CampusX: Empowering College Selection with 3D insights using machine Learning approach.

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2024 | Volume :02 | Issue : 02 | Page : 11-20
By
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Reena Kothari,

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Utkarsh Mishra,

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Siddhant Singh,

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Satya Prakash Mishra,

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Aditya Mishra,

  1. Assitant Professor, Department of Computer Science Engineering, Shree L. R. Tiwari College of Engineering, Mira Road East, Mira Bhayandar,, Maharashtra,, India
  2. Student,, Department of Computer Science Engineering, Shree L. R. Tiwari College of Engineering, Mira Road East, Mira Bhayandar,, Maharashtra,, India
  3. Student,, Department of Computer Science Engineering, Shree L. R. Tiwari College of Engineering, Mira Road East, Mira Bhayandar,, Maharashtra,, India
  4. Student,, Department of Computer Science Engineering, Shree L. R. Tiwari College of Engineering, Mira Road East, Mira Bhayandar,, Maharashtra,, India
  5. Student,, Department of Computer Science Engineering, Shree L. R. Tiwari College of Engineering, Mira Road East, Mira Bhayandar,, Maharashtra,, India

Abstract document.addEventListener(‘DOMContentLoaded’,function(){frmFrontForm.scrollToID(‘frm_container_abs_121607’);});Edit Abstract & Keyword

CampusX redefines college selection with dynamic 3D insights, empowering students to navigate campuses virtually. Utilizing cutting-edge machine learning and visualization techniques, it transforms static data into interactive experiences. Personalized comparisons enable informed decision-making, while predictive analytics forecast future campus developments. With a user-centric interface and robust privacy protocols, CampusX ensures seamless exploration and data security. This innovative platform bridges the gap between prospective students and their ideal educational environments, revolutionizing the higher education landscape. One of the most important choices a student will ever make in the fast-paced world of today is which institution to attend. The decision-making process might be daunting because there are thousands of universities across the globe, each with unique facilities, curricula, and cultures. Presenting CampusX, a ground-breaking tool that uses immersive 3D and machine intelligence to enable students and their families to make better college decisions. Students may more easily visualise and compare universities using CampusX’s comprehensive overview, which blends data-driven insights with interactive 3D models of campuses. By incorporating a machine learning technique that examines a wide range of variables, from academic performance and campus amenities to social life and job placement statistics, CampusX aims to overcome the challenges associated with college selection. By using 3D visualisations, it provides an immersive experience that makes campuses come to life, going beyond still photos or written descriptions. Students may evaluate their compatibility with potential schools more easily thanks to this comprehensive approach, which gives them a better understanding of the physical and cultural surroundings of each institution.

Keywords: 3D insights, machine learning, visualization, personalized comparisons, predictive analytics, data security, exploration, LiDAR scans, Blender.

[This article belongs to International Journal of Optical Innovations & Research (ijoir)]

How to cite this article:
Reena Kothari, Utkarsh Mishra, Siddhant Singh, Satya Prakash Mishra, Aditya Mishra. CampusX: Empowering College Selection with 3D insights using machine Learning approach.. International Journal of Optical Innovations & Research. 2024; 02(02):11-20.
How to cite this URL:
Reena Kothari, Utkarsh Mishra, Siddhant Singh, Satya Prakash Mishra, Aditya Mishra. CampusX: Empowering College Selection with 3D insights using machine Learning approach.. International Journal of Optical Innovations & Research. 2024; 02(02):11-20. Available from: https://journals.stmjournals.com/ijoir/article=2024/view=0

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Regular Issue Subscription Review Article
Volume 02
Issue 02
Received 29/07/2024
Accepted 13/11/2024
Published 26/11/2024