Please use this identifier to cite or link to this item: https://repositorio.fei.edu.br/handle/FEI/3392
Title: Leveraging digital knowledge ecosystem framework implementation: Case study: Aligning knowledge management and innovation goals for agricultural aerial pest control
Authors: GATTAZ, C. C.
BERNARDES, R. C.
CRUVINEL, P. E.
Issue Date: 24-Mar-2016
Abstract: This article puts forward a process model for information gathering, planning and execution for decision making in relation to thetechnological approach in agricultural pest control. The proposed model was tested on aerial application of pesticides for pestcontrol. In here, we propose a methodology based on action–research for implementation of a business, system, and technologymodel to assist and facilitate the collaborative use of resources and expertise, as well as to adjust one solution based on techno-logical knowledge and management. A case study on pest control on agricultural landscapes in Brazil is presented to illustrate theresults of this action–research approach in three different contexts. Its relevance may be measured by its benefits captured by thesharing of information within the networks, to facilitate the flows from information collected to improve the perception from theenvironment in the form of collective intelligence, so as to compare with previous cases stored in the knowledgebase, forformulation of action planning. Such arrangements pave the way for non-linear methods replacing attempts at objectivity, linearthought and control, as well as risks consideration to be integrated into a social computing system. The results demonstrate that suchcommand-and-control system could be expanded for deployment in other sectors related to agriculture.
Keywords: knowledge ecosystem framework
Journal: 2016 IEEE Tenth International Conference on Semantic Computing (ICSC)
ISSN: 2529-7392
Citation: GATTAZ, C. C.; BERNARDES, R. C.; CRUVINEL, P. E. Leveraging digital knowledge ecosystem framework implementation: Case study: Aligning knowledge management and innovation goals for agricultural aerial pest control. 2016 IEEE Tenth International Conference on Semantic Computing (ICSC). v. 2, n. 3, p. 1950001-1 - 1950001-11, 2019.
Access Type: Acesso Restrito
DOI: 10.1109/ICSC.2016.81
URI: https://repositorio.fei.edu.br/handle/FEI/3392
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