Jakob Wiest
Pronouns: He/Him
Research Mentor(s): Kimberlee Kearfott
Research Mentor School/College/Department: NERS/BME / Engineering
Program:
Authors: Jakob R Wiest, Joseph J Mascort, Caleb M Bush, Clay D Hudson, Jordan D Noey, Kimberlee J Kearfott
Session: Session 5: 2:40 pm – 3:30 pm
Poster: 2
Abstract
It is important to understand background radiation so that changes in it, due to intentional or unintentional events, are easy to detect and the significance of radiation levels is placed in proper perspective. With this in mind, several University of Michigan’s North Campus areas were mapped using two different detectors. First, standard Ludlum MicroR survey meters were modified with electronics and special software, called Counts.Pro, enabling them to capture Global Positioning System (GPS) data from a cellphone. In addition, an affordable prototype spectroscopic system based upon a sound card interfaced with a Raspberry Pi microcomputer was also deployed. Areas surveyed included the Gerstacker Grove and areas in and around the Cooley Laboratory. Data were output from the detectors in comma-separated value (CSV) files and uploaded using the open-source geographic interface system (GIS) software QGIS. Several issues arose in the visualization process such as data stacking in areas with more detailed surveying and inaccurate indoor GPS location data. However, by implementing data-smoothing MATLAB code, the CSV longitude-latitude data could be averaged to a resolution of ~ 1.1 square meters. Work is still underway to improve the MATLAB code for better resolution and solve issues relating to indoor location inaccuracy with the Counts.Pro data. Implementation of RadMap is still prospective, as experiments measuring its capabilities are ongoing. The culmination of these methods will provide clear and accurate measurements of the University of Michigan North Campus and a better understanding of radiation mapping for future, larger-scale deployment.
