A Conceptual Model of Farm Management Information System for Decision Support
In a today economy, it is crucial to have systems able to handle information with precision. In addition, it is also important to apply technological innovations in the various domains, with the objective to modernize and transform them to become more com
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University “Politehnica” of Bucharest, Faculty of Automatic Control and Computer Science, Bucharest, Romania 2 Centre of Technology and Systems, CTS, UNINOVA, 2829-516 Caparica, Portugal {burlacu_george85,dan_popescu_2002}@yahoo.com, {rddc,jfss,rg}@uninova.pt
Abstract. In a today economy, it is crucial to have systems able to handle information with precision. In addition, it is also important to apply technological innovations in the various domains, with the objective to modernize and transform them to become more competitive. In this paper, a conceptual framework for a Farm Management Information System (FMIS) is presented. It is focused in the different ways of using the information coming from various sources as sensors to assist farmers in decision making of agriculture business. Keywords: Ontology, Management Information System, Data Acquisition.
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Introduction
Precision agriculture is a modern method to make agriculture, which refers to optimizing the production through the fusion of traditional mechanized agriculture procedures with new technologies such as monitoring systems, command & control systems, geographical location systems and support information systems. These optimizations have the aim of choosing the right time for culture seeding, at the right place and monitoring the culture throughout the growth period, depending on the various parameters. Precision agriculture uses various tools for collecting information such as soil quality sampling, remote field sensing and yield monitoring. Optimization focuses on increasing yields, reducing cultivation costs and minimizing environmental impacts [1]. The challenges that precision agriculture tries to overcome are: - Automatic collection of the related information about the physical structure and chemical composition of the soil; - Development of a well-structured database, which should be integrated in GIS (Geographical Information Systems); - Development of intelligent agricultural machinery for farm working with high degree of spatial accuracy; - Nutrients distribution in variable doses required for uniform plants growth, in order to compensate the unevenness of soil characteristics; L.M. Camarinha-Matos et al. (Eds.): DoCEIS 2014, IFIP AICT 423, pp. 47–54, 2014. © IFIP International Federation for Information Processing 2014
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- Pesticides applications have to take into consideration the nature of existing pests and weeds in crops [2]; - Making crop productivity maps in real time based on flow sensors mounted in combine hopper that harvested grain [3]; - Making electrical conductivity distribution maps of soil. These maps provide an overview of water distribution and concentration in soil [4]. Traditional agriculture uses a variety of techniques to improve land quality in order to make it suitable for planting. This includes using animal manure and digging water-channels for field’s irrigation. Modern agriculture uses technologies for plant breeding and pesticides and fertilizers optimization.
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Relationship to Collectiv
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