Fatemah M h a m Sheshtar

Ms. Fatemah M h a m Sheshtar


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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22 January 2025 in Applied Sciences
Verified
Journal Article
Open access
PDF file
FSFatemah M h a m Sheshtar
Fatemah M h a m Sheshtar
WAWajd Muhammad Alhatlani
Wajd Muhammad Alhatlani
MMMichael John Moulden
Michael John Moulden
JKJong Hyuk Kim
Jong Hyuk Kim
Accurate and fast 3D mapping of crime scenes is crucial in law enforcement, and first responders often need to document scenes in detail under challenging conditions and within a limited time. Traditional methods often fail to capture the details required to understand these scenes comprehensively. This study investigates the effectiveness of recent mobile phone-based mapping technologies equipped with a LiDAR (Light Detection and Ranging) sensor. The performance of LiDAR and pure photogrammetry is evaluated under different illumination (day and night) and scanning conditions (slow and fast scanning) in a mock-up crime scene. The results reveal that the mapping using an iPhone LIDAR in daylight conditions with 5 min of fast scanning shows the best results, yielding 0.1084 m of error. Also, the cloud-to-cloud distance showed that 90% of the point clouds exhibited under 0.1224 m of error, demonstrating the utility of these tools for rapid and portable scanning in crime scenes.

15 November 2024 in Preprints.org
Verified
Preprint
Open access
PDF file
FSFatemah M h a m Sheshtar
Fatemah M h a m Sheshtar
WAWajd Muhammad Alhatlani
Wajd Muhammad Alhatlani
MMMichael John Moulden
Michael John Moulden
JKJong Hyuk Kim
Jong Hyuk Kim
Accurate and fast 3D mapping of crime scenes is crucial in law enforcement, and first responders often need to document the scenes in detail under challenging conditions and within a limited time. Traditional methods often fail to capture the details to understand the scenes comprehensively. This study investigates the effectiveness of recent mobile phone-based mapping technologies equipped with a LiDAR (Light Detection and Ranging) sensor. The performance of LiDAR and pure photogrammetry is evaluated under different illumination (day and night) and scanning conditions (slow and fast scanning) in a mock-up crime scene. The results reveal that the mapping using an iPhone LIDAR in day-light conditions with 5 minutes of fast scanning shows the best results, yielding 0.1084 meters of error. Also, the cloud-to-cloud distance showed that 90% of the point clouds exhibited under 0.1224 meters of error, demonstrating the utility of these tools for rapid and portable scanning in crime scenes.