Automated Pest Detection and Control in Agriculture using IoT and Image Processing

Abstract

This paper explores the development and application of an innovative Automated Pest Detection and Control System (APDCS) in agriculture, leveraging Internet of Things (IoT) technology and advanced image processing techniques. The primary aim of this research is to provide a sustainable, efficient, and cost-effective solution to the challenge of pest management in agricultural settings, reducing reliance on manual labor and chemical pesticides. By integrating IoT sensors and devices with cutting-edge image recognition algorithms, the proposed system is designed to automatically detect and identify various agricultural pests in real-time. The methodology encompasses the design of the APDCS, including the selection and deployment of suitable IoT hardware (such as cameras and environmental sensors), and the development of a robust image processing model capable of accurately identifying pests from captured images. A pilot study was conducted in a controlled agricultural environment to evaluate the system's effectiveness, focusing on its detection accuracy, response time, and overall impact on pest control practices.

Key findings from the research demonstrate that the APDCS achieves high accuracy in pest detection, significantly reduces the time and labor involved in monitoring crops for pests, and has the potential to decrease pesticide use by enabling targeted pest control measures. These results suggest that the integration of IoT and image processing technologies offers a promising approach to modernizing and improving pest management strategies in agriculture. The implications of this study are far-reaching, indicating a shift towards more sustainable and technology-driven agriculture practices. By highlighting the system's success in automating pest detection and control, the research contributes valuable insights into the potential for similar technologies to address other challenges in agriculture, paving the way for further innovation in the sector.