An Ensemble Classification Model for Crop Recommendation with Edge Computing

Smart farming may be defined as a farming practise that uses the thought process of modern technology to increase the number and quality of agricultural products. Edge-based smart farming is a system designed solely for the monitoring of crops in the field using sensors and automating the irrigation system to meet our demands. Old cloud-based systems that rely heavily on IoT models are incapable of handling traffic and also knowledge information. As a result, there seems to be reduced latency, longer battery life for IoT devices, lots of cost-effective money-based information management, access to knowledge management and AI, cubic centimetres. So, in this paper we propose an algorithm Ensembled Enabled Edge computing algorithm for developing a smart farming system for crop recommendation in better way for getting best result and compared with some of the existing base classifiers like SVM and Naïve-Bayes in which the proposed algorithm gave the best accuracy when compared with the exisiting classifiers i.e., 91%.