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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Postolache, O. (2023). Smart Systems and AI for Precision Agriculture. International Conference on Sensing Technology.
Exportar Referência (IEEE) 
O. A. Postolache,  "Smart Systems and AI for Precision Agriculture", in Int. Conf. on Sensing Technology, 2023
Exportar BibTeX 
@misc{postolache2023_1777358163530,
	author = "Postolache, O.",
	title = "Smart Systems and AI for Precision Agriculture",
	year = "2023",
	url = "https://icst.bits-hyderabad.ac.in/"
}
Exportar RIS 
TY  - CPAPER
TI  - Smart Systems and AI for Precision Agriculture
T2  - International Conference on Sensing Technology
AU  - Postolache, O.
PY  - 2023
UR  - https://icst.bits-hyderabad.ac.in/
AB  - The precision agriculture (PA) combines technologies and practices that assure the optimization of the operations associated agricultural production through specific farm management. 
Regarding the employed technologies distributed smart sensing systems characterized by fixed and mobile nodes (based on remote sensing  and Unnamed Aerial Vehicle (UAV))) are used to turn the farming operations into data, and to optimize the future operation based on data driven models. Edge and cloud computing platforms that are capable to run AI/ML algorithms may contribute to help on human decisions. This new mode to act in agriculture based on digital transformation through the  combination of technologies such as smart sensors, cloud and mobile computing, data science is related to the fact that classical decisions cannot be applied nowadays when the cultivated areas are much extended, and the adverse meteorological events are occurring frequently that conduct to miss-management with yield losses. 
In this talk we’ll see together the meaning of precision agriculture in the context of heavily uncertainty associated with climate change. The IoT ecosystem technologies for precision agriculture will be discussed including multimodal sensing and artificial intelligence. Referring to the sensing in-situ and remote sensing are considered special attention being granted to the soil characteristics (moisture and macronutrients concentration). The agriculture UAV imagery and satellite  imagery solutions as so as the relation between the data coming from the smart sensors distributed in the field and acquired images using multispectral imagery techniques will be part of the presentation. Metrological characteristics of smart sensors as so as the test and calibration procedure for in-situ and remote measurement smart sensing systems will be part of the talk.
 Another important technology associated with innovative precision agriculture is related to development of AI data driven models for farming operations considering data coming from different source Examples of data driven models for smart irrigation and nutrients delivery will be considered. for an increased crops quality will be discussed. 

ER  -