An Artificial Neural Network-Based Pest Identification and Control in Smart Agriculture Using Wireless Sensor Networks

Kamred Udham Singh, Ankit Kumar, Linesh Raja, Vikas Kumar, Alok Kumar Singh Kushwaha, Neeraj Vashney, Manoj Chhetri

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Despite living in a rural country, farmers in India face several challenges. Every year, they suffer significant losses due to agricultural insect infestation. These losses are primarily the result of inadequate field surveillance, crop diseases, and ineffective pesticide management. We need cutting-edge technology that is constantly evolving to maintain control over such major concerns responsible for output reductions year after year. Wireless sensor networks address all of these issues; in fact, wireless sensor network technology is quickly becoming the backbone of modern precision agriculture. We propose a strategy for pest monitoring using wireless sensor networks in this study by simply recognizing insect behaviour using various sensors. We proposed a rapid and accurate insect detection and categorization approach based on five important crops and associated insect pests. This method examines insect behaviour by collecting data from sensors placed in the field. The results show that the proposed work improves the accuracy of the existing work by 3.9 percent.

Original languageEnglish
Article number5801206
JournalJournal of Food Quality
Volume2022
DOIs
Publication statusPublished - 2022

All Science Journal Classification (ASJC) codes

  • Food Science
  • Safety, Risk, Reliability and Quality

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