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  2. Volume 7, Issue 4
  3. Authors

Online ISSN: 2515-8260

Volume7, Issue4

Prediction of the Crop Cultivating using Resembling and IoT Techniques in Agricultural Fields for Increasing Productivity

    Anant Ram Rakesh Kumar

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 50-53

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Abstract

The agriculture plays a prevailing job in the development of the nation's economy. Atmosphere and other natural changes has become a significant danger in the agribusiness field. AI is a fundamental methodology for accomplishing viable and viable answers for this issue. Harvest Prediction includes anticipating the best output from accessible authentic information like climate parameters and soil parameters. This recommender system uses real time data as input to the machine learning. The sensors collect data from the soil and send that data to the cloud (firebase). Then the machine learning model retrieves that data and predicts the best crop and sends that crop to the cloud. We develop an android application which retrieves the sensor values from the cloud and displays them. This forecasting facilitates the farmer to forecast the best crop earlier than cultivating onto the agriculture field, which in turn increases the productivity.
Keywords:
    Machine Learning IoT Sensors prediction Best crop
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(2020). Prediction of the Crop Cultivating using Resembling and IoT Techniques in Agricultural Fields for Increasing Productivity. European Journal of Molecular & Clinical Medicine, 7(4), 50-53.
Anant Ram; Rakesh Kumar. "Prediction of the Crop Cultivating using Resembling and IoT Techniques in Agricultural Fields for Increasing Productivity". European Journal of Molecular & Clinical Medicine, 7, 4, 2020, 50-53.
(2020). 'Prediction of the Crop Cultivating using Resembling and IoT Techniques in Agricultural Fields for Increasing Productivity', European Journal of Molecular & Clinical Medicine, 7(4), pp. 50-53.
Prediction of the Crop Cultivating using Resembling and IoT Techniques in Agricultural Fields for Increasing Productivity. European Journal of Molecular & Clinical Medicine, 2020; 7(4): 50-53.
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