Prospects of Automation Agents in Agribusiness (Hop Industry) Decision Support Systems Related to Production, Marketing and Education
Author(s) -
Martín Pavlovic,
Fotis N. Koumboulis
Publication year - 2010
Publication title -
intech ebooks
Language(s) - English
Resource type - Book series
DOI - 10.5772/39454
Subject(s) - hop (telecommunications) , agribusiness , automation , production (economics) , business , marketing , industrial organization , engineering , economics , telecommunications , geography , agriculture , microeconomics , mechanical engineering , archaeology
Difficulty for decision making in modern agribusiness has increased significantly, since it involves a large number of strongly interrelated factors that affect the satisfaction of the performance criteria describing product quality, production timing and cost. In addition, decision making has to take into account regulations and restrictions concerning the safety of the personnel, the environmental protection and the energy saving. Moreover, agriculture is becoming more commercialized, as farmers are competing with other farmers all over the world. To face these challenges modern agricultural practices must be adopted; however, they require appropriately educated and informed farmers (Abdon & Raab, 2004). So, the question is how to provide the required knowledge and information to farmers, even to those without a high education level. A powerful tool to circumvent these difficulties is the technological area of agroinformatics and concerns the use of Information Management and Decision Support Systems (IMDSS). They aim to monitoring all functions of an agricultural process and facilitating decision making by proposing scenarios towards satisfying specific performance criteria and restrictions. IMDSS may perform several operations: monitoring the agricultural process, action planning and proposal of scenarios, processing of measurement data to extract information regarding the production cost and the product quality, fault diagnosis and alarm management. Decision Support Systems (DSS) have been extensively used in industrial applications to support the human-supervisor decisions regarding assurance of efficient and safe processes operation (Lambert et al., 1999; Sanchez et al., 1996). The degree of automation in decision making is the major factor of differentiation between DSS. The DSS characterized by the lower degree of automation simply facilitate decision making by offering information to the operator; in an upper stage DSS incorporate decision-making units that simply propose actions without the jurisdiction of activation. DSS classified in the highest degree of
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