CROP: Cluster-Based Routing Using Optimized Framework for IoT-Based Precision Agriculture

The advancements in the field of the Internet of Things (IoT) have fueled technological advancements in remotely handling agricultural operations, as well as the successful implementation of Precision Agriculture (PA) around the world. In this paper, we present Cluster-based Routing using an Optimized framework for Precision agricultural monitoring (CROP) that uses the recently developed Sooty Tern Optimization Algorithm (STOA). CROP specifically aims to detect unauthenticated entry into the agricultural field and various other factors related to PA. We perform a simulation analysis of CROP, and the performance of CROP is overwhelming, as it not only enhances stability period and network longevity by 58.9% and 65.5% respectively, but also proves to be scalable as compared to the Fuzzy-C-Means (FCM) algorithm and other routing protocols pertaining to PA.