Autonomous Monitoring of Large Scale Agricultural Plants through Unmanned Aerial Vehicles
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
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.
