Implementation of Smart Indoor Agriculture System and Predictive Analysis

Abstract

Day by day Indoor Agricultural system is becoming more popular and enhancing agricultural productivity. Smart agriculture systems call on different type of Internet of Things (IOT) capabilities to improve farming production and deliver new monitoring facilities. In Smart agriculture system, sensors are placed within the ground may record real-time data on soil moisture, temperature and pH. The main challenges of a smart agriculture system are the integration of these sensors and tying the sensor data to the analytics driving automation and response activities. When integrated, the use of data analytics can reduce the overall cost of agriculture and contribute to higher production from the same amount of area through precise control of water, fertilizer and light. The aim of this paper is to develop an automatic decision making system to watering, lighting and airing the plants based on sensor data. Finally, the paper gives an idea of a prediction formula to find the value of the sensors which will reduce the cost of the sensor