An IoT-Based System for Efficient Detection of Cotton Pest

Considering the importance of cotton products, timely identification pests (flying moths—being a significant threat to crops) helps protect crops and improve their production quality. This study proposes real-time detection Cotton Flying Moths (CFMs) with assistance an Internet Things (IoT)-based system in agricultural field. The proposed prototype contains group sharp infrared sensors, Zigbee-based communication module, Arduino 2560 Mega board, lithium polymer battery (to power mote), gateway device, unmanned aerial vehicle (UAV) respond as pesticide-sprayer against detected pest. pest algorithm detects flying insects’ presence by monitoring variations reflected light. Based on this, it sends alert device. device coordinates drone/UAV spraying pesticide region. A real testbed simulation scenarios were implemented evaluate effectiveness system. results implementation suggest sensor design CFM detection. Initial from indicate suitability deployment would not only help minimize use pesticides but also maintain quality quantity products. originality this is custom-made cost-effective IoT for