Albeedan, M (2024) Crime Scene Investigations through Augmented Reality. Doctoral thesis, Liverpool John Moores University.

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Abstract

Traditional forensic investigation training faces challenges such as time-intensive processes, geographical limitations, accessibility barriers, and contamination risks to crime scenes. This study introduces a two-fold approach to modernize training while addressing these challenges. An extensive literature review on 3D scanning for crime scene reconstruction and an examination of Extended Reality (XR) technologies, including Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR). To understand current solutions, a hybrid theoretical framework integrates Task-technology Fit (TTF), Technology Acceptance Model (TAM), and AR headset features like immersion, interactivity, and mobility. This framework is rooted in theories from human-computer interaction, cognitive psychology, and education. The primary objective is to investigate junior investigators' behavioral intentions regarding AR headset adoption. Empirical validation is achieved through a questionnaire administered to 160 police academy students, analyzed with Partial Least Squares-Structural Equation Modeling (PLS-SEM). Beyond theory, this research conducts crime scene reconstructions using 3D scanning technology. An AR-based training system is designed, developed, and deployed, tailored for crime scene investigation training, showcasing the viability and efficiency of AR technology in this realm. System evaluation comprises quantitative feedback from 160 students and qualitative interviews with 11 experts. The findings reveal the diverse impacts of TTF and Individual Technology Fit on the perceived utility and ease of use of AR applications in investigative training. The results consistently reflect positive tendencies toward usability, user interaction, and overall satisfaction with the AR-based system, positioning it as a promising tool for future crime scene education and investigative practices. By bridging theoretical concepts with practical implementations, this work showcases the viability and effectiveness of HoloLens 2 in this domain. While presenting promising advancements, this research also underscores the importance of acknowledging the current limitations of AR technology and suggests valuable avenues for future exploration and refinement.

Item Type:	Thesis (Doctoral)
Uncontrolled Keywords:	Crime investigation; Crime scene investigation; 3D reconstruction; 3D scanning; Augmented reality; crime scene investigation training; VR Training; Technology acceptance model
Subjects:	H Social Sciences > H Social Sciences (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General)
Divisions:	Computer Science & Mathematics
SWORD Depositor:	A Symplectic
Date Deposited:	26 Jan 2024 10:30
Last Modified:	26 Jan 2024 10:30
Supervisors:	Kolivand, H, Khan, W, Hammady, R and Saba, T
URI:	https://researchonline.ljmu.ac.uk/id/eprint/22442

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