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Fuzzy Rule based Effective Prediction of Crop using WSN & IOT


Affiliations
1 Department of Computer Science and Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, TamilNadu, India
     

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The objective of Fuzzy Rule based effective prediction of crop using WSN & IOT is to predict the high yielding crop effectively. IoT plays major role in agriculture to connect the values obtained by the sensors with the Internet remotely to give accurate prediction of crop. Initially, temperature of the atmosphere and humidity of the soil is measured by temperature sensors and humidity sensors respectively. These values are used as input variables for predicting the climate. These input variables are evaluated by fuzzy rules which use Fuzzy Associative Mapping. After predicting the climate, list of crops to be grown for predicted climate can be generated using knowledge base. Then, Effective list of crops to be grown for predicted climate and pH value of the soil obtained by pH Sensor is generated using fuzzy equation. Finally, the effective list of crop to be grown is sent to the corresponding land owners as SMS. Sensors are coordinated using GPS and are connected to the base station using WLAN. Fuzzy rules are used to increases the prediction accuracy and reduces the false negatives.


Keywords

IoT, Sensors, Fuzzy Rules, Prediction.
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  • Fuzzy Rule based Effective Prediction of Crop using WSN & IOT

Abstract Views: 215  |  PDF Views: 2

Authors

S. Sangeetha
Department of Computer Science and Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, TamilNadu, India

Abstract


The objective of Fuzzy Rule based effective prediction of crop using WSN & IOT is to predict the high yielding crop effectively. IoT plays major role in agriculture to connect the values obtained by the sensors with the Internet remotely to give accurate prediction of crop. Initially, temperature of the atmosphere and humidity of the soil is measured by temperature sensors and humidity sensors respectively. These values are used as input variables for predicting the climate. These input variables are evaluated by fuzzy rules which use Fuzzy Associative Mapping. After predicting the climate, list of crops to be grown for predicted climate can be generated using knowledge base. Then, Effective list of crops to be grown for predicted climate and pH value of the soil obtained by pH Sensor is generated using fuzzy equation. Finally, the effective list of crop to be grown is sent to the corresponding land owners as SMS. Sensors are coordinated using GPS and are connected to the base station using WLAN. Fuzzy rules are used to increases the prediction accuracy and reduces the false negatives.


Keywords


IoT, Sensors, Fuzzy Rules, Prediction.