Proceedings
Authors
| Filter results2 paper(s) found. |
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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 StalksFuel 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. Satellite Embedding-Based Corn Yield Prediction Using AutoML and Explainable AIAccurate, spatially explicit yield mapping underpins many precision agriculture decisions (e.g., variable-rate inputs and zone management), yet reliable yield monitor data are not always available and can be difficult to standardize across operations. Satellite-based yield models are often built from hand-crafted vegetation indices or phenology metrics, which may limit transferability across fields and years. Here, we evaluated a pixel-level corn yield prediction workflow that uses Satellite Embedding... V.S. Silva, E.S. Silva, D.O. Silva, M.F. Oliveira, A.C. Tavares, R.P. Negrini, L.A. Mendes |