Comparative Study of Camera- and Sensor-Based Traps for Insect Pest Monitoring Applications

Effective insect pest remote monitoring is critical for precision agriculture as it facilitates timely pest detection and management strategies. This study conducts a comparative anal-ysis of camera-based and sensor-based traps by evaluating their suitability for real-time monitoring and data collection in agricul-ture fields. By examining the strengths and limitations of each approach, this research highlights the potential of integrating camera-based systems with sensors and wireless communication technologies. These integrated traps, leveraging image processing, AI algorithms, and IoT technologies, contribute to sustainable agricultural practices by enabling targeted interventions and reducing the need for indiscriminate pesticide use. The study discusses the potential benefits of trap network development, providing cost-effectiveness and statistical efficacy, highlights the importance of advancing detection algorithms, and integrating data analytics for proactive and precise pest management in the context of precision agriculture.