EFFICIENT PESTICIDE SPRAYING USING CLOUD BASED MULTI-ROBOT SYSTEM

Abstract

This thesis investigates the development and implementation of a cloud-based multi-robot system designed for efficient pesticide spraying in agricultural fields. Leveraging communication technologies such asWiFi, Bluetooth, LoRa, and Zigbee, the system aims to address the inefficiencies and health risks associated with traditional pesticide application methods. By utilizing a network of robots equipped with these advanced communication protocols, our approach ensures precise and targeted pesticide application, thereby reducing waste and mitigating environmental impact. The research involved extensive experimentation to evaluate the performance of various communication protocols, focusing on parameters such as range, reliability, and power consumption. Our findings highlight LoRa technology as particularly advantageous for agricultural applications due to its long-range capabilities and low power requirements. The integration of cloud computing further optimizes the system by enabling real-time data analysis and decision-making, enhancing overall efficiency. Results from our study demonstrate that the proposed multi-robot system significantly enhances the accuracy and efficiency of pesticide spraying compared to conventional methods. This work contributes to the field of precision agriculture by offering a scalable and robust solution for automated pest control. Future research will explore the integration of additional sensors for comprehensive crop health monitoring and the application of machine learning algorithms for dynamic path planning and system optimization.