Singh, Aditya

0000-0001-5559-9151

Applications of Unmanned Aerial Systems in Agricultural Operation Management: Part III: Best Practices for Efficient Aerial Surveying

Aditya Singh and James Fletcher

Applications of Unmanned Aerial Systems in Agricultural Operation Management: Part I: Overview

James Fletcher and Aditya Singh

Applications of Unmanned Aerial Systems in Agricultural Operation Management: Part II: Platforms and Payloads

Aditya Singh and James Fletcher

Mission Planner: An Open-Source Alternative to Commercial Flight Planning Software for Unmanned Aerial Systems

Jesse Chintanadilok, Sahaj Patel, Yilin Zhuang, and Aditya Singh

All UASs need periodic maintenance and repair. These changes have raised questions among Extension agents regarding which UASs to purchase and use, and how these changes affect their operations going forward. Free and open-source (FOSS) options may be a very useful alternative to commercial-off-the-shelf (COTS) UASs. Written by Jesse Chintanadilok, Sahaj Patel, Yilin Zhuang, and Aditya Singh, and published by the UF/IFAS Department of Agricultural and Biological Engineering, August 2022.

WebODM: An Open-Source Alternative to Commercial Image Stitching Software for Uncrewed Aerial Systems

Sahaj Patel, Jesse Chintanadilok, Brittany Hall-Scharf, Yilin Zhuang, Joseph Strickland, and Aditya Singh

This publication aims to help UAS operators become familiar with advanced data processing tools integrated into the WebODM FOSS. The central aim of this publication is to underscore the process and sequence involved in producing data and outcomes by acquainting users with the fundamental features of WebODM. Written by Sahaj Patel, Jesse Chintanadilok, Brittany Hall-Scharf, Yilin Zhuang, Joseph Strickland, and Aditya Singh, and published by the UF/IFAS Department of Agricultural and Biological Engineering, February 2024.

Artificial Intelligence (AI) For Crop Yield Forecasting

Clyde Fraisse, Yiannis Ampatzidis, Sandra Guzmán, Wonsuk Lee, Christopher Martinez, Sanjay Shukla, Aditya Singh, and Ziwen Yu

This publication aims to introduce readers to recent crop yield forecasting approaches based on artificial intelligence (AI) and to provide examples of how AI can potentially improve yield forecasting at the field and regional levels. Written by Clyde Fraisse, Yiannis Ampatzidis, Sandra Guzmán, Wonsuk Lee, Christopher Martinez, Sanjay Shukla, Aditya Singh, and Ziwen Yu, and published by the UF/IFAS Department of Agricultural and Biological Engineering, April 2022.