A NOVEL APPROACH FOR SMART INTELLIGENT GREENHOUSE SYSTEM TO ENHANCE THE ECONOMICAL GROWTH OF AGRICULTURE

People's desire for the processes and performance of greenhouse farm commodities are continuously enhancing, to successfully fulfill their need for vegetable greenhouse monitorin gowing to the country's rapid agricultural development. The crops inside a greenhouse are protected from adverse conditions such as wind, hail, and UV radiation because it is an enclosed framework. This work is largely focused on improving present agricultural methods through the adoption of effective techniques to increase production. A framework of a smart greenhouse that enables farmers to take up farming activities remotely with less need for extensive physical examination is developed. Relying on remote sensing data and ZigBee technologies, this research developed a smart intelligent greenhouse platform. We could achieve remote monitoring of crops withtechnology; EHA-CNN (Enhanced Hybrid AdaBoost and convolutional neural network) is employed to detect the GH-parameter. The collected datasets are pre?processed for noise removal by employing the random oversampling and under-sampling approach with EHA-CNN approach for effective prediction. This approach has an incalculable impact on boosting the economic expansion of agricultural farming because of the profit generated by reliability. To demonstrate the validity of our study, we compare the proposed method to state-of-the-art solutions and examine its performance metrics. The findings of the proposed technique are expressed in a graphical format by employing the MATLAB tool