CV Lattes
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Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Agrícola (FEAGRI) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Bachelor's at Agricultural Engineering from State University of Campinas (1984), Master's at Electric Engineering (Operations Research) from State University of Campinas (1989) and PhD at Agricultural Engineering (Decision Support Systems) from Cranfield University (1995). Since 2006, Associate Professor in Data Mining at the School of Agricultural Engineering at the State University of Campinas. I have experience in Intelligent Decision Support Systems, mainly KDD (Knowledge Discovery in Databases), Expert Systems and Fuzzy Logic. Coordinator of the Graduate Program in Agricultural Engineering at University of Campinas (Jul/2013 to Jul/2015). Winner of the "Zeferino Vaz" UNICAMP Award in 2012. Since 2015, Coordenator of a Node in Brazil for the Network BigDSSAgro, coordinated by Lleida University, Spain, under the CYTED. Group Member of an IberoAmerican Research Project (AgIoT: Agricultural Internet of Things and Data Analytics to Make Better Decisions), sponsored by CYTED (2021-2025), coordenated by Prof. Diego Dujovne (Chile). (Source: Lattes Curriculum)
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For the agricultural planning of sugarcane crop, it is necessary to understand the relationship between the crop yield and the production environment, management performed, climate, and variety and maturity of the plant. Currently, the most widely used yield estimates are subjective; experts perform this work based on their experience and field evaluations. There are two crop yield predic…
The current status of the internet of things not only allows for the farmer to improve his decision-making process but also for studies to unravel characteristics of crops through intensive monitoring of environmental conditions and their growth. For instance, the growth of tomato plants is affected by instant and average temperatures and by temperatures above and below optimum. Thus, mon…
The availability of microelectronics and low-cost sensors simplifies the development of systems capable of acquiring, processing and modeling various factors inside a greenhouse. One of such sensors is the camera, which can be used to identify fruits, diseases, and pests in crops. In this work, an image acquisition and processing system will be implemented with the objective of identifyin…
Dynamic crop growth models combined with the vast body of available data have been seen as part of the response to the problem of a more resource efficient Agriculture. Although such models require calibration steps without which their predictive performance may be insufficient to aid in decision making, real-time monitoring may circumvent this need. Dynamic models and satellite images ha…
Data Mining and Knowledge Discovery in Databases (KDD) are fields of knowledge relatively recent and it is increasing its use by academic community. In Agricultural Science, Data Mining has been considered an important alternative due to technological advances during last years. These technological advances have been allowing increasing data collection and storage; furthermore, there are …
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