PARS

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Ausgangspunkt

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PARS ist ein neues Forschungs- und Entwicklungsprojekt, das im Rahmen des CENTRIC-Projekts (ID: 22081/05.10.2022) bewilligt wurde, als Teil des „Operationellen Programms Wettbewerbsfähigkeit“: Zentrum für Wissenstransfer an Unternehmen im IKT-Bereich. Das Projekt wird in Zusammenarbeit mit einem Forschungsteam der Ștefan cel Mare Universität Suceava umgesetzt.

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7 Monate

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Zeitleiste

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dateTime
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120.000 €

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Budget

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coinEuro
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POC

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Förderrahmen

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sitemap
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Lösung

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Autonome Erkennungs- und Unterstützungsplattform

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lightbulbCog
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Einsatzmöglichkeiten

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Überwachung, Aufklärung, Militär/Verteidigung, Landwirtschaft, Rettungsdienste

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stackThree
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Herausforderung

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Echtzeitinformationen aus dem Einsatzgebiet in risikoreichen Situationen

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unlink
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Partnern

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Section Name
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Image of first reponders getting real-time information from PARS
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Die Gelegenheit

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Eines der größten Probleme, mit denen Ersthelfer in Hochrisikosituationen konfrontiert sind, ist die schnelle und sichere Beschaffung von Echtzeitinformationen aus dem Einsatzgebiet. Gleichzeitig ist die Menge der Daten, die aggregiert und gefiltert werden müssen, für einen Menschen nicht zu bewältigen. Das Risiko menschlicher Fehler ist hoch, kann jedoch durch die Übertragung der Makroentscheidungen und -kontrollen auf eine KI-gesteuerte Softwarelösung gemindert werden.

Drohnen wurden in der Vergangenheit für Aufklärungs- und Unterstützungsmissionen eingesetzt, jedoch meist fernbedient von menschlichen Operatoren. Dies führt zu Problemen hinsichtlich Skalierbarkeit und Synchronisation, insbesondere wenn eine große Anzahl von Einheiten im selben Szenario agiert. Aus diesem Grund löst die Entwicklung eines KI-gesteuerten Schwarms nicht nur diese Herausforderungen, sondern eröffnet auch neue Möglichkeiten zur Bewältigung von Hochrisikoeinsätzen.

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Hochwertige Komponenten

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PARS ist eine autonome Aufklärungs- und Unterstützungsplattform, die als Lösung konzipiert wurde, um öffentliche Behörden in kritischen Situationen zu unterstützen, in denen schnelle Reaktionszeiten sowie eine optimale Koordination von Ressourcen und Informationsflüssen erforderlich sind. Die vorgeschlagene Lösung ermöglicht durch ein aus einem Kommandozentrum und einem autonomen Drohnenschwarm bestehendes Software- und Hardware-Ökosystem die schnelle Identifizierung von Schwachstellen sowie die Generierung dynamischer, an die Lage angepasster Lösungen.

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Image of the PARS Project Autonomous Recognition and Support Platform Drone
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Unsere Beiträge zum Projekt
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VR-Anwendung

Type
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Ermöglicht die manuelle Steuerung von Drohnen über Peripheriegeräte wie Joysticks oder Tastaturen und die Schulung von Ersthelfern in Hochrisikoszenarien.

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Kommando- und Kontrollzentrum

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Schafft eine Brücke zwischen der Schwarm-KI und den Außendienstmitarbeitern, indem Befehle vom ML-Schwarm-Agenten verarbeitet und übertragen werden.

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KI-Modul

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Verwendet ein verstärktes Lernmodell, um eine Gruppe von Drohnen als Reaktion auf erkannte Gefahren oder Vorfälle zu steuern.

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AR Hardware

Type
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Erfasst und überträgt Echtzeitdaten von den Drohnen an die Bildverarbeitungskomponente und ermöglicht so die Interaktion mit dem Schwarm.

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Hochpräzise digitale Zwillinge

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Die Genauigkeit des Systems hängt von den 3D-Modellen der Drohnen und der Umgebung für das Training des KI-Schwarms ab.

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Synthetischer Datengenerator

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Erzeugt synthetische Bilder, die für das Training des ML-Algorithmus über das Untermodul zur Bilderkennung verwendet werden.

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Innovation durch modernste Technologien fördern

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Wir nutzen fortschrittliche Technologien, um robuste und effiziente Mobil- und Webanwendungen zu entwickeln, die eine erstklassige Leistung und plattformübergreifende Kompatibilität gewährleisten.

View Reference
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Type
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Bemerkenswerte Fortschritte

Texts

Das Bildverarbeitungsmodul ist vom ML Swarm Agent getrennt und ermöglicht das Training eines KI-Akteurs, um reale Objekte anhand synthetischer Bilder als Eingabe zu erkennen. Ein wichtiges Ergebnis dieses Ansatzes ist das Tool VisioSynthASSISTant, das Unreal Engine 5 nutzt, um Bilddaten mit konfigurierbaren Umgebungen, Domänen-Randomisierung und Distraktor-Generierung für das Training von Computervisionsmodellen zu generieren.

Image
Multiple monitors showing VisioSynthASSISTant tool
Label
Anwendbare Szenarien:
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Type
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Überwachung

Type
Text

Modernste Überwachungs- und Kontrollanwendungen.

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Type
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Aufklärung

Type
Text

Integration autonomer Drohnenschwärme in  Aufklärungsanwendungen.

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Verteidigung

Type
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Forschung und Entwicklung eines Prototyps, der militärische Zielfernrohre unterstützen würde.

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Spitzenforschung

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Wir empfehlen Ihnen, diese Artikel zu lesen, die unsere Kollegen in fachkollegial begutachteten Veröffentlichungen veröffentlicht haben und in denen Prozesse, Ideen und die verwendete Technologie detailliert beschrieben werden, wie zum Beispiel: Experimentelle Ergebnisse zur Generierung synthetischer Daten in Unreal Engine 5 für die Erkennung realer Objekte 2023, 17. Internationale Konferenz über die Konstruktion moderner elektrischer Systeme (EMES).

Entdecken Sie einen innovativen Durchbruch in der Welt der Algorithmen zur Objektdetektion (OD)! Unsere Forschung befasst sich mit einer bahnbrechenden Methode zur Erstellung erstklassiger synthetischer Trainingsdaten, die die Zukunft der OD-Technologie vorantreiben. Durch die Nutzung der Möglichkeiten der Photogrammetrie verwandeln wir reale Objekte nahtlos in präzise digitale 3D-Repliken  und das alles innerhalb von Unreal Engine 5 (UE5).

Images
Demo of object detection implementation
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Youtube URL
https://www.youtube.com/watch?v=Fi-71-D2lqA
Type
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Demo-Video

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Die Art und Weise, wie Simulationen eingesetzt werden, durch strategische Maßnahmen, die in verschiedenen Bereichen anwendbar sind, revolutionieren.

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Section Name
Inside Paragraphs
Block Reference
Contact
Promoted Image
PARS drone
Application Types
Main Activities
Customer/Partner Country
Year
2022
Background Color
#ebebeb
OG image
OG PARS
Order
4
Short Description

PARS unterstützt Behörden in kritischen Situationen, die schnelle Reaktionszeiten erfordern.

Show On Homepage
No
Main Industries
Company size
Company description

PARS ist ein neues Forschungs- und Entwicklungsprojekt, das im Rahmen des CENTRIC-Projekts bewilligt wurde, als Teil des „Operationellen Programms Wettbewerbsfähigkeit“: Zentrum für Wissenstransfer an Unternehmen im IKT-Bereich. Das Projekt wird in Zusammenarbeit mit einem Forschungsteam der Ștefan cel Mare Universität Suceava umgesetzt.

Intro Description

Autonome Erkennungs- & Unterstützungsplattform

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Card Industry
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Yes
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Project Overview Title
Eigenes Produkt
Is EU Project
Yes
Has all fields translated
Yes