JOURNAL ARTICLE

AI + ML for Forensic Scene Reconstruction: A Simulation-Based Study of Blood Spatter, Fingerprint, and Visual Evidence Mapping.

  • Published In: International Scientific Journal of Engineering & Management, 2025, v. 4, n. 10. P. 1 1 of 3

  • Database: Applied Science & Technology Source Ultimate 2 of 3

  • Authored By: Shaji, Vishnupriya; Waghole, Shweta Anil 3 of 3

Abstract

The article focuses on the development of an Artificial Intelligence (AI) and Machine Learning (ML)-based framework for forensic scene reconstruction, aiming to automate the creation of accurate 3D crime scene models from 2D images. Utilizing computer vision techniques such as photogrammetry and Structure-from-Motion (SfM), the system detects and tags forensic evidence including blood spatter, fingerprints, and weapons through deep learning models. The research proposes a user-friendly interface for law enforcement to interact with reconstructed scenes, enabling spatial and temporal hypothesis testing to improve investigative accuracy and reduce human error. Evaluation will compare the AI-assisted approach with traditional manual methods, highlighting potential applications in courtroom presentations and forensic training.

Additional Information

  • Source:International Scientific Journal of Engineering & Management. 2025/10, Vol. 4, Issue 10, p1
  • Document Type:Article
  • Subject Area:Science
  • Publication Date:2025
  • ISSN:25836129
  • DOI:10.55041/ISJEM05106
  • Accession Number:189119150
  • Copyright Statement:Copyright of International Scientific Journal of Engineering & Management is the property of International Scientific Journal of Engineering & Management and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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