this suggests some of the activity does not originate there and could actually be from impacts instead,” Charalambous said.
      The findings also highlight how researchers are harnessing AI to improve planetary science by making better use of all the data gathered by NASA and ESA (European Space Agency) missions. In addition to studying Martian craters, Bickel has used AI to search for landslides, dust devils, and seasonal dark features that appear on steep slopes, called slope streaks or recurring slope linae. AI tools have been used to find craters and landslides on Earth’s Moon as well.
      “Now we have so many images from the Moon and Mars that the struggle is to process and analyze the data,” Bickel said. “We’ve finally arrived in the big data era of planetary science.”
      More About InSight
      JPL managed InSight for the agency’s Science Mission Directorate. InSight was part of NASA’s Discovery Program, managed by the agency’s Marshall Space Flight Center in Huntsville, Alabama. Lockheed Martin Space in Denver built the InSight spacecraft, including its cruise stage and lander, and supported spacecraft operations for the mission.
      A number of European partners, including France’s Centre National d’Études Spatiales (CNES) and the German Aerospace Center (DLR), supported the InSight mission. CNES provided the Seismic Experiment for Interior Structure (SEIS) instrument to NASA, with the principal investigator at IPGP (Institut de Physique du Globe de Paris). Significant contributions for SEIS came from IPGP; the Max Planck Institute for Solar System Research (MPS) in Germany; the Swiss Federal Institute of Technology (ETH Zurich) in Switzerland; Imperial College London and Oxford University in the United Kingdom; and JPL. DLR provided the Heat Flow and Physical Properties Package (HP3) instrument, with significant contributions from the Space Research Center (CBK) of the Polish Academy of Sciences and Astronika in Poland. Spain’s Centro de Astrobiología (CAB) supplied the temperature and wind sensors.
      A division of Caltech in Pasadena, California, JPL manages the Mars Reconnaissance Orbiter Project for NASA’s Science Mission Directorate, Washington. The University of Arizona, in Tucson, operates HiRISE, which was built by BAE Systems in Boulder, Colorado. The Context Camera was built by, and is operated by, Malin Space Science Systems in San Diego. 
      For more about Insight, visit:

      https://science.nasa.gov/mission/insight/
      For more about MRO, visit:

      https://science.nasa.gov/mission/mars-reconnaissance-orbiter/
      News Media Contacts
      Andrew Good
      Jet Propulsion Laboratory, Pasadena, Calif.
      818-393-2433
      andrew.c.good@jpl.nasa.gov
      Karen Fox / Molly Wasser
      NASA Headquarters, Washington
      202-358-1600
      |karen.c.fox@nasa.gov / molly.l.wasser@nasa.gov
      2025-013
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      Last Updated Feb 03, 2025 Related Terms
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