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Sisällön tarjoaa tinyML Foundation and TinyML Foundation. tinyML Foundation and TinyML Foundation tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.
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Revolutionizing Space Technology with Edge AI and Satellite Autonomy

1:01:39
 
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Manage episode 433140734 series 3574631
Sisällön tarjoaa tinyML Foundation and TinyML Foundation. tinyML Foundation and TinyML Foundation tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

Imagine a world where satellites can make real-time decisions without waiting for ground-based commands. Learn how edge AI is revolutionizing space technology with David Maloney from Ubotica, who brings unparalleled expertise from his time at Movidius and Intel. Uncover the transformative power of performing AI inference directly on satellites, and why traditional ground-based systems are no longer sufficient. We explore advanced imaging techniques like hyperspectral imaging, which can now detect forest fires or monitor environmental changes with unprecedented speed and accuracy.
Delve into the fascinating intersection of image compression and generative AI, and see how these technologies can overcome the challenges of power consumption and energy efficiency in space. Hear about real-world implementations such as the FISAT-1 satellite's cloud detection and removal capabilities and the impressive radiation tolerance of hardware tested at CERN's Large Hadron Collider. By examining the trade-offs and legacies of space technology, we reveal how cutting-edge AI applications are optimizing data transmission and processing.
Finally, we discuss the advanced applications of hyperspectral sensors and image pattern recognition in environmental monitoring and security. Learn how these technologies can assess vegetation health, evaluate soil nutrients, and even detect illegal activities. Discover the challenges of deploying sensors in the harsh conditions of space and the significance of early warning systems for space weather events. With insights into the European Space Agency's Vigil mission and real-time edge processing in space, we also cover the exciting potential of Tiny Train technology for on-board training and updates, ensuring that our satellites are smarter and more responsive than ever before.

Learn more about the tinyML Foundation - tinyml.org

  continue reading

Luvut

1. Edge AI in Space Applications (00:00:00)

2. AI Implementation in Space Applications (00:16:22)

3. Space AI Applications and Challenges (00:29:01)

4. Real-Time Edge Processing in Space (00:39:04)

5. Edge AI Implementation in Space Missions (00:49:46)

5 jakso

Artwork
iconJaa
 
Manage episode 433140734 series 3574631
Sisällön tarjoaa tinyML Foundation and TinyML Foundation. tinyML Foundation and TinyML Foundation tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

Imagine a world where satellites can make real-time decisions without waiting for ground-based commands. Learn how edge AI is revolutionizing space technology with David Maloney from Ubotica, who brings unparalleled expertise from his time at Movidius and Intel. Uncover the transformative power of performing AI inference directly on satellites, and why traditional ground-based systems are no longer sufficient. We explore advanced imaging techniques like hyperspectral imaging, which can now detect forest fires or monitor environmental changes with unprecedented speed and accuracy.
Delve into the fascinating intersection of image compression and generative AI, and see how these technologies can overcome the challenges of power consumption and energy efficiency in space. Hear about real-world implementations such as the FISAT-1 satellite's cloud detection and removal capabilities and the impressive radiation tolerance of hardware tested at CERN's Large Hadron Collider. By examining the trade-offs and legacies of space technology, we reveal how cutting-edge AI applications are optimizing data transmission and processing.
Finally, we discuss the advanced applications of hyperspectral sensors and image pattern recognition in environmental monitoring and security. Learn how these technologies can assess vegetation health, evaluate soil nutrients, and even detect illegal activities. Discover the challenges of deploying sensors in the harsh conditions of space and the significance of early warning systems for space weather events. With insights into the European Space Agency's Vigil mission and real-time edge processing in space, we also cover the exciting potential of Tiny Train technology for on-board training and updates, ensuring that our satellites are smarter and more responsive than ever before.

Learn more about the tinyML Foundation - tinyml.org

  continue reading

Luvut

1. Edge AI in Space Applications (00:00:00)

2. AI Implementation in Space Applications (00:16:22)

3. Space AI Applications and Challenges (00:29:01)

4. Real-Time Edge Processing in Space (00:39:04)

5. Edge AI Implementation in Space Missions (00:49:46)

5 jakso

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