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Intelligent system to improve the sustainability of oil palm crops through the construction of forecasting maps
online resourceposted on 23.01.2020, 15:17 by Alejandro PenaAlejandro Pena, Mario GongoraMario Gongora, Isis BonetIsis Bonet, Fabio CaraffiniFabio Caraffini
The Oil Palm is considered by de Colombian Government as one of the main agricultural products to promote the substitution of illegal crops and for job creation in the countryside for a sustainable peace process evolution. To improve the sustainability of this crop, the RSPO (Roundtable on Sustainable Palm Oil) has established principles to reduce the use of pesticides, fertilizers and fires, as well as fair treatment of land and workers according to local and international labour rights. This project aims to develop an intelligent system to improve the sustainability of this crop in Colombia, using novel adaptive vegetation indices obtained from multispectral aerial views. This will be integrated into a forecasting map using Computational Intelligence concepts, to achieve international standards that support the development of oil palm crops in Colombia, both at small and medium scale. Further to this, an additional goal of the agreement between universities and industry is the creation of a novel service to improve the sustainability of oil palm crops in a study zone based in information systems and technologies in precision agriculture, which can further be extended to improve the sustainability of this crop in other places where it is grown as an alternative to existing crops. The role of the partners neatly complements each other. In this way, the industry partner, Unipalma of the Llanos will validate the model in a real environment. The Institute of Artificial Intelligence (IAI) located in De Montfort University, is the academic partner that provides advice regarding the implementation of the Intelligent System as a service. EIA University will execute the field research activities related to image capture and processing, the implementation and validation of the intelligence system in a simulated and real environment.