Abstract
The high demand of information and communication technology (ICT) in agriculture applications has led to the introduction of the concept of smart farming. In this respect, moving from the main features of the Fourth Industrial Revolution (Industry 4.0) promoted by the European Community, new approaches have been suggested and adopted in agriculture, giving rise to the so-called Agriculture 4.0. Improvements in automation, advanced information systems and Internet technologies allow for farmers to increase the productivity and to allocate the resources reasonably. For these reasons, agricultural decision support systems (DSS) for Agriculture 4.0 have become a very interesting research topic. DSS are interactive tools that enable users to make informed decisions about unstructured problems, and can be either fully computerized, human or a combination of both. In general, a DSS analyzes and synthesizes large amounts of data to assist in decision making. This paper presents an innovative decision support system solution to address the issues faced by coconut oil producers in making strategic decisions, particularly in the comparison of different methods of oil extraction. In more detail, the adopted methodology describes how to address the problems of coconut oil extraction in order to minimize the processing time and processing cost and to obtain energy savings. To this end, the coconut oil extraction process of the Leão São Tomé and Principe Company is presented as a case study: a DSS instance that analyzes the problem of the optimal selection between two different oil coconut extraction methods (fermentation-based and standard extraction processes) is developed as a meta-heuristics with a mixed integer linear programming problem. The obtained results show that there is clearly a trade-off between the increase in cost and reliability that the decision-maker may be willing to evaluate. In this respect, the proposed model provides a tool to support the decision-maker in choosing the best combination between the two different coconut oil extraction methods. The proposed DSS has been tested in a real application context through an experimental campaign.
Highlights
This section focuses on the application of the decision-making approach (1) by accounting for, as the case study, the fermentation-based coconut oil extraction process used within the company Leão São Tomé and Principe Company and the standard extraction process
The system boundaries involved in this study are the processing phases for the extraction of coconut oil described in Section 2.2.1: coconut harvest, coconut preparation, coconut pulp powdering, nock pulp dehydration, dried pulp pressing and filtering
The inputs computed as in (5)–(7); The maximum allowed total processing time (TiMAX ); The maximum allowed total cost (CiMAX ); The maximum allowed total energy consumption (ECiMAX ); The processing time (TCi ) and energy (ET) costs; if we indicate with Obj the value of the objective function computed for the fermentationbased extraction process (i = 1) and the standard one (i = 2), the results reported in Table 4 were obtained by solving the optimization problem (1)
Summary
Agriculture 1.0 refers to a traditional approach that is mainly based on manpower and animal forces and where simple tools (e.g., sickles, mattocks, etc.) are used. At this stage, the crop productivity is at a low level. In the 20th century, Agriculture 3.0 emerged thanks to the introduction of information and communication technologies (ICT). In this respect, process automation and robotic techniques allow us to perform operations efficiently: the various production tasks can be repeated in cycles and the production processes can be efficiently monitored in order to prevent system and machine failures [3]. The main aims of this revolution are related to the introduction of automation and digital technologies (Internet of things—IoT [4], big data, artificial intelligence [5], cloud computing, remote sensing [6], wireless sensor network (WSN) [7,8], etc.)
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