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Lamparelli, R.A
Louis, J
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Authors
Pereira, F.R
Dos Reis, A.A
Freitas, R.G
Oliveira, S.R
Amaral, L.R
Figueiredo, G.K
Antunes, J.F
Lamparelli, R.A
Moro, E
Pereira, N.D
Magalhães, P.S
Pereira, F.R
Lima, J.P
Freitas, R.G
Dos Reis, A.A
Amaral, L.R
Figueiredo, G.K
Lamparelli, R.A
Pereira, J.C
Magalhães, P.S
Dhal, S
Louis, J
O'Sullivan, N
Gumero, J
Soetan, M
Kalafatis, S
Lusher, J
Mahanta, S
Topics
Big Data, Data Mining and Deep Learning
In-Season Nitrogen Management
Decision Support Systems
Type
Poster
Oral
Year
2022
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1. A Framework for Imputation of Missing Parts in UAV Orthomosaics Using Planetscope and Sentinel-2 Data

In recent years, the emergence of Unmanned Aerial Vehicles (UAV), also known as drones, with high spatial resolution, has broadened the application of remote sensing in agriculture. However, UAV images commonly have specific problems with missing areas due to drone flight restrictions. Data mining techniques for imputing missing data is an activity often demanded in several fields of science. In this context, this research used the same approach to predict missing parts on orthomosaics obtained... F.R. Pereira, A.A. Dos reis, R.G. Freitas, S.R. Oliveira, L.R. Amaral, G.K. Figueiredo, J.F. Antunes, R.A. Lamparelli, E. Moro, N.D. Pereira, P.S. Magalhães

2. Nitrogen Status Prediction on Pasture Fields Can Be Reached Using Visible Light UAV Data Combined with Sentinel-2 Imagery

Pasture fields under integrated crop-livestock system usually receive low or no nitrogen fertilization rates, since the expectation is that nitrogen demand will be provided by the soybean remaining straw cropped previously. However, keeping nitrogen at suitable levels in the entire field is the key to achieving sustainability in agricultural production systems. In this sense, remote sensing technologies play an essential role in nitrogen monitoring in pastures and crops. With the launch of the... F.R. Pereira, J.P. Lima, R.G. Freitas, A.A. Dos reis, L.R. Amaral, G.K. Figueiredo, R.A. Lamparelli, J.C. Pereira, P.S. Magalhães

3. An IoT-based Smart Real Time Sensing and Control of Heavy Metals to Ensure Optimal Growth of Plants in an Aquaponic Set-up

The concentration of heavy metals that needs to be maintained in aquaponic environments for habitable growth of plants has been a cause of concern for many decades now as it is not possible to eliminate them completely in a commercial set-up. Our goal is to design a cost-effective real-time smart sensing and actuation system in order to control the concentration of heavy metals in aquaponic solutions. Our solution consists of sensing the nutrient concentrations in the aquaponic solution, namely... S. Dhal, J. Louis, N. O'sullivan, J. Gumero, M. Soetan, S. Kalafatis, J. Lusher, S. Mahanta