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Proceedings Paper

Proposed tethered unmanned aerial system for the detection of pollution entering the Chesapeake Bay area
Author(s): J. Goodman; J. McKay; W. Evans; S. Andrew Gadsden
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Paper Abstract

This paper is based on a proposed unmanned aerial system platform that is to be outfitted with high-resolution sensors. The proposed system is to be tethered to a moveable ground station, which may be a research vessel or some form of ground vehicle (e.g., car, truck, or rover). The sensors include, at a minimum: camera, infrared sensor, thermal, normalized difference vegetation index (NDVI) camera, global positioning system (GPS), and a light-based radar (LIDAR). The purpose of this paper is to provide an overview of existing methods for pollution detection of failing septic systems, and to introduce the proposed system. Future work will look at the high-resolution data from the sensors and integrating the data through a process called information fusion. Typically, this process is done using the popular and well-published Kalman filter (or its nonlinear formulations, such as the extended Kalman filter). However, future work will look at using a new type of strategy based on variable structure estimation for the information fusion portion of the data processing. It is hypothesized that fusing data from the thermal and NDVI sensors will be more accurate and reliable for a multitude of applications, including the detection of pollution entering the Chesapeake Bay area.

Paper Details

Date Published: 17 May 2016
PDF: 7 pages
Proc. SPIE 9866, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping, 98660P (17 May 2016); doi: 10.1117/12.2223368
Show Author Affiliations
J. Goodman, Univ. of Maryland, Baltimore County (United States)
J. McKay, Maryland Dept. of the Environment (United States)
W. Evans, Maryland Dept. of the Environment (United States)
S. Andrew Gadsden, Univ. of Maryland, Baltimore County (United States)


Published in SPIE Proceedings Vol. 9866:
Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping
John Valasek; J. Alex Thomasson, Editor(s)

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