SVM-Guided Dynamic Routing for Post-Harvest Quality Preservation in Smart Warehouses with IoT
K. Umamaheswari, Deepu Rajan, Jayabharathi Ramasamy, Senthil Kumar Seeni, R. Meenakshi, R. Thamizhamuthu
Abstract
This research presents a new approach to smart warehouse quality preservation after harvest by combining the Internet of Things (IoT) with Support Vector Machine (SVM)-guided dynamic routing. Preserving the quality of harvested goods during storage and transportation is of utmost importance in today's agricultural supply chain. Critical characteristics like temperature and humidity are monitored using real-time data acquired from sensors via the IoT. It uses the SVM algorithm to optimize the items' route dynamically according to the changing environmental conditions. The adaptable and efficient flow of agricultural goods throughout the warehouse is guaranteed by this dynamic routing method, which is led by SVM decision-making. A number of aspects that impact quality preservation, the method lessen the possibility of degradation during transit and storage. The effectiveness of the suggested strategy is supported by simulation findings, which demonstrate better preservation of post-harvest quality in comparison to conventional approaches. Smart warehouses may benefit greatly from the combination of SVM and the IoT, which solves many problems in the agricultural supply chain and helps improve sustainable postharvest management.