| Full text | |
| Author(s): |
Cruvinel, Paulo E.
;
IEEE
Total Authors: 2
|
| Document type: | Journal article |
| Source: | 16TH IEEE INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING (ICSC 2022); v. N/A, p. 8-pg., 2022-01-01. |
| Abstract | |
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. (AU) | |
| FAPESP's process: | 17/19350-2 - Advanced digital tool for the agricultural risk management |
| Grantee: | Paulo Estevão Cruvinel |
| Support Opportunities: | Research Grants - Research Partnership for Technological Innovation - PITE |