Redirigiendo al acceso original de articulo en 19 segundos...
Inicio  /  Agriculture  /  Vol: 14 Par: 1 (2024)  /  Artículo
ARTÍCULO
TITULO

Applying Remote Sensing, Sensors, and Computational Techniques to Sustainable Agriculture: From Grain Production to Post-Harvest

Dágila Melo Rodrigues    
Paulo Carteri Coradi    
Newiton da Silva Timm    
Michele Fornari    
Paulo Grellmann    
Telmo Jorge Carneiro Amado    
Paulo Eduardo Teodoro    
Larissa Pereira Ribeiro Teodoro    
Fábio Henrique Rojo Baio and José Luís Trevizan Chiomento    

Resumen

In recent years, agricultural remote sensing technology has made great progress. The availability of sensors capable of detecting electromagnetic energy and/or heat emitted by targets improves the pre-harvest process and therefore becomes an indispensable tool in the post-harvest phase. Therefore, we outline how remote sensing tools can support a range of agricultural processes from field to storage through crop yield estimation, grain quality monitoring, storage unit identification and characterization, and production process planning. The use of sensors in the field and post-harvest processes allows for accurate real-time monitoring of operations and grain quality, enabling decision-making supported by computer tools such as the Internet of Things (IoT) and artificial intelligence algorithms. This way, grain producers can get ahead, track and reduce losses, and maintain grain quality from field to consumer.

 Artículos similares