Enhancing Crime Scene Analysis: The Impact of AI Technologies on Evidence Processing

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Author(s): Saquib Ahmed (Sharda University, India), Mohd. Faheem Khan (Galgotias University, India), Bhupinder Singh (Sharda University, India), Nituja Singh (Symbiosis Law School, Symbiosis International University, India)and Bhumika Sharma (Sharda University, India)
Copyright: 2025
Pages: 22
Source title: Forensic Intelligence and Deep Learning Solutions in Crime Investigation
Source Author(s)/Editor(s): Christian Kaunert (Dublin City University, Ireland), Anjali Raghav (Sharda University, India), Kamalesh Ravesangar (Tunku Abdul Rahman University of Management and Technology, Malaysia)and Bhupinder Singh (Sharda University, India)
DOI: 10.4018/979-8-3693-9405-2.ch004

Keywords: Criminal Science and Forensics / Digital Crime & Forensics / Information Science Reference / Security & Forensics

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Abstract

Conventional approaches often find it challenging to adapt to the growing complexity and data volume in crime scene analysis. The advent of artificial intelligence technologies, such as machine learning, computer vision, and natural language processing, is transforming the processing of evidence by improving efficiency, precision, and scalability. AI algorithms can swiftly analyse extensive datasets, uncovering patterns and relationships that may be overlooked by human investigators. For example, AI-driven tools enable the rapid examination of digital evidence and DNA samples, significantly alleviating backlogs in forensic laboratories. This chapter also explores the application of AI in reconstructing crime scenes through sophisticated 3D modelling techniques, which offer investigators a detailed perspective of events and enhance courtroom presentations. Additionally, the chapter addresses ethical issues related to the use of AI in forensic science, including privacy concerns, algorithmic bias, and the importance of human oversight.

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