Proceedings of the First International Conference on Computing, Communication and Control System, I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India

Research Article

Design of Intelligent Insect Monitoring System Using Deep Learning Techniques

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  • @INPROCEEDINGS{10.4108/eai.7-6-2021.2308788,
        author={V.Ceronmani  Sharmila and Neeraj  Chauhan and Rajdeep  Kumar and Suraj Kumar Barwal},
        title={Design of Intelligent Insect Monitoring System Using Deep Learning Techniques},
        proceedings={Proceedings of the First International Conference on Computing, Communication and Control System, I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India},
        publisher={EAI},
        proceedings_a={I3CAC},
        year={2021},
        month={6},
        keywords={insect or pest classification algorithm insect or pest detection algorithm machine learning cnn algorithm k-means clustering algorithm},
        doi={10.4108/eai.7-6-2021.2308788}
    }
    
  • V.Ceronmani Sharmila
    Neeraj Chauhan
    Rajdeep Kumar
    Suraj Kumar Barwal
    Year: 2021
    Design of Intelligent Insect Monitoring System Using Deep Learning Techniques
    I3CAC
    EAI
    DOI: 10.4108/eai.7-6-2021.2308788
V.Ceronmani Sharmila1,*, Neeraj Chauhan1, Rajdeep Kumar1, Suraj Kumar Barwal1
  • 1: Hindustan Institute of Technology and Science, No.1, Rajiv Gandhi Salai, OMR, Chennai-603103
*Contact email: csharmila@hindustanuniv.ac.in

Abstract

The agriculture field is growing up its potential to better the demand of food and delivers healthy and nutritious foodstuff. This project presents an insect or pest detection and classification for the plant using machine learning. It’s a challenging part for the farmers to the crops which are acquiring defective and the degree or grade of excellence is also getting reduced day by day due to various pest or insect attacks. Earlier insect identification has been a big issue due to not well-skilled taxonomists to name the insects based on surface structure construction features accurately. Here, the proposed system will be a research tool for the study of early insects on the plants and leaves which will classify it using CNN and K-Means Clustering algorithm in machine learning. The detection analysis of insects was executed with shorter computational point in time for wang dataset using insect image Median Filter. The final classification results of accuracy were utilized to identify the pest and insects in the earliest period and increased the period to grow the harvest fertility and crop degree of excellence in the field of agriculture.