IoT-Based Cotton Plant Pest Detection and Smart-Response System

IoT technology and drones are indeed a step towards modernization. Everything from field monitoring to pest identification is being conducted through these technologies. In this paper, we consider the issue of smart pest detection and management of cotton plants which is an important crop for an agricultural country. We proposed an IoT framework to detect insects through motion detection sensors and then receive an automatic response using drones based targeted spray. In our proposed method, we also explored the use of drones to improve field surveillance and then proposed a predictive algorithm for a pest detection response system using a decision-making theory. To validate the working behavior of our framework, we have included the simulation results of the tested scenarios in the cup-carbon IoT simulator. The purpose of our work is to modernize pest management so that farmers can not only attain higher profits but can also increase the quantity and quality of their crops.

Automated summary

In this paper, an IoT framework is proposed for the smart pest detection and management of cotton plants using drones. The framework uses motion detection sensors for insect detection and drones for targeted spray. A predictive algorithm is also proposed for optimizing the pest detection response system. The simulation results validate the effectiveness of the framework in modernizing pest management for higher profits and improved crop quality and quantity.