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Early Detection of Grape Stem Borer Using IoT

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Next Generation Information Processing System

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1162 ))

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Abstract

Grape stem borer is a serious threat to grapes due to its severe symptoms and loss of production. Traditional diagnosis of grape stem borer depends upon symptom identification, due to sensitivity limits of identification tools in vineyards. Grape stem borer prime indications are parching and sneering of affected branches. Recognition of the borer in early stages is a most challenging chore. This paper presents a novel system, utilizing sound sensor for detection of stem borer in grape vineyard using Internet of things. Foremost contribution of this work is a technique for early detection of stem borer pest based on IoT through an handheld device. The analytic solution detailed in this paper does not necessitate the farmer or any user to be an IoT expert in order to use it. The accuracy achieved for the identification of grape stem borer is higher than 90%. The system is envisioned to incorporate the significant advancements in communication technologies and wireless sensor networks.

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Acknowledgements

I extend my sincere thanks and contribution to Mr. Prashant Pawar and Mr. Boraste who helped us in this effort. It was possible due to their diligent guidance and motivation to carry out this research.

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Authors and Affiliations

  1. SNJB COE Chandwad, Research Scholar SGGS, Nanded, Maharastra, India

    Kainjan Sanghavi

  2. MGM COE, Nanded, Maharashtra, India

    A. M. Rajurkar

Authors
  1. Kainjan Sanghavi
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  2. A. M. Rajurkar
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Corresponding author

Correspondence to Kainjan Sanghavi .

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Dr. Babasaheb Ambedkar Technological University, Lonere, Maharashtra, India

    Prachi Deshpande

  2. Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  3. Department of Electronics and Telecommunication Engineering, Dr. Babasaheb Ambedkar Technological University, Lonere, Maharashtra, India

    Brijesh Iyer

  4. School of Information Science and Engineering, University of Jinan, Jinan, Shandong, China

    Kun Ma

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Sanghavi, K., Rajurkar, A.M. (2021). Early Detection of Grape Stem Borer Using IoT. In: Deshpande, P., Abraham, A., Iyer, B., Ma, K. (eds) Next Generation Information Processing System. Advances in Intelligent Systems and Computing, vol 1162 . Springer, Singapore. https://doi.org/10.1007/978-981-15-4851-2_22

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