Description of original award (Fiscal Year 2018, $91,416)
Problem Statement: The purpose of this project is to evaluate remote sensing technologies for reconstructing crime scenes. Conventional methods, such as photography, charting, and using a terrestrial laser scanner (TLS), increase the possibility of contamination because they require a physical presence in the scene. If equipped with a clear understanding of the technologys benefits and limitations, law enforcement could use aerial remote sensing with sUAS to potentially remedy this shortfall by maintaining crime scene reconstruction integrity without needing to enter the scene. Partnerships: Kansas State University's Applied Aviation Research Center (AARC) specializes in the operationalization of sUAS technology. By partnering with Kansas Bureau of Investigation's (KBI) nationally recognized experts, the research team will explore the relevance of this disruptive technology to forensics sciences.
Research and Design Methods: This is a six-month research project where three controlled mock crime scenes representing different environments will be reconstructed with three remote sensing methods. Terrestrial laser scanning will serve as the conventional method whereas, structure from motion (SfM) and light detection and ranging (LIDAR) will serve as the two sUAS remote sensing methods. Each of these methods will produce point cloud reconstructions of the crime scenes and this data will be compared using quantitative and qualitative metrics. Analysis: The analysis of the point clouds will incorporate quantitative and qualitative metrics. Quantitative metrics include measurement error, point cloud density, time to collect data, and cost. Measurement error is the highest weighted metric and will be evaluated by comparing true known measurements throughout the crime scene to estimated measurements within the model. Qualitative metrics include ease of data acquisition, environmental effects, and completeness of the model. All metrics will be incorporated into a final score to show which remote sensing method performs best in certain environments and use-cases.
Resubmission: This proposal is a resubmission of the application 2017-90639-KS-DN. Highlights of the revision include focusing on only one phase of the project, following an aircraft-agnostic approach, rigorous sensor comparison, and collaboration with law enforcement entities already incorporating the use of sUAS.
This project contains a research and/or development component, as defined in applicable law, and complies with Part 200 Uniform Requirements - 2 CFR 200.210(a)(14).