Title

Autonomous Monitoring of Large Scale Agricultural Plants through Unmanned Aerial Vehicles

Presenter Information

Ken Goss

Department

Computer Science

Major

Computer Science; Computer Engineering

Research Advisor

Silvestri, Simone

Advisor's Department

Computer Science

Funding Source

National Science Foundation (U.S.); Missouri Transect

Abstract

The importance of understanding how crops are impacted by climate change and drought cannot be overstated as the globe continues in both population growth and industrialization. This project seeks to use UAVs in an innovative framework to improve both the efficiency and efficacy of a wide array of agricultural pursuits. For the first time, a framework to optimize the tradeoff between the monitoring accuracy provided by a UAV network, and its cost, will be developed and proposed. The primary focus of this research is in the development of models to reliably and authentically represent a UAV swarm, from power, to coordination, and overall swarm performance in a wide array of sensing applications.

Biography

Ken is currently a senior in both Computer Science and Computer Engineering. He is an Undergraduate Research Assistant in the Networking Laboratory. He is the founder and current President of STARS (S&T Astronomical Research Society). He will graduate May 2017 and pursue graduate studies thereafter.

Research Category

Research Proposals

Presentation Type

Poster Presentation

Document Type

Poster

Location

Upper Atrium/Hallway

Presentation Date

11 Apr 2016, 9:00 am - 11:45 am

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Apr 11th, 9:00 AM Apr 11th, 11:45 AM

Autonomous Monitoring of Large Scale Agricultural Plants through Unmanned Aerial Vehicles

Upper Atrium/Hallway

The importance of understanding how crops are impacted by climate change and drought cannot be overstated as the globe continues in both population growth and industrialization. This project seeks to use UAVs in an innovative framework to improve both the efficiency and efficacy of a wide array of agricultural pursuits. For the first time, a framework to optimize the tradeoff between the monitoring accuracy provided by a UAV network, and its cost, will be developed and proposed. The primary focus of this research is in the development of models to reliably and authentically represent a UAV swarm, from power, to coordination, and overall swarm performance in a wide array of sensing applications.