A Novel Integrated Expert System Modelling Approach for Sugarcane Management

Abstract

Statistics in Pakistan show that sugarcane, cultivated in tropical and subtropical areas, produced 1.9 billion tons in 2020, achieving the highest position in the world. The existing practices and processes of sugarcane management are lacking in lack of efficiency and effectiveness, which are time-consuming and wasteful, wastage of money with improper management, creating issues of conflicts among farmers, workers, and mill administration. To overcome this significant concern, there is a dire need for an intelligent management system that could integrate the various tools, techniques, and technologies to achieve the objectives of adequate information for making rational decisions by minimizing time, cost, and optimizing the utilization of resources. The Phases of the study include: firstly, acquiring the Knowledge about the problem domain, i.e., Sugarcane Management System’s key factors, tools, and techniques, as well as SWOT (Strengths Weakness Opportunity Threat) analysis to identify the gap. In the second phase, to analyze and find priorities of the key factors and criteria weights through AHP (Analytical Hierarchy Process). Thirdly, to model the whole knowledge in different forms, like Decision Table, Weight Allocation Table, Decision Tree, and Conceptual Model etc. Finally, developing a prototype Rule-Based Expert System named ESFSMS (Expert System for Sugarcane Management System) and testing the proposed model through ESFSMS. The final report shows that the aggregate weight of all the factors equals 0.9995, which is nearly equal to 1.00, i.e., the goal. It is limited to a few factors, which can be extended in further research studies and the usage of modern techniques.