A Novel IoT-Based Smart and Security System Model for Large Scale Farm Sustainability

Abstract

The security and automation of work for large scale farm became major problem. Across the globe small scale farm have many techniques to implements but for large scale farm the technical data need to be analyzed for proper implementation of work. The main problem in farming is farming conditions now a days are unpredictable due to environment changes. Hence, we need to observe the environmental conditions for at least 3-years and save the data regarding rainfall and sunlight, O2 and CO2 levels etc. By analyzing such things, the framing can be improved. In this paper, a land near Amaravathi is considered and observed the conditions of soil moisture and prepared a data for further analysis of the study. Smart and Security (SAS) is the most important measure for all the farms to grow substantially. In this paper, the idea of involving Internet of Things (IoT), Global System for Mobile communication (GSM) Module, Global Positioning System (GPS) modules provide security and updated information of the specification to the farmer. Fingerprint based entry system into the farm helps to improve the security. The main objective is to help farmers in monitoring the entire farm land with the help of internet in hand and achieve important updates like soil moisture, temperature is sent to mobile via GSM module for every hour. The entire data collected from the sensors is updated in the cloud server. A dataset is created in the cloud server and will be further utilized for other farms. The articles present a smart and secure monitoring system for large agriculture farm by utilizing both hardware and software systems. A machine learning technique, i.e., deep convolutional neural network is utilized for the development and implementation of proposed model. The parameters like accuracy, sensitivity and specificity have been evaluated to know the performance of proposed model. The proposed model achieved an accuracy of 94.2% which is more efficient when compared to other existing techniques. The entire process has been simulated in MATLAB software tool.