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Article

An IoT-Based System for Efficient Detection of Cotton Pest

1
Department of Computer Science, Federal Urdu University of Arts, Science and Technology, Karachi 75300, Pakistan
2
Faculty of Computer and Information Systems, Islamic University, Medina 42351, Saudi Arabia
3
Department of Computer Science and IT, Sir Syed University of Engineering and Technology, Karachi 75300, Pakistan
4
Department of Computer Science, University of Karachi, Karachi 75270, Pakistan
*
Author to whom correspondence should be addressed.
Appl. Sci. 2023, 13(5), 2921; https://doi.org/10.3390/app13052921
Submission received: 5 January 2023 / Revised: 19 February 2023 / Accepted: 20 February 2023 / Published: 24 February 2023

Abstract

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

Share and Cite

MDPI and ACS Style

Azfar, S.; Nadeem, A.; Ahsan, K.; Mehmood, A.; Siddiqui, M.S.; Saeed, M.; Ashraf, M. An IoT-Based System for Efficient Detection of Cotton Pest. Appl. Sci. 2023, 13, 2921. https://doi.org/10.3390/app13052921

AMA Style

Azfar S, Nadeem A, Ahsan K, Mehmood A, Siddiqui MS, Saeed M, Ashraf M. An IoT-Based System for Efficient Detection of Cotton Pest. Applied Sciences. 2023; 13(5):2921. https://doi.org/10.3390/app13052921

Chicago/Turabian Style

Azfar, Saeed, Adnan Nadeem, Kamran Ahsan, Amir Mehmood, Muhammad Shoaib Siddiqui, Muhammad Saeed, and Mohammad Ashraf. 2023. "An IoT-Based System for Efficient Detection of Cotton Pest" Applied Sciences 13, no. 5: 2921. https://doi.org/10.3390/app13052921

APA Style

Azfar, S., Nadeem, A., Ahsan, K., Mehmood, A., Siddiqui, M. S., Saeed, M., & Ashraf, M. (2023). An IoT-Based System for Efficient Detection of Cotton Pest. Applied Sciences, 13(5), 2921. https://doi.org/10.3390/app13052921

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