SmartCane – Backend-Driven Digital Solution with AI/ML Insights

Abstract

Sugar industries commonly depend on disconnected systems and manual procedures to manage key operations such as production monitoring, inventory control, farmer coordination, and financial activities. This fragmented approach often results in inefficiencies, inconsistent data handling, and delays in decision-making processes. To overcome these limitations, this paper introduces a Unified Platform for Sugar Factory Management that integrates and automates both industrial and agricultural operations within a single system. The platform includes modules for farmer and land registration, sugarcane supply monitoring, soil testing services, payment and subsidy management, as well as communication features for meetings and election processes.

To enhance system functionality, advanced technologies such as machine learning and artificial intelligence are incorporated. Predictive models are utilized to estimate sugarcane yield by analyzing environmental and agricultural factors, while an AI-powered chatbot provides farmers with real-time guidance and support. Additionally, tools like the Smart Plantation Planner assist in efficient resource management by calculating seedling requirements based on land area.

The proposed system enhances transparency, minimizes human errors, and provides real-time access to data, enabling more informed decision-making. Experimental observations demonstrate improvements in operational efficiency, reduction in processing time, and better coordination between farmers and factory authorities. The platform is scalable, economical, and well-suited for small to medium-scale sugar industries, thereby promoting higher productivity and sustainable agricultural practices.