Advanced Digital Platform for Agricultural Risk Management

This paper presents a robust system for agricultural risk management based on semantic knowledge and decision-making processes at farm scale. Thus, in order to anticipate, avoid and react to shocks arising from negative externalities that may occur during a production process, the method has been st...

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Bibliographic Details
Published in2022 IEEE 16th International Conference on Semantic Computing (ICSC) pp. 299 - 306
Main Author Cruvinel, Paulo E.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.2022
Subjects
agricultural risk
big data
Cloud computing
Crops
Electric shock
intelligent systems
Plants (biology)
Production
semantic computation
Semantics
Statistical analysis
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DOI10.1109/ICSC52841.2022.00056

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Summary:This paper presents a robust system for agricultural risk management based on semantic knowledge and decision-making processes at farm scale. Thus, in order to anticipate, avoid and react to shocks arising from negative externalities that may occur during a production process, the method has been structured using algorithms that enable not only an efficient agricultural management, but also a rational use of inputs in the crop management phase. The processing services have been implemented on a cloud computing infrastructure, being specific for geo-spatialized agricultural applications, i. e., involving large amounts of data and analytics. For the validation case studies were considered based on corn crop cycles (Zea Mays. L.) under rainfed conditions, two of them in the normal harvest period and the third in the off-season period, using the concept related to Research-on-Farm.
DOI:10.1109/ICSC52841.2022.00056