An Intelligent Irrigation System and Prediction of Environmental Weather Based on Nano Electronics and Internet of Things Devices

Abstract

Internet of Things (IoT) shows a significant aspect in day-to-day life like Health monitoring, Environmental monitoring, vehicle monitoring, crop monitoring, material science and other applications. The proposed method objective is to monitor the environmental factors periodically on analysing the data collected from sensors and Nano electronics devices. IoT dependent smart irrigation system could aids in attaining the optimal resource utilization in the precise farming. The proposed system intelligence depends on smarter algorithm that considers sensed data with weather forecast parameters such as moisture, air temperature, humidity, precipitation in near future. Primarily, the input data is acquired from sensors placed at transmitter side that is connected to microcontroller and attained data is thus stored in the cloud paradigm from which the data is monitored and processed for making further decision. At the side of receiver module, the data collected is thus preprocessed. The features are extracted using Adaptive Fisher discriminant analysis. The optimum best features were chosen by employing optimization process with the help of multi-strategic gradient Salp swarm optimization (MSG-SSOA). Finally, the Deep residual LeNet classifier is employed for the classification of sensed data. Consequently, for the effectual performance assessment of suggested strategy the existing methods are related with proposed methods to validate the proposed system effectiveness.