Proceedings

Find matching any: Reset
DuPont, E.M
Sawyer, .E
Salvaggio, C
Lajunen, A
Delgadillo, C.A
Add filter to result:
Authors
Archer, J.K
Delgadillo, C.A
Shen, F
Hughes, E.W
Pethybridge, S.J
Salvaggio, C
van Aardt, J
Kikkert, J.R
DuPont, E.M
Kolar, P.R
Li, D
Miao, Y
Fernández, .G
Kitchen, N.R
Ransom, C.
Bean, G.M
Sawyer, .E
Camberato, J.J
Carter, .R
Ferguson, R.B
Franzen, D.W
Franzen, D.W
Franzen, D.W
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Shanahan, J.F
Ahrends, H.E
Lajunen, A
Thomas, L
Jakimow, B
Janz, A
Hostert, P
Lajunen, A
Lajunen, A
Hovio, H
Topics
Standards & Data Stewardship
Applications of Unmanned Aerial Systems
Robotics, Guidance and Automation
ISPA Community: Nitrogen
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Artificial Intelligence (AI) in Agriculture
Wireless Sensor Networks and Farm Connectivity
Type
Oral
Poster
Year
2016
2018
2022
2024
Home » Authors » Results

Authors

Filter results7 paper(s) found.

1. Key Data Ownership, Privacy and Protection Issues and Strategies for the International Precision Agriculture Industry

Precision agriculture companies seek to leverage technology to process greater volumes of data, greater varieties of data, and at a velocity unfathomable to most. The promises of boundless benefits are coupled with risks associated with data ownership, stewardship and privacy. This paper presents some risks related to the management of farm data, in general, as well as those unique to operating in the international arena.  Examples of U.S. and international laws related to data protection... J.K. Archer, C.A. Delgadillo, F. Shen

2. Snap Bean Flowering Detection from UAS Imaging Spectroscopy

Sclerotinia sclerotiorum (white mold) is a fungus that infects the flowers of snap beans and causes a reduction in the number of pods, and subsequent yields, due to premature pod abscission. Snap bean fields typically are treated with prophylactic fungicide applications to control white mold, once 10% of the plants have at least one flower. The holistic goal of this research is to develop spatially-explicit white mold risk models, based on inputs from remote sensing systems aboard unmanned... E.W. Hughes, S.J. Pethybridge, C. Salvaggio, J. Van aardt, J.R. Kikkert

3. Synchronized Windrow Intelligent Perception System (SWIPE)

The practice of bale production, in forage agriculture, involves various machines that include tractors, tedders, rakers, and balers. As part of the baling process, silage material is placed in windrows, linearly raked mounds, to drive over with a baler for easy collection into bales. Traditionally, a baler is an implement that is attached on the back of a tractor to generate bales of a specific shape. Forage agricultural equipment manufacturers have recently released an operator driven, self-propelled... E.M. Dupont, P.R. Kolar

4. Developing a Machine Learning and Proximal Sensing-based In-season Site-specific Nitrogen Management Strategy for Corn in the US Midwest

Effective in-season site-specific nitrogen (N) management strategies are urgently needed to ensure both food security and sustainable agricultural development. Different active canopy sensor-based precision N management strategies have been developed and evaluated in different parts of the world. Recent studies evaluating several sensor-based N recommendation algorithms across the US Midwest indicated that these locally developed algorithms generally did not perform well when used broadly across... D. Li, Y. Miao, .G. Fernández, N.R. Kitchen, C. . Ransom, G.M. Bean, .E. Sawyer, J.J. Camberato, .R. Carter, R.B. Ferguson, D.W. Franzen, D.W. Franzen, D.W. Franzen, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.F. Shanahan

5. Proximal Sensing of Penetration Resistance at a Permanent Grassland Site in Southern Finland

Proximal soil sensing allows for assessing soil spatial heterogeneity at a high spatial resolution. These data can be used for decision support on soil and crop agronomic management. Recent sensor systems are capable of simultaneously mapping several variables, such as soil electrical conductivity (EC), spectral reflectance, temperature, and water content, in real-time. In autumn 2021, we used a commercial soil scanner (Veris iScan+) to derive information on soil spatial variability for a permanent... H.E. Ahrends, A. Lajunen

6. Spectral Imaging Deep Learning Mapper for Precision Agriculture

With the growing variety of RGB cameras, spectral sensors, and platforms like field robots or unmanned aerial vehicles (UAV) in precision agriculture, there is a demand for straightforward utilization of collected field data. In recent years, deep learning has gained significant attention and delivered impressive results in the realm of computer vision tasks, such as semantic segmentation. These models have also found extensive applications in research related to precision agriculture and spectral... L. Thomas, B. Jakimow, A. Janz, P. Hostert, A. Lajunen

7. Affordable Telematics System for Recording and Monitoring Operational Data in Crop Farming

The aim of this research was to create an affordable telematics system for agricultural tractors for enhancing existing data logging capabilities. This system enables real-time transmission of operational data from the tractor's CAN bus to a server for storage, monitoring, and further analysis. By leveraging standardized communication protocols like ISO 11783 and J1939, operational data such as fuel consumption and engine load can be easily monitored. The system was built around a Raspberry... A. Lajunen, H. Hovio