Cite this DOI

SharathKumar KR, Mohan K, & Nirisha (2020). Arecanut Crop Disease Prediction using IoT and Machine Learning. *Journal of Science & Technology*, *5*(3). https://doi.org/10.46243/jst.2020.v5.i3.pp160-165

@article{sharathkumarkr2020arecanut,
  author    = {SharathKumar KR and Mohan K and Nirisha},
  title     = {{Arecanut Crop Disease Prediction using IoT and Machine Learning}},
  journal   = {Journal of Science \& Technology},
  year      = {2020},
  month     = {may},
  volume    = {5},
  number    = {3},
  publisher = {Longman Publishers},
  issn      = {2456-5660},
  doi       = {10.46243/jst.2020.v5.i3.pp160-165},
  url       = {https://doi.org/10.46243/jst.2020.v5.i3.pp160-165},
  language  = {en},
  abstract  = {A prevailing recession in the agricultural goods sector is evident from the present scarcity and lack of food supplies. A major reason for this scarcity is the inherent growth of diseases in essential crops. A major development is thus required in this field for avoiding these problems in the future. This development is intended to simplify the management tasks of different roles in agricultural industries. A proper intimation of the importance of disease prediction and environmental factors must be done to the less aware farmers. To address these challenges, we have proposed a disease prediction system that takes into consideration temperature (°C), humidity(\%), rainfall(cm), wind flow(m/s) and soil moisture (\%) around the region of crop and developed a model to predict the occurrence of disease. This system will provide information prior to the occurrence of disease by analyzing different relationships among environmental factors.}
}

TY  - JOUR
TI  - Arecanut Crop Disease Prediction using IoT and Machine Learning
AU  - SharathKumar KR
AU  - Mohan K
AU  - Nirisha
JO  - Journal of Science & Technology
PY  - 2020
DA  - 2020/05/29/
VL  - 5
IS  - 3
PB  - Longman Publishers
SN  - 2456-5660
LA  - en
AB  - A prevailing recession in the agricultural goods sector is evident from the present scarcity and lack of food supplies. A major reason for this scarcity is the inherent growth of diseases in essential crops. A major development is thus required in this field for avoiding these problems in the future. This development is intended to simplify the management tasks of different roles in agricultural industries. A proper intimation of the importance of disease prediction and environmental factors must be done to the less aware farmers. To address these challenges, we have proposed a disease prediction system that takes into consideration temperature (°C), humidity(%), rainfall(cm), wind flow(m/s) and soil moisture (%) around the region of crop and developed a model to predict the occurrence of disease. This system will provide information prior to the occurrence of disease by analyzing different relationships among environmental factors.
DO  - 10.46243/jst.2020.v5.i3.pp160-165
UR  - https://doi.org/10.46243/jst.2020.v5.i3.pp160-165
ER  -

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    "type": "article-journal",
    "id": "10.46243/jst.2020.v5.i3.pp160-165",
    "DOI": "10.46243/jst.2020.v5.i3.pp160-165",
    "URL": "https://doi.org/10.46243/jst.2020.v5.i3.pp160-165",
    "title": "Arecanut Crop Disease Prediction using IoT and Machine Learning",
    "source": "Smart Scholars DOI Registry",
    "container-title": "Journal of Science & Technology",
    "author": [
        {
            "family": "SharathKumar KR"
        },
        {
            "family": "Mohan K",
            "ORCID": "https://orcid.org/0009-0002-7687-9798"
        },
        {
            "family": "Nirisha"
        }
    ],
    "issued": {
        "date-parts": [
            [
                2020,
                5,
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    "volume": "5",
    "issue": "3",
    "publisher": "Longman Publishers",
    "language": "en",
    "abstract": "A prevailing recession in the agricultural goods sector is evident from the present scarcity and lack of food supplies. A major reason for this scarcity is the inherent growth of diseases in essential crops. A major development is thus required in this field for avoiding these problems in the future. This development is intended to simplify the management tasks of different roles in agricultural industries. A proper intimation of the importance of disease prediction and environmental factors must be done to the less aware farmers. To address these challenges, we have proposed a disease prediction system that takes into consideration temperature (°C), humidity(%), rainfall(cm), wind flow(m/s) and soil moisture (%) around the region of crop and developed a model to predict the occurrence of disease. This system will provide information prior to the occurrence of disease by analyzing different relationships among environmental factors.",
    "ISSN": "2456-5660"
}

From the record as registered (version 2) — the record and its history. Programs: https://registry.smartscholars.in/api.php?action=cite&doi=10.46243%2Fjst.2020.v5.i3.pp160-165 gives all four in one JSON answer.