Enhancing Fruit and Vegetable Preservation with Support Vector Machine and IoT Connectivity
D. Satyaraj, T. Prabakaran, Y M Blessy, L.N. Jayanthi, S K Mouleeswaran, S. Velmurugan
Abstract
This paper presents a new method for extending the shelf life of perishable food items by combining the use of Support Vector Machine (SVM) algorithms with Internet of Things (IoT) connection. Problems with early spoiling detection and inefficient storage condition control plague conventional approaches to fruit and vegetable preservation. Using SVM it analyze environmental variables including humidity, temperature, and gas concentrations that impact commodities with a near-term expiration date in real time via this research. Sensors, actuators, and a command centre can all communicate to one other without a hitch thanks to the IoT. With this integration, storage conditions may be dynamically adjusted according to SVM predictions, guaranteeing the best possible preservation. In light of the ever-changing nature of farming, the suggested system provides an adaptable and scalable answer to the growing need for effective and environmentally friendly food storage solutions. The experimental findings show that the suggested method may prolong the freshness and quality of produce while reducing the amount of resources wasted. The findings of this study will help bring data-driven technology into the food business more widely and improve smart agriculture practices. It highlights the efficacy of combining IoT connection with SVM algorithms for vegetables and fruits storage. Agricultural operations and customers may both profit from the results, which show a considerable decrease in waste, an increase in freshness, and better quality control.