Proceedings :: International Society of Precision Agriculture

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Chimello, L

Carreira, A.D

Camolesi, A.R

C. R. Seruffo, M

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Authors

Zonfrilli, L.E

Camolesi, A.R

Canata, T

de Souza Silva, R

Zonfrilli, L.E

Andrade da Silva, A

Pereira da Silva, R.P

Carreira, A.D

H. S. Sousa , F

S. Maciel, T

M. dos Reis, M

Santos, R.D

M. Santos, A

M. S. de Souza, A

K. F. Veras, A

G. Ferreira, G

P. M. Nunes, M

C. R. Seruffo, M

C. C. Daher, L

G.M. Silva, A

Chaves, C

Quicaña, A.

Chimello, L

Hermes, M

Andreoli, A

Albuquerque, M

Figueiredo, G

Topics

Artificial Intelligence, Big Data, and Advanced Analytics in Agriculture

UAV-Based Scouting, Imaging, and Targeted Applications

Digital Solutions for Soil Health, Water Quality, and Conservation Practices

Type

Oral

Poster

Year

2026

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Filter results4 paper(s) found.
1. Impact of Telemetry Data Preprocessing on the Accuracy of Fuel Consumption Predictive Models in Heavy-Duty Truck Transport of Sugarcane Stalks Fuel consumption efficiency in biomass transport is a determinant factor for the sustainability of agribusiness. However, agricultural machinery telemetry data present intrinsic challenges, such as onboard sensor noise and inconsistencies. This study aimed to demonstrate that meticulous data preprocessing is more relevant than algorithmic complexity in achieving high-performance predictive models. The raw dataset contained 43,112 trips by trucks responsible for transporting sugarcane stalks from... L.E. Zonfrilli, A.R. Camolesi, T. Canata Download paper
2. Alternative Method for Measuring Fuel Consumption in Agricultural Machinery Using Arduino and Flow Sensors Monitoring fuel consumption in agricultural machinery is a strategic component of precision agriculture, as it is directly associated with operational efficiency, cost reduction, and the mitigation of CO₂ emissions. Despite technological advances in agricultural tractors, most machines, including recent models, do not feature dedicated sensors for direct fuel flow measurement, relying instead on visual fuel level indicators or estimates based on engine parameters, which limits the accuracy of... R. De Souza Silva, L.E. Zonfrilli, A. Andrade Da Silva, R.P. Silva, A.D. Carreira
3. Development and Field Validation of a Scalable UAV-Based Framework for Automated Cattle Counting and Herd Management in Extensive Production Systems Brazil holds the largest commercial cattle herd in the world, with more than 230 million head, representing approximately 20% of the global population. In this context, technologies capable of optimizing herd monitoring are strategic for increasing production efficiency, reducing operational costs, and promoting sustainability in livestock systems. Among these technologies, computer vision–based systems have emerged as a promising alternative for automated animal detection and counting in... F. H. S. Sousa , T. S. Maciel, M. M. Dos Reis, R.D. Santos, A. M. Santos, A. M. S. De Souza, A. K. F. Veras, G. G. Ferreira, M. P. M. Nunes, M. C. R. Seruffo, L. C. C. Daher, A. G.m. Silva
4. Use of Digital Permeameter for the Functional Characterization of Geoenvironments Characterizing agricultural geoenvironments with precision is inherently a complex task. Historically, this process has relied on quasi-static edaphic attributes, such as soil texture and apparent electrical conductivity. However, a critical problem exists, as these parameters exhibit low sensitivity to ephemeral structural changes resulting from soil management systems. Texture conditions the productive potential, yet it fails to reflect modifications in pore geometry induced by mechanical pressures... C. Chaves, A. . Quicaña, L. Chimello, M. Hermes, A. Andreoli, M. Albuquerque, G. Figueiredo, M. Hermes

Filter results4 paper(s) found.

1. Impact of Telemetry Data Preprocessing on the Accuracy of Fuel Consumption Predictive Models in Heavy-Duty Truck Transport of Sugarcane Stalks

Fuel consumption efficiency in biomass transport is a determinant factor for the sustainability of agribusiness. However, agricultural machinery telemetry data present intrinsic challenges, such as onboard sensor noise and inconsistencies. This study aimed to demonstrate that meticulous data preprocessing is more relevant than algorithmic complexity in achieving high-performance predictive models. The raw dataset contained 43,112 trips by trucks responsible for transporting sugarcane stalks from... L.E. Zonfrilli, A.R. Camolesi, T. Canata

Download paper

2. Alternative Method for Measuring Fuel Consumption in Agricultural Machinery Using Arduino and Flow Sensors

Monitoring fuel consumption in agricultural machinery is a strategic component of precision agriculture, as it is directly associated with operational efficiency, cost reduction, and the mitigation of CO₂ emissions. Despite technological advances in agricultural tractors, most machines, including recent models, do not feature dedicated sensors for direct fuel flow measurement, relying instead on visual fuel level indicators or estimates based on engine parameters, which limits the accuracy of... R. De Souza Silva, L.E. Zonfrilli, A. Andrade Da Silva, R.P. Silva, A.D. Carreira

3. Development and Field Validation of a Scalable UAV-Based Framework for Automated Cattle Counting and Herd Management in Extensive Production Systems

Brazil holds the largest commercial cattle herd in the world, with more than 230 million head, representing approximately 20% of the global population. In this context, technologies capable of optimizing herd monitoring are strategic for increasing production efficiency, reducing operational costs, and promoting sustainability in livestock systems. Among these technologies, computer vision–based systems have emerged as a promising alternative for automated animal detection and counting in... F. H. S. Sousa , T. S. Maciel, M. M. Dos Reis, R.D. Santos, A. M. Santos, A. M. S. De Souza, A. K. F. Veras, G. G. Ferreira, M. P. M. Nunes, M. C. R. Seruffo, L. C. C. Daher, A. G.m. Silva

4. Use of Digital Permeameter for the Functional Characterization of Geoenvironments

Characterizing agricultural geoenvironments with precision is inherently a complex task. Historically, this process has relied on quasi-static edaphic attributes, such as soil texture and apparent electrical conductivity. However, a critical problem exists, as these parameters exhibit low sensitivity to ephemeral structural changes resulting from soil management systems. Texture conditions the productive potential, yet it fails to reflect modifications in pore geometry induced by mechanical pressures... C. Chaves, A. . Quicaña, L. Chimello, M. Hermes, A. Andreoli, M. Albuquerque, G. Figueiredo, M. Hermes