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Chimello, L
Carreira, A.D
Camolesi, A.R
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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
Chaves, C
Quicaña, A.
Chimello, L
Hermes, M
Andreoli, A
Albuquerque, M
Figueiredo, G
Topics
Artificial Intelligence, Big Data, and Advanced Analytics in Agriculture
Digital Solutions for Soil Health, Water Quality, and Conservation Practices
Type
Oral
Poster
Year
2026
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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

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. 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