Genetic Algorithm based Internet of Precision Agricultural Things (IopaT) for Agriculture 4.0

The development of IoT is increasing in our daily life. Its applications are now becoming famous in rural areas also, such as Agriculture 4.0. Cheap sensors, climate data, soil information, and drones are now used to solve many real-time problems. One of the most emerging topics in the IoT in the Agriculture field is IoT based precision agriculture. The range of IoT applications can range between water spraying from drone, soil recommendation for different crops, weather prediction and recommendation for water supply, etc. In this paper we propose a system that will recommend whether water is needed or not by predicting the rain fall using Genetic Algorithm. In this article, we proposed a unique decision making method to predict Rainfall using Genetic Algorithm (GA) to identify the necessity of manual water supply is needed or not. The sensor based system will be activated to check wheather the GA based system completes its prediction correctly or not by sensing moisture level from the soil. If the moisture level of the soil crosses the pre-defined threshold value then plant watering is performed by quadrotor UAV. A terrace gardening system is also implemented in this article, which uses a pump for water spraying. Various atmospheric parameters help to develop a rainfall prediction system to enhance efficiancy more than 80% in the proposed IopaT system to make the system more interoperable. (C) 2020 Elsevier B.V. All rights reserved.

Automated summary

This article introduces a unique system in the field of IoT agriculture applications, using genetic algorithm to predict rainfall and recommend watering. The system verifies predictions by monitoring soil moisture levels to enhance system efficiency.