Proceedings
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| Filter results6 paper(s) found. |
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1. Development of a Sensing Device for Detecting Defoliation in SoybeanEstimating defoliation by insects in an agricultural field, specifically soybean, is performed by manually removing multiple leaf samples, visually inspecting the leaves for feeding, and assigning a value representing a “best guess” at the level of leaf material missing. These estimates can require considerable time and are subjective. The goal of this study was to design a low-cost system containing light sensors and a microcontroller that could remotely record and report long-term... P. Astillo, J. Maja, J. Greene |
2. High Resolution Vegetation Mapping with a Novel Compact Hyperspectral Camera SystemThe COSI-system is a novel compact hyperspectral imaging solution designed for small remotely piloted aircraft systems (RPAS). It is designed to supply accurate action and information maps related to the crop status and health for precision agricultural applications. The COSI-Cam makes use of a thin film hyperspectral filter technology which is deposited onto an image sensor chip resulting in a compact and lightweight instrument design. This paper reports on the agricultural monitoring... B. Delauré, P. Baeck, J. Blommaert, S. Delalieux, S. Livens, A. Sima, M. Boonen, J. Goffart, G. Jacquemin, D. Nuyttens |
3. A Comparative Study of Field-Wide Estimation of Soil Moisture Using Compressive SensingIn precision agriculture, monitoring of soil moisture plays an essential role in correct decision making. In practice, regular mesh installation, or large random deployment of moisture sensors over a large field is not possible due to cost and maintenance prohibitions. Consequently, direct measurement of moisture is possible at only a few points in the field. A value for the moisture may then be estimated for the remaining areas using a variety of algorithms. It is shown that although... H. Pourshamsaei, A. Nobakhti |
4. Optimal Sensor Placement for Field-Wide Estimation of Soil MoistureSoil moisture is one of the most important parameters in precision agriculture. While techniques such as remote sensing seems appropriate for moisture monitoring over large areas, they generally do not offer sufficiently fine resolution for precision work, and there are time restrictions on when the data is available. Moreover, while it is possible to get high resolution-on demand data, but the costs are often prohibitive for most developing countries. Direct ground level measurement... H. Pourshamsaei, A. Nobakhti |
5. Design of an Autonomous Ag Platform Capable of Field Scale Data Collection in Support of Artificial IntelligenceThe Pivot+ Array is intended to serve as an innovative, multi-user research platform dedicated to the autonomous monitoring, analysis, and manipulation of crops and inputs at the plant scale, covering extensive areas. It will effectively address many constraints that have historically limited large-scale agricultural sensor and robotic research. This achievement will be made possible by augmenting the well-established center pivot technology, known for its autonomy, with robust power infrastructure,... S. Jha, J. Krogmeier, D. Buckmaster, D.J. Love, R.H. Grant, M. Crawford, C. Brinton, C. Wang, D. Cappelleri, A. Balmos |
6. Spectral Imaging Deep Learning Mapper for Precision AgricultureWith 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 |