Is this project an undergraduate, graduate, or faculty project?
Undergraduate
Project Type
individual
Campus
Daytona Beach
Authors' Class Standing
Kaleb Nails, Senior
Lead Presenter's Name
Kaleb Nails
Lead Presenter's College
DB College of Engineering
Faculty Mentor Name
Marc Compere
Abstract
This paper presents design and test results from a multi-modal research effort to understand airborne Particulate Matter (PM) distribution. The multi-modal nature includes (a) 1D stationary ground-based measurements, (b) 2D mobile ground-based measurements, and (c) 3D airborne measurements using small Uncrewed Aircraft (sUA). The goal is to improve understanding of particulate matter distribution by extending PM measurements to all three spatial dimensions. Reference Monitors with high accuracy PM measurements are typically heavier and larger than small uncrewed aircraft can carry for extended sampling periods. This drives the use of small, lightweight, low cost, and low power PM sensors. The results indicate a positive future for 3D atmospheric collection. This paper presents useful PM data and focuses on low-cost, multi-sensor, multi-modal sampling. The data collection system design and conclusions are presented with lessons learned for others to advance their knowledge when planning future experiments.
Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?
Yes, Spark Grant
Multi-Modal Atmospheric Data Collection using Low-Cost Particulate Matter Sensors
This paper presents design and test results from a multi-modal research effort to understand airborne Particulate Matter (PM) distribution. The multi-modal nature includes (a) 1D stationary ground-based measurements, (b) 2D mobile ground-based measurements, and (c) 3D airborne measurements using small Uncrewed Aircraft (sUA). The goal is to improve understanding of particulate matter distribution by extending PM measurements to all three spatial dimensions. Reference Monitors with high accuracy PM measurements are typically heavier and larger than small uncrewed aircraft can carry for extended sampling periods. This drives the use of small, lightweight, low cost, and low power PM sensors. The results indicate a positive future for 3D atmospheric collection. This paper presents useful PM data and focuses on low-cost, multi-sensor, multi-modal sampling. The data collection system design and conclusions are presented with lessons learned for others to advance their knowledge when planning future experiments.