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  Published Paper Details:

  Paper Title

SPACE DEBRIS REMOVAL USING AI AND DEEP LEARNING

  Authors

  Devesh Shailesh Auti,  Anushree Ajit Kale,  Atharva Vijay Deo,  Shivam Shendre

  Keywords

- Space Debris, AI Driven Frame work, Data Fusion Algorithms, Satellite-Based Sensors, Autonomous Decision-Making; space Debris Remediation.

  Abstract


The term "space debris" refers to spacecraft not removed from orbit at the end of their service life, upper stages in the geostationary orbit region, as well as to the fragments of spacecraft and upper stages formed as a result of deliberate or accidental collision of spacecraft and upper stages with each other or with natural space debris. The problem of removing space debris from outer space is a global problem. Many countries are realizing projects on space debris cataloging, various technical means are being studied for space debris removal into graveyard orbits with parameters agreed upon by the international community. Various countries conducting space exploration have adopted special standards and guidelines for preventing the space debris formation The exponential growth of space debris poses a significant threat to future space missions and the sustainability of space exploration. This project focuses on the development and implementation of an innovative AI-driven framework for efficient and autonomous space debris removal. Leveraging advanced machine learning and computer vision techniques, the proposed system autonomously identifies, tracks, and categorizes space debris, enabling targeted and precise removal strategies. The framework integrates real-time data analysis, predictive modeling, and robotic control to orchestrate coordinated debris collection and disposal operations. Through a combination of satellite-based sensors, data fusion algorithms, and autonomous decision-making, the AI system demonstrates remarkable adaptability and scalability, ensuring the continual mitigation of space debris risks. Furthermore, the project emphasizes the importance of international collaboration and regulatory frameworks for the adoption of standardized practices in sustainable space debris management. This research represents a significant step toward the establishment of a safer and more sustainable space environment, fostering the continued progress of humanity's exploration and utilization of outer space.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT24A3321

  Paper ID - 254538

  Page Number(s) - l187-l200

  Pubished in - Volume 12 | Issue 3 | March 2024

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Devesh Shailesh Auti,  Anushree Ajit Kale,  Atharva Vijay Deo,  Shivam Shendre,   "SPACE DEBRIS REMOVAL USING AI AND DEEP LEARNING", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 3, pp.l187-l200, March 2024, Available at :http://www.ijcrt.org/papers/IJCRT24A3321.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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