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Carvalho, A.L
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Authors
Avelar, R
dos Reis Silva, F.O
Carvalho, A.L
Alves Soares, F.M
Santana, C.C
Carvalho, A.L
Santana, C.C
Avelar, R
Silva, F.D
Soares, F
Soares, F
Santana, C.C
Avelar, R
Silva, F.O
Carvalho, A.L
Topics
Agricultural Robotics, Automation, and Mechanization
Predictive Modeling, Phenotyping, and Digital Tools for Decision Support
Remote and Proximal Sensing of Soils and Crops
Type
Poster
Year
2026
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1. Development of a System for Intelligent Plant Monitoring and Cultivation

Cultivation in protected environments and indoor systems requires continuous monitoring. Labor shortages and delays in management decisions compromise productivity, uniformity, and efficiency. Assessments of plant stand, vegetative vigor, nutritional status, and the incidence of pests and diseases still rely on visual inspections conducted over limited periods, reducing diagnostic accuracy and response time. Although automation technologies are advancing in horticultural production, available... R. Avelar, F.O. Dos Reis Silva, A.L. Carvalho, F.M. Alves Soares, C.C. Santana

2. Development and Validation of a Low-Cost IoT-Based Weather Station Using LoRa Communication for Precision Agriculture

Access to accurate local meteorological data remains a critical bottleneck for precision agriculture adoption among small and medium-scale Brazilian farmers. Commercial weather stations cost between R$ 15,000 and R$ 50,000, while public networks such as INMET operate with average inter-station spacing of 30–50 km, insufficient to capture the microclimate variability that drives field-scale irrigation and crop management decisions. This study presents the development, field validation, and... A.L. Carvalho, C.C. Santana, R. Avelar, F.D. Silva, F. Soares

3. Maturity Monitoring in Chickpea Using RGB Images Obtained by UAVs

Chickpea is a legume of great importance for global food security, and precise maturity monitoring is fundamental to optimize harvest timing and reduce grain losses. Remote sensing using unmanned aerial vehicles (UAVs) equipped with RGB cameras offers a non-destructive and high-throughput alternative for crop phenotyping, enabling rapid and reliable assessments of maturation progression. In this context, this study aimed to identify the best vegetation index based on RGB aerial images to monitor... F. Soares, C.C. Santana, R. Avelar, F.O. Silva, A.L. Carvalho