Proceedings :: International Society of Precision Agriculture

Proceedings

Find matching any: Reset

Jimenez Lopez, F.R

Otoboni, C.E

» Add more authors

Add filter to result:

Authors

Jimenez Lopez, F.R

Jimenez, A

Ruge Ruge, I.A

Garcia Ramirez, D.Y

Jimenez Lopez, F.R

Jimenez, A

Garcia Ramirez, D.Y

Rolon, R

Fischer, H

Otoboni, C.E

Luvizotto, C.K

de Almeida, M.C

Sanches , J

Fischer, H

de Almeida, M.C

Luvizzoto, C.K

Otoboni, C.E

Topics

Agricultural Robotics, Automation, and Mechanization

Precision Crop Protection, Pest, and Plant Health

Site-Specific Nutrient, Lime and Seed Management

Type

Oral

Poster

Year

2026

Home » Authors » Results

Authors

Filter results4 paper(s) found.
1. Hybrid Fuzzy–pid Control for Variable-rate Center Pivot Irrigation: an Automation-driven Approach to Precision Water Management Precision agriculture increasingly relies on advanced automation and intelligent control strategies to address the spatial and temporal variability of crop water requirements while minimizing resource consumption. Center pivot irrigation systems are widely deployed in large-scale farming operations; however, their conventional control architectures are typically based on fixed schedules or linear feedback laws, which are insufficient to handle the nonlinear dynamics, uncertainties, and disturbances... F.R. Jimenez Lopez, A. Jimenez, I.A. Ruge Ruge, D.Y. Garcia Ramirez Download paper
2. Deep Learning-based Anomaly Detection System for Rice Crop Health Monitoring Global food security relies heavily on the stable production of rice (Oryza sativa L.), yet cultivation remains vulnerable to various phytosanitary anomalies, including foliar diseases like Pyricularia and Rhynchosporium, scald, and abiotic stressors such as herbicide damage. Traditional agronomic management relies on visual scouting, which is inherently subjective, labor-intensive, and often leads to delayed interventions. This study proposes an automated, high-throughput solution for real-time... F.R. Jimenez Lopez, A. Jimenez, D.Y. Garcia Ramirez Download paper
3. A Hardware Classification Matrix for Precision Agriculture: Structuring an On-Farm Living Lab in Brazilian Citrus and Sugarcane Systems The consolidation of Precision Agriculture (PA) in Brazilian fields depends fundamentally on the physical infrastructure deployed on-farm, including sensors, actuators, embedded controllers, and implements. Although citrus and sugarcane represent pillars of São Paulo's agribusiness, the sector still lacks a systematized inventory that catalogues and classifies PA hardware effectively adopted across different producer profiles. Integrated into the Smart B100 Advanced Research Center... R. Rolon, H. Fischer, C.E. Otoboni, C.K. Luvizotto, M.C. De Almeida
4. Systematic Multi-criteria Assessment of Soil Analysis Technologies for an Agricultural Living Lab: Readiness Levels and Field Applicability for Citrus and Sugarcane Production Precision Agriculture (PA) fundamentally depends on accurate and timely edaphic diagnostics for site-specific decision-making. Within the scope of the Smart B100 Advanced Research Center (CCD-SB100/IAC), funded by FAPESP, an agricultural Living Lab is being structured. While the project's initial focus includes citrus and sugarcane in São Paulo State, the foundational soil sensing technologies evaluated are crop-agnostic. Currently, traditional laboratory methods for soil analysis remain... J. Sanches , H. Fischer, M.C. De Almeida, C.K. Luvizzoto, C.E. Otoboni Download paper

Filter results4 paper(s) found.

1. Hybrid Fuzzy–pid Control for Variable-rate Center Pivot Irrigation: an Automation-driven Approach to Precision Water Management

Precision agriculture increasingly relies on advanced automation and intelligent control strategies to address the spatial and temporal variability of crop water requirements while minimizing resource consumption. Center pivot irrigation systems are widely deployed in large-scale farming operations; however, their conventional control architectures are typically based on fixed schedules or linear feedback laws, which are insufficient to handle the nonlinear dynamics, uncertainties, and disturbances... F.R. Jimenez Lopez, A. Jimenez, I.A. Ruge Ruge, D.Y. Garcia Ramirez

Download paper

2. Deep Learning-based Anomaly Detection System for Rice Crop Health Monitoring

Global food security relies heavily on the stable production of rice (Oryza sativa L.), yet cultivation remains vulnerable to various phytosanitary anomalies, including foliar diseases like Pyricularia and Rhynchosporium, scald, and abiotic stressors such as herbicide damage. Traditional agronomic management relies on visual scouting, which is inherently subjective, labor-intensive, and often leads to delayed interventions. This study proposes an automated, high-throughput solution for real-time... F.R. Jimenez Lopez, A. Jimenez, D.Y. Garcia Ramirez

Download paper

3. A Hardware Classification Matrix for Precision Agriculture: Structuring an On-Farm Living Lab in Brazilian Citrus and Sugarcane Systems

The consolidation of Precision Agriculture (PA) in Brazilian fields depends fundamentally on the physical infrastructure deployed on-farm, including sensors, actuators, embedded controllers, and implements. Although citrus and sugarcane represent pillars of São Paulo's agribusiness, the sector still lacks a systematized inventory that catalogues and classifies PA hardware effectively adopted across different producer profiles. Integrated into the Smart B100 Advanced Research Center... R. Rolon, H. Fischer, C.E. Otoboni, C.K. Luvizotto, M.C. De Almeida

4. Systematic Multi-criteria Assessment of Soil Analysis Technologies for an Agricultural Living Lab: Readiness Levels and Field Applicability for Citrus and Sugarcane Production

Precision Agriculture (PA) fundamentally depends on accurate and timely edaphic diagnostics for site-specific decision-making. Within the scope of the Smart B100 Advanced Research Center (CCD-SB100/IAC), funded by FAPESP, an agricultural Living Lab is being structured. While the project's initial focus includes citrus and sugarcane in São Paulo State, the foundational soil sensing technologies evaluated are crop-agnostic. Currently, traditional laboratory methods for soil analysis remain... J. Sanches , H. Fischer, M.C. De Almeida, C.K. Luvizzoto, C.E. Otoboni

Download paper